rust/src/rustllvm/PassWrapper.cpp

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// Copyright 2013 The Rust Project Developers. See the COPYRIGHT
// file at the top-level directory of this distribution and at
// http://rust-lang.org/COPYRIGHT.
//
// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
// http://www.apache.org/licenses/LICENSE-2.0> or the MIT license
// <LICENSE-MIT or http://opensource.org/licenses/MIT>, at your
// option. This file may not be copied, modified, or distributed
// except according to those terms.
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#include <stdio.h>
#include <vector>
#include <set>
#include "rustllvm.h"
#include "llvm/Analysis/TargetLibraryInfo.h"
#include "llvm/Analysis/TargetTransformInfo.h"
#include "llvm/IR/AutoUpgrade.h"
#include "llvm/IR/AssemblyAnnotationWriter.h"
#include "llvm/Support/CBindingWrapping.h"
#include "llvm/Support/FileSystem.h"
#include "llvm/Support/Host.h"
#include "llvm/Target/TargetMachine.h"
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#include "llvm/Transforms/IPO/PassManagerBuilder.h"
#if LLVM_VERSION_GE(6, 0)
#include "llvm/CodeGen/TargetSubtargetInfo.h"
#else
#include "llvm/Target/TargetSubtargetInfo.h"
#endif
#if LLVM_VERSION_GE(4, 0)
#include "llvm/Transforms/IPO/AlwaysInliner.h"
rustc: Implement ThinLTO This commit is an implementation of LLVM's ThinLTO for consumption in rustc itself. Currently today LTO works by merging all relevant LLVM modules into one and then running optimization passes. "Thin" LTO operates differently by having more sharded work and allowing parallelism opportunities between optimizing codegen units. Further down the road Thin LTO also allows *incremental* LTO which should enable even faster release builds without compromising on the performance we have today. This commit uses a `-Z thinlto` flag to gate whether ThinLTO is enabled. It then also implements two forms of ThinLTO: * In one mode we'll *only* perform ThinLTO over the codegen units produced in a single compilation. That is, we won't load upstream rlibs, but we'll instead just perform ThinLTO amongst all codegen units produced by the compiler for the local crate. This is intended to emulate a desired end point where we have codegen units turned on by default for all crates and ThinLTO allows us to do this without performance loss. * In anther mode, like full LTO today, we'll optimize all upstream dependencies in "thin" mode. Unlike today, however, this LTO step is fully parallelized so should finish much more quickly. There's a good bit of comments about what the implementation is doing and where it came from, but the tl;dr; is that currently most of the support here is copied from upstream LLVM. This code duplication is done for a number of reasons: * Controlling parallelism means we can use the existing jobserver support to avoid overloading machines. * We will likely want a slightly different form of incremental caching which integrates with our own incremental strategy, but this is yet to be determined. * This buys us some flexibility about when/where we run ThinLTO, as well as having it tailored to fit our needs for the time being. * Finally this allows us to reuse some artifacts such as our `TargetMachine` creation, where all our options we used today aren't necessarily supported by upstream LLVM yet. My hope is that we can get some experience with this copy/paste in tree and then eventually upstream some work to LLVM itself to avoid the duplication while still ensuring our needs are met. Otherwise I fear that maintaining these bindings may be quite costly over the years with LLVM updates!
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#include "llvm/Transforms/IPO/FunctionImport.h"
#include "llvm/Transforms/Utils/FunctionImportUtils.h"
#include "llvm/LTO/LTO.h"
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#if LLVM_VERSION_LE(4, 0)
#include "llvm/Object/ModuleSummaryIndexObjectFile.h"
#endif
#endif
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#include "llvm-c/Transforms/PassManagerBuilder.h"
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using namespace llvm;
using namespace llvm::legacy;
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extern cl::opt<bool> EnableARMEHABI;
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typedef struct LLVMOpaquePass *LLVMPassRef;
typedef struct LLVMOpaqueTargetMachine *LLVMTargetMachineRef;
DEFINE_STDCXX_CONVERSION_FUNCTIONS(Pass, LLVMPassRef)
DEFINE_STDCXX_CONVERSION_FUNCTIONS(TargetMachine, LLVMTargetMachineRef)
DEFINE_STDCXX_CONVERSION_FUNCTIONS(PassManagerBuilder,
LLVMPassManagerBuilderRef)
extern "C" void LLVMInitializePasses() {
PassRegistry &Registry = *PassRegistry::getPassRegistry();
initializeCore(Registry);
initializeCodeGen(Registry);
initializeScalarOpts(Registry);
initializeVectorization(Registry);
initializeIPO(Registry);
initializeAnalysis(Registry);
initializeTransformUtils(Registry);
initializeInstCombine(Registry);
initializeInstrumentation(Registry);
initializeTarget(Registry);
}
enum class LLVMRustPassKind {
Other,
Function,
Module,
};
static LLVMRustPassKind toRust(PassKind Kind) {
switch (Kind) {
case PT_Function:
return LLVMRustPassKind::Function;
case PT_Module:
return LLVMRustPassKind::Module;
default:
return LLVMRustPassKind::Other;
}
}
extern "C" LLVMPassRef LLVMRustFindAndCreatePass(const char *PassName) {
StringRef SR(PassName);
PassRegistry *PR = PassRegistry::getPassRegistry();
const PassInfo *PI = PR->getPassInfo(SR);
if (PI) {
return wrap(PI->createPass());
}
return nullptr;
}
extern "C" LLVMRustPassKind LLVMRustPassKind(LLVMPassRef RustPass) {
assert(RustPass);
Pass *Pass = unwrap(RustPass);
return toRust(Pass->getPassKind());
}
extern "C" void LLVMRustAddPass(LLVMPassManagerRef PMR, LLVMPassRef RustPass) {
assert(RustPass);
Pass *Pass = unwrap(RustPass);
PassManagerBase *PMB = unwrap(PMR);
PMB->add(Pass);
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}
rustc: Implement ThinLTO This commit is an implementation of LLVM's ThinLTO for consumption in rustc itself. Currently today LTO works by merging all relevant LLVM modules into one and then running optimization passes. "Thin" LTO operates differently by having more sharded work and allowing parallelism opportunities between optimizing codegen units. Further down the road Thin LTO also allows *incremental* LTO which should enable even faster release builds without compromising on the performance we have today. This commit uses a `-Z thinlto` flag to gate whether ThinLTO is enabled. It then also implements two forms of ThinLTO: * In one mode we'll *only* perform ThinLTO over the codegen units produced in a single compilation. That is, we won't load upstream rlibs, but we'll instead just perform ThinLTO amongst all codegen units produced by the compiler for the local crate. This is intended to emulate a desired end point where we have codegen units turned on by default for all crates and ThinLTO allows us to do this without performance loss. * In anther mode, like full LTO today, we'll optimize all upstream dependencies in "thin" mode. Unlike today, however, this LTO step is fully parallelized so should finish much more quickly. There's a good bit of comments about what the implementation is doing and where it came from, but the tl;dr; is that currently most of the support here is copied from upstream LLVM. This code duplication is done for a number of reasons: * Controlling parallelism means we can use the existing jobserver support to avoid overloading machines. * We will likely want a slightly different form of incremental caching which integrates with our own incremental strategy, but this is yet to be determined. * This buys us some flexibility about when/where we run ThinLTO, as well as having it tailored to fit our needs for the time being. * Finally this allows us to reuse some artifacts such as our `TargetMachine` creation, where all our options we used today aren't necessarily supported by upstream LLVM yet. My hope is that we can get some experience with this copy/paste in tree and then eventually upstream some work to LLVM itself to avoid the duplication while still ensuring our needs are met. Otherwise I fear that maintaining these bindings may be quite costly over the years with LLVM updates!
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extern "C"
bool LLVMRustPassManagerBuilderPopulateThinLTOPassManager(
LLVMPassManagerBuilderRef PMBR,
LLVMPassManagerRef PMR
) {
#if LLVM_VERSION_GE(4, 0)
unwrap(PMBR)->populateThinLTOPassManager(*unwrap(PMR));
return true;
#else
return false;
#endif
}
#ifdef LLVM_COMPONENT_X86
#define SUBTARGET_X86 SUBTARGET(X86)
#else
#define SUBTARGET_X86
#endif
#ifdef LLVM_COMPONENT_ARM
#define SUBTARGET_ARM SUBTARGET(ARM)
#else
#define SUBTARGET_ARM
#endif
#ifdef LLVM_COMPONENT_AARCH64
#define SUBTARGET_AARCH64 SUBTARGET(AArch64)
#else
#define SUBTARGET_AARCH64
#endif
#ifdef LLVM_COMPONENT_MIPS
#define SUBTARGET_MIPS SUBTARGET(Mips)
#else
#define SUBTARGET_MIPS
#endif
#ifdef LLVM_COMPONENT_POWERPC
#define SUBTARGET_PPC SUBTARGET(PPC)
#else
#define SUBTARGET_PPC
#endif
#ifdef LLVM_COMPONENT_SYSTEMZ
#define SUBTARGET_SYSTEMZ SUBTARGET(SystemZ)
#else
#define SUBTARGET_SYSTEMZ
#endif
#ifdef LLVM_COMPONENT_MSP430
#define SUBTARGET_MSP430 SUBTARGET(MSP430)
#else
#define SUBTARGET_MSP430
#endif
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#ifdef LLVM_COMPONENT_SPARC
#define SUBTARGET_SPARC SUBTARGET(Sparc)
#else
#define SUBTARGET_SPARC
#endif
#ifdef LLVM_COMPONENT_HEXAGON
#define SUBTARGET_HEXAGON SUBTARGET(Hexagon)
#else
#define SUBTARGET_HEXAGON
#endif
#define GEN_SUBTARGETS \
SUBTARGET_X86 \
SUBTARGET_ARM \
SUBTARGET_AARCH64 \
SUBTARGET_MIPS \
SUBTARGET_PPC \
SUBTARGET_SYSTEMZ \
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SUBTARGET_MSP430 \
SUBTARGET_SPARC \
SUBTARGET_HEXAGON
#define SUBTARGET(x) \
namespace llvm { \
extern const SubtargetFeatureKV x##FeatureKV[]; \
extern const SubtargetFeatureKV x##SubTypeKV[]; \
}
GEN_SUBTARGETS
#undef SUBTARGET
extern "C" bool LLVMRustHasFeature(LLVMTargetMachineRef TM,
const char *Feature) {
#if LLVM_RUSTLLVM
TargetMachine *Target = unwrap(TM);
const MCSubtargetInfo *MCInfo = Target->getMCSubtargetInfo();
const FeatureBitset &Bits = MCInfo->getFeatureBits();
const ArrayRef<SubtargetFeatureKV> FeatTable = MCInfo->getFeatureTable();
for (auto &FeatureEntry : FeatTable)
if (!strcmp(FeatureEntry.Key, Feature))
return (Bits & FeatureEntry.Value) == FeatureEntry.Value;
#endif
return false;
}
enum class LLVMRustCodeModel {
Other,
Small,
Kernel,
Medium,
Large,
None,
};
static CodeModel::Model fromRust(LLVMRustCodeModel Model) {
switch (Model) {
case LLVMRustCodeModel::Small:
return CodeModel::Small;
case LLVMRustCodeModel::Kernel:
return CodeModel::Kernel;
case LLVMRustCodeModel::Medium:
return CodeModel::Medium;
case LLVMRustCodeModel::Large:
return CodeModel::Large;
default:
report_fatal_error("Bad CodeModel.");
}
}
enum class LLVMRustCodeGenOptLevel {
Other,
None,
Less,
Default,
Aggressive,
};
static CodeGenOpt::Level fromRust(LLVMRustCodeGenOptLevel Level) {
switch (Level) {
case LLVMRustCodeGenOptLevel::None:
return CodeGenOpt::None;
case LLVMRustCodeGenOptLevel::Less:
return CodeGenOpt::Less;
case LLVMRustCodeGenOptLevel::Default:
return CodeGenOpt::Default;
case LLVMRustCodeGenOptLevel::Aggressive:
return CodeGenOpt::Aggressive;
default:
report_fatal_error("Bad CodeGenOptLevel.");
}
}
enum class LLVMRustRelocMode {
Default,
Static,
PIC,
DynamicNoPic,
ROPI,
RWPI,
ROPIRWPI,
};
static Optional<Reloc::Model> fromRust(LLVMRustRelocMode RustReloc) {
switch (RustReloc) {
case LLVMRustRelocMode::Default:
return None;
case LLVMRustRelocMode::Static:
return Reloc::Static;
case LLVMRustRelocMode::PIC:
return Reloc::PIC_;
case LLVMRustRelocMode::DynamicNoPic:
return Reloc::DynamicNoPIC;
#if LLVM_VERSION_GE(4, 0)
case LLVMRustRelocMode::ROPI:
return Reloc::ROPI;
case LLVMRustRelocMode::RWPI:
return Reloc::RWPI;
case LLVMRustRelocMode::ROPIRWPI:
return Reloc::ROPI_RWPI;
#else
default:
break;
#endif
}
report_fatal_error("Bad RelocModel.");
}
#if LLVM_RUSTLLVM
/// getLongestEntryLength - Return the length of the longest entry in the table.
///
static size_t getLongestEntryLength(ArrayRef<SubtargetFeatureKV> Table) {
size_t MaxLen = 0;
for (auto &I : Table)
MaxLen = std::max(MaxLen, std::strlen(I.Key));
return MaxLen;
}
extern "C" void LLVMRustPrintTargetCPUs(LLVMTargetMachineRef TM) {
const TargetMachine *Target = unwrap(TM);
const MCSubtargetInfo *MCInfo = Target->getMCSubtargetInfo();
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const Triple::ArchType HostArch = Triple(sys::getProcessTriple()).getArch();
const Triple::ArchType TargetArch = Target->getTargetTriple().getArch();
const ArrayRef<SubtargetFeatureKV> CPUTable = MCInfo->getCPUTable();
unsigned MaxCPULen = getLongestEntryLength(CPUTable);
printf("Available CPUs for this target:\n");
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if (HostArch == TargetArch) {
const StringRef HostCPU = sys::getHostCPUName();
printf(" %-*s - Select the CPU of the current host (currently %.*s).\n",
MaxCPULen, "native", (int)HostCPU.size(), HostCPU.data());
}
for (auto &CPU : CPUTable)
printf(" %-*s - %s.\n", MaxCPULen, CPU.Key, CPU.Desc);
printf("\n");
}
extern "C" void LLVMRustPrintTargetFeatures(LLVMTargetMachineRef TM) {
const TargetMachine *Target = unwrap(TM);
const MCSubtargetInfo *MCInfo = Target->getMCSubtargetInfo();
const ArrayRef<SubtargetFeatureKV> FeatTable = MCInfo->getFeatureTable();
unsigned MaxFeatLen = getLongestEntryLength(FeatTable);
printf("Available features for this target:\n");
for (auto &Feature : FeatTable)
printf(" %-*s - %s.\n", MaxFeatLen, Feature.Key, Feature.Desc);
printf("\n");
printf("Use +feature to enable a feature, or -feature to disable it.\n"
"For example, rustc -C -target-cpu=mycpu -C "
"target-feature=+feature1,-feature2\n\n");
}
#else
extern "C" void LLVMRustPrintTargetCPUs(LLVMTargetMachineRef) {
printf("Target CPU help is not supported by this LLVM version.\n\n");
}
extern "C" void LLVMRustPrintTargetFeatures(LLVMTargetMachineRef) {
printf("Target features help is not supported by this LLVM version.\n\n");
}
#endif
extern "C" LLVMTargetMachineRef LLVMRustCreateTargetMachine(
const char *TripleStr, const char *CPU, const char *Feature,
LLVMRustCodeModel RustCM, LLVMRustRelocMode RustReloc,
LLVMRustCodeGenOptLevel RustOptLevel, bool UseSoftFloat,
bool PositionIndependentExecutable, bool FunctionSections,
std: Add a new wasm32-unknown-unknown target This commit adds a new target to the compiler: wasm32-unknown-unknown. This target is a reimagining of what it looks like to generate WebAssembly code from Rust. Instead of using Emscripten which can bring with it a weighty runtime this instead is a target which uses only the LLVM backend for WebAssembly and a "custom linker" for now which will hopefully one day be direct calls to lld. Notable features of this target include: * There is zero runtime footprint. The target assumes nothing exists other than the wasm32 instruction set. * There is zero toolchain footprint beyond adding the target. No custom linker is needed, rustc contains everything. * Very small wasm modules can be generated directly from Rust code using this target. * Most of the standard library is stubbed out to return an error, but anything related to allocation works (aka `HashMap`, `Vec`, etc). * Naturally, any `#[no_std]` crate should be 100% compatible with this new target. This target is currently somewhat janky due to how linking works. The "linking" is currently unconditional whole program LTO (aka LLVM is being used as a linker). Naturally that means compiling programs is pretty slow! Eventually though this target should have a linker. This target is also intended to be quite experimental. I'm hoping that this can act as a catalyst for further experimentation in Rust with WebAssembly. Breaking changes are very likely to land to this target, so it's not recommended to rely on it in any critical capacity yet. We'll let you know when it's "production ready". --- Currently testing-wise this target is looking pretty good but isn't complete. I've got almost the entire `run-pass` test suite working with this target (lots of tests ignored, but many passing as well). The `core` test suite is still getting LLVM bugs fixed to get that working and will take some time. Relatively simple programs all seem to work though! --- It's worth nothing that you may not immediately see the "smallest possible wasm module" for the input you feed to rustc. For various reasons it's very difficult to get rid of the final "bloat" in vanilla rustc (again, a real linker should fix all this). For now what you'll have to do is: cargo install --git https://github.com/alexcrichton/wasm-gc wasm-gc foo.wasm bar.wasm And then `bar.wasm` should be the smallest we can get it! --- In any case for now I'd love feedback on this, particularly on the various integration points if you've got better ideas of how to approach them!
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bool DataSections,
bool TrapUnreachable,
bool Singlethread) {
auto OptLevel = fromRust(RustOptLevel);
auto RM = fromRust(RustReloc);
std::string Error;
Triple Trip(Triple::normalize(TripleStr));
const llvm::Target *TheTarget =
TargetRegistry::lookupTarget(Trip.getTriple(), Error);
if (TheTarget == nullptr) {
LLVMRustSetLastError(Error.c_str());
return nullptr;
}
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StringRef RealCPU = CPU;
if (RealCPU == "native") {
RealCPU = sys::getHostCPUName();
}
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TargetOptions Options;
Options.FloatABIType = FloatABI::Default;
if (UseSoftFloat) {
Options.FloatABIType = FloatABI::Soft;
}
Options.DataSections = DataSections;
Options.FunctionSections = FunctionSections;
if (TrapUnreachable) {
// Tell LLVM to translate `unreachable` into an explicit trap instruction.
// This limits the extent of possible undefined behavior in some cases, as
// it prevents control flow from "falling through" into whatever code
// happens to be laid out next in memory.
Options.TrapUnreachable = true;
}
std: Add a new wasm32-unknown-unknown target This commit adds a new target to the compiler: wasm32-unknown-unknown. This target is a reimagining of what it looks like to generate WebAssembly code from Rust. Instead of using Emscripten which can bring with it a weighty runtime this instead is a target which uses only the LLVM backend for WebAssembly and a "custom linker" for now which will hopefully one day be direct calls to lld. Notable features of this target include: * There is zero runtime footprint. The target assumes nothing exists other than the wasm32 instruction set. * There is zero toolchain footprint beyond adding the target. No custom linker is needed, rustc contains everything. * Very small wasm modules can be generated directly from Rust code using this target. * Most of the standard library is stubbed out to return an error, but anything related to allocation works (aka `HashMap`, `Vec`, etc). * Naturally, any `#[no_std]` crate should be 100% compatible with this new target. This target is currently somewhat janky due to how linking works. The "linking" is currently unconditional whole program LTO (aka LLVM is being used as a linker). Naturally that means compiling programs is pretty slow! Eventually though this target should have a linker. This target is also intended to be quite experimental. I'm hoping that this can act as a catalyst for further experimentation in Rust with WebAssembly. Breaking changes are very likely to land to this target, so it's not recommended to rely on it in any critical capacity yet. We'll let you know when it's "production ready". --- Currently testing-wise this target is looking pretty good but isn't complete. I've got almost the entire `run-pass` test suite working with this target (lots of tests ignored, but many passing as well). The `core` test suite is still getting LLVM bugs fixed to get that working and will take some time. Relatively simple programs all seem to work though! --- It's worth nothing that you may not immediately see the "smallest possible wasm module" for the input you feed to rustc. For various reasons it's very difficult to get rid of the final "bloat" in vanilla rustc (again, a real linker should fix all this). For now what you'll have to do is: cargo install --git https://github.com/alexcrichton/wasm-gc wasm-gc foo.wasm bar.wasm And then `bar.wasm` should be the smallest we can get it! --- In any case for now I'd love feedback on this, particularly on the various integration points if you've got better ideas of how to approach them!
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if (Singlethread) {
Options.ThreadModel = ThreadModel::Single;
}
#if LLVM_VERSION_GE(6, 0)
Optional<CodeModel::Model> CM;
#else
CodeModel::Model CM = CodeModel::Model::Default;
#endif
if (RustCM != LLVMRustCodeModel::None)
CM = fromRust(RustCM);
TargetMachine *TM = TheTarget->createTargetMachine(
Trip.getTriple(), RealCPU, Feature, Options, RM, CM, OptLevel);
return wrap(TM);
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}
extern "C" void LLVMRustDisposeTargetMachine(LLVMTargetMachineRef TM) {
delete unwrap(TM);
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}
// Unfortunately, LLVM doesn't expose a C API to add the corresponding analysis
// passes for a target to a pass manager. We export that functionality through
// this function.
extern "C" void LLVMRustAddAnalysisPasses(LLVMTargetMachineRef TM,
LLVMPassManagerRef PMR,
LLVMModuleRef M) {
PassManagerBase *PM = unwrap(PMR);
PM->add(
createTargetTransformInfoWrapperPass(unwrap(TM)->getTargetIRAnalysis()));
}
extern "C" void LLVMRustConfigurePassManagerBuilder(
LLVMPassManagerBuilderRef PMBR, LLVMRustCodeGenOptLevel OptLevel,
bool MergeFunctions, bool SLPVectorize, bool LoopVectorize) {
// Ignore mergefunc for now as enabling it causes crashes.
// unwrap(PMBR)->MergeFunctions = MergeFunctions;
unwrap(PMBR)->SLPVectorize = SLPVectorize;
unwrap(PMBR)->OptLevel = fromRust(OptLevel);
unwrap(PMBR)->LoopVectorize = LoopVectorize;
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}
// Unfortunately, the LLVM C API doesn't provide a way to set the `LibraryInfo`
// field of a PassManagerBuilder, we expose our own method of doing so.
extern "C" void LLVMRustAddBuilderLibraryInfo(LLVMPassManagerBuilderRef PMBR,
LLVMModuleRef M,
bool DisableSimplifyLibCalls) {
Triple TargetTriple(unwrap(M)->getTargetTriple());
TargetLibraryInfoImpl *TLI = new TargetLibraryInfoImpl(TargetTriple);
if (DisableSimplifyLibCalls)
TLI->disableAllFunctions();
unwrap(PMBR)->LibraryInfo = TLI;
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}
// Unfortunately, the LLVM C API doesn't provide a way to create the
// TargetLibraryInfo pass, so we use this method to do so.
extern "C" void LLVMRustAddLibraryInfo(LLVMPassManagerRef PMR, LLVMModuleRef M,
bool DisableSimplifyLibCalls) {
Triple TargetTriple(unwrap(M)->getTargetTriple());
TargetLibraryInfoImpl TLII(TargetTriple);
if (DisableSimplifyLibCalls)
TLII.disableAllFunctions();
unwrap(PMR)->add(new TargetLibraryInfoWrapperPass(TLII));
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}
// Unfortunately, the LLVM C API doesn't provide an easy way of iterating over
// all the functions in a module, so we do that manually here. You'll find
// similar code in clang's BackendUtil.cpp file.
extern "C" void LLVMRustRunFunctionPassManager(LLVMPassManagerRef PMR,
LLVMModuleRef M) {
llvm::legacy::FunctionPassManager *P =
unwrap<llvm::legacy::FunctionPassManager>(PMR);
P->doInitialization();
// Upgrade all calls to old intrinsics first.
for (Module::iterator I = unwrap(M)->begin(), E = unwrap(M)->end(); I != E;)
UpgradeCallsToIntrinsic(&*I++); // must be post-increment, as we remove
for (Module::iterator I = unwrap(M)->begin(), E = unwrap(M)->end(); I != E;
++I)
if (!I->isDeclaration())
P->run(*I);
P->doFinalization();
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}
extern "C" void LLVMRustSetLLVMOptions(int Argc, char **Argv) {
// Initializing the command-line options more than once is not allowed. So,
// check if they've already been initialized. (This could happen if we're
// being called from rustpkg, for example). If the arguments change, then
// that's just kinda unfortunate.
static bool Initialized = false;
if (Initialized)
return;
Initialized = true;
cl::ParseCommandLineOptions(Argc, Argv);
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}
enum class LLVMRustFileType {
Other,
AssemblyFile,
ObjectFile,
};
static TargetMachine::CodeGenFileType fromRust(LLVMRustFileType Type) {
switch (Type) {
case LLVMRustFileType::AssemblyFile:
return TargetMachine::CGFT_AssemblyFile;
case LLVMRustFileType::ObjectFile:
return TargetMachine::CGFT_ObjectFile;
default:
report_fatal_error("Bad FileType.");
}
}
extern "C" LLVMRustResult
LLVMRustWriteOutputFile(LLVMTargetMachineRef Target, LLVMPassManagerRef PMR,
LLVMModuleRef M, const char *Path,
LLVMRustFileType RustFileType) {
llvm::legacy::PassManager *PM = unwrap<llvm::legacy::PassManager>(PMR);
auto FileType = fromRust(RustFileType);
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std::string ErrorInfo;
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std::error_code EC;
raw_fd_ostream OS(Path, EC, sys::fs::F_None);
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if (EC)
ErrorInfo = EC.message();
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if (ErrorInfo != "") {
LLVMRustSetLastError(ErrorInfo.c_str());
return LLVMRustResult::Failure;
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}
unwrap(Target)->addPassesToEmitFile(*PM, OS, FileType, false);
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PM->run(*unwrap(M));
// Apparently `addPassesToEmitFile` adds a pointer to our on-the-stack output
// stream (OS), so the only real safe place to delete this is here? Don't we
// wish this was written in Rust?
delete PM;
return LLVMRustResult::Success;
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}
// Callback to demangle function name
// Parameters:
// * name to be demangled
// * name len
// * output buffer
// * output buffer len
// Returns len of demangled string, or 0 if demangle failed.
typedef size_t (*DemangleFn)(const char*, size_t, char*, size_t);
namespace {
class RustAssemblyAnnotationWriter : public AssemblyAnnotationWriter {
DemangleFn Demangle;
std::vector<char> Buf;
public:
RustAssemblyAnnotationWriter(DemangleFn Demangle) : Demangle(Demangle) {}
// Return empty string if demangle failed
// or if name does not need to be demangled
StringRef CallDemangle(StringRef name) {
if (!Demangle) {
return StringRef();
}
if (Buf.size() < name.size() * 2) {
// Semangled name usually shorter than mangled,
// but allocate twice as much memory just in case
Buf.resize(name.size() * 2);
}
auto R = Demangle(name.data(), name.size(), Buf.data(), Buf.size());
if (!R) {
// Demangle failed.
return StringRef();
}
auto Demangled = StringRef(Buf.data(), R);
if (Demangled == name) {
// Do not print anything if demangled name is equal to mangled.
return StringRef();
}
return Demangled;
}
void emitFunctionAnnot(const Function *F,
formatted_raw_ostream &OS) override {
StringRef Demangled = CallDemangle(F->getName());
if (Demangled.empty()) {
return;
}
OS << "; " << Demangled << "\n";
}
void emitInstructionAnnot(const Instruction *I,
formatted_raw_ostream &OS) override {
const char *Name;
const Value *Value;
if (const CallInst *CI = dyn_cast<CallInst>(I)) {
Name = "call";
Value = CI->getCalledValue();
} else if (const InvokeInst* II = dyn_cast<InvokeInst>(I)) {
Name = "invoke";
Value = II->getCalledValue();
} else {
// Could demangle more operations, e. g.
// `store %place, @function`.
return;
}
if (!Value->hasName()) {
return;
}
StringRef Demangled = CallDemangle(Value->getName());
if (Demangled.empty()) {
return;
}
OS << "; " << Name << " " << Demangled << "\n";
}
};
class RustPrintModulePass : public ModulePass {
raw_ostream* OS;
DemangleFn Demangle;
public:
static char ID;
RustPrintModulePass() : ModulePass(ID), OS(nullptr), Demangle(nullptr) {}
RustPrintModulePass(raw_ostream &OS, DemangleFn Demangle)
: ModulePass(ID), OS(&OS), Demangle(Demangle) {}
bool runOnModule(Module &M) override {
RustAssemblyAnnotationWriter AW(Demangle);
M.print(*OS, &AW, false);
return false;
}
void getAnalysisUsage(AnalysisUsage &AU) const override {
AU.setPreservesAll();
}
static StringRef name() { return "RustPrintModulePass"; }
};
} // namespace
namespace llvm {
void initializeRustPrintModulePassPass(PassRegistry&);
}
char RustPrintModulePass::ID = 0;
INITIALIZE_PASS(RustPrintModulePass, "print-rust-module",
"Print rust module to stderr", false, false)
extern "C" void LLVMRustPrintModule(LLVMPassManagerRef PMR, LLVMModuleRef M,
const char *Path, DemangleFn Demangle) {
llvm::legacy::PassManager *PM = unwrap<llvm::legacy::PassManager>(PMR);
2013-08-23 03:58:42 +00:00
std::string ErrorInfo;
2014-09-30 21:20:22 +00:00
std::error_code EC;
raw_fd_ostream OS(Path, EC, sys::fs::F_None);
2014-09-30 21:20:22 +00:00
if (EC)
ErrorInfo = EC.message();
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formatted_raw_ostream FOS(OS);
PM->add(new RustPrintModulePass(FOS, Demangle));
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PM->run(*unwrap(M));
}
extern "C" void LLVMRustPrintPasses() {
LLVMInitializePasses();
struct MyListener : PassRegistrationListener {
void passEnumerate(const PassInfo *Info) {
#if LLVM_VERSION_GE(4, 0)
StringRef PassArg = Info->getPassArgument();
StringRef PassName = Info->getPassName();
if (!PassArg.empty()) {
// These unsigned->signed casts could theoretically overflow, but
// realistically never will (and even if, the result is implementation
// defined rather plain UB).
printf("%15.*s - %.*s\n", (int)PassArg.size(), PassArg.data(),
(int)PassName.size(), PassName.data());
}
#else
if (Info->getPassArgument() && *Info->getPassArgument()) {
printf("%15s - %s\n", Info->getPassArgument(), Info->getPassName());
}
#endif
}
} Listener;
2013-08-23 03:58:42 +00:00
PassRegistry *PR = PassRegistry::getPassRegistry();
PR->enumerateWith(&Listener);
}
extern "C" void LLVMRustAddAlwaysInlinePass(LLVMPassManagerBuilderRef PMBR,
bool AddLifetimes) {
#if LLVM_VERSION_GE(4, 0)
unwrap(PMBR)->Inliner = llvm::createAlwaysInlinerLegacyPass(AddLifetimes);
#else
unwrap(PMBR)->Inliner = createAlwaysInlinerPass(AddLifetimes);
#endif
}
Implement LTO This commit implements LTO for rust leveraging LLVM's passes. What this means is: * When compiling an rlib, in addition to insdering foo.o into the archive, also insert foo.bc (the LLVM bytecode) of the optimized module. * When the compiler detects the -Z lto option, it will attempt to perform LTO on a staticlib or binary output. The compiler will emit an error if a dylib or rlib output is being generated. * The actual act of performing LTO is as follows: 1. Force all upstream libraries to have an rlib version available. 2. Load the bytecode of each upstream library from the rlib. 3. Link all this bytecode into the current LLVM module (just using llvm apis) 4. Run an internalization pass which internalizes all symbols except those found reachable for the local crate of compilation. 5. Run the LLVM LTO pass manager over this entire module 6a. If assembling an archive, then add all upstream rlibs into the output archive. This ignores all of the object/bitcode/metadata files rust generated and placed inside the rlibs. 6b. If linking a binary, create copies of all upstream rlibs, remove the rust-generated object-file, and then link everything as usual. As I have explained in #10741, this process is excruciatingly slow, so this is *not* turned on by default, and it is also why I have decided to hide it behind a -Z flag for now. The good news is that the binary sizes are about as small as they can be as a result of LTO, so it's definitely working. Closes #10741 Closes #10740
2013-12-03 07:19:29 +00:00
extern "C" void LLVMRustRunRestrictionPass(LLVMModuleRef M, char **Symbols,
size_t Len) {
llvm::legacy::PassManager passes;
auto PreserveFunctions = [=](const GlobalValue &GV) {
for (size_t I = 0; I < Len; I++) {
if (GV.getName() == Symbols[I]) {
return true;
}
}
return false;
};
passes.add(llvm::createInternalizePass(PreserveFunctions));
passes.run(*unwrap(M));
Implement LTO This commit implements LTO for rust leveraging LLVM's passes. What this means is: * When compiling an rlib, in addition to insdering foo.o into the archive, also insert foo.bc (the LLVM bytecode) of the optimized module. * When the compiler detects the -Z lto option, it will attempt to perform LTO on a staticlib or binary output. The compiler will emit an error if a dylib or rlib output is being generated. * The actual act of performing LTO is as follows: 1. Force all upstream libraries to have an rlib version available. 2. Load the bytecode of each upstream library from the rlib. 3. Link all this bytecode into the current LLVM module (just using llvm apis) 4. Run an internalization pass which internalizes all symbols except those found reachable for the local crate of compilation. 5. Run the LLVM LTO pass manager over this entire module 6a. If assembling an archive, then add all upstream rlibs into the output archive. This ignores all of the object/bitcode/metadata files rust generated and placed inside the rlibs. 6b. If linking a binary, create copies of all upstream rlibs, remove the rust-generated object-file, and then link everything as usual. As I have explained in #10741, this process is excruciatingly slow, so this is *not* turned on by default, and it is also why I have decided to hide it behind a -Z flag for now. The good news is that the binary sizes are about as small as they can be as a result of LTO, so it's definitely working. Closes #10741 Closes #10740
2013-12-03 07:19:29 +00:00
}
extern "C" void LLVMRustMarkAllFunctionsNounwind(LLVMModuleRef M) {
for (Module::iterator GV = unwrap(M)->begin(), E = unwrap(M)->end(); GV != E;
++GV) {
GV->setDoesNotThrow();
Function *F = dyn_cast<Function>(GV);
if (F == nullptr)
continue;
for (Function::iterator B = F->begin(), BE = F->end(); B != BE; ++B) {
for (BasicBlock::iterator I = B->begin(), IE = B->end(); I != IE; ++I) {
if (isa<InvokeInst>(I)) {
InvokeInst *CI = cast<InvokeInst>(I);
CI->setDoesNotThrow();
}
}
}
}
}
extern "C" void
LLVMRustSetDataLayoutFromTargetMachine(LLVMModuleRef Module,
LLVMTargetMachineRef TMR) {
TargetMachine *Target = unwrap(TMR);
unwrap(Module)->setDataLayout(Target->createDataLayout());
}
extern "C" void LLVMRustSetModulePIELevel(LLVMModuleRef M) {
unwrap(M)->setPIELevel(PIELevel::Level::Large);
}
rustc: Implement ThinLTO This commit is an implementation of LLVM's ThinLTO for consumption in rustc itself. Currently today LTO works by merging all relevant LLVM modules into one and then running optimization passes. "Thin" LTO operates differently by having more sharded work and allowing parallelism opportunities between optimizing codegen units. Further down the road Thin LTO also allows *incremental* LTO which should enable even faster release builds without compromising on the performance we have today. This commit uses a `-Z thinlto` flag to gate whether ThinLTO is enabled. It then also implements two forms of ThinLTO: * In one mode we'll *only* perform ThinLTO over the codegen units produced in a single compilation. That is, we won't load upstream rlibs, but we'll instead just perform ThinLTO amongst all codegen units produced by the compiler for the local crate. This is intended to emulate a desired end point where we have codegen units turned on by default for all crates and ThinLTO allows us to do this without performance loss. * In anther mode, like full LTO today, we'll optimize all upstream dependencies in "thin" mode. Unlike today, however, this LTO step is fully parallelized so should finish much more quickly. There's a good bit of comments about what the implementation is doing and where it came from, but the tl;dr; is that currently most of the support here is copied from upstream LLVM. This code duplication is done for a number of reasons: * Controlling parallelism means we can use the existing jobserver support to avoid overloading machines. * We will likely want a slightly different form of incremental caching which integrates with our own incremental strategy, but this is yet to be determined. * This buys us some flexibility about when/where we run ThinLTO, as well as having it tailored to fit our needs for the time being. * Finally this allows us to reuse some artifacts such as our `TargetMachine` creation, where all our options we used today aren't necessarily supported by upstream LLVM yet. My hope is that we can get some experience with this copy/paste in tree and then eventually upstream some work to LLVM itself to avoid the duplication while still ensuring our needs are met. Otherwise I fear that maintaining these bindings may be quite costly over the years with LLVM updates!
2017-07-23 15:14:38 +00:00
extern "C" bool
LLVMRustThinLTOAvailable() {
#if LLVM_VERSION_GE(4, 0)
return true;
#else
return false;
#endif
}
#if LLVM_VERSION_GE(4, 0)
// Here you'll find an implementation of ThinLTO as used by the Rust compiler
// right now. This ThinLTO support is only enabled on "recent ish" versions of
// LLVM, and otherwise it's just blanket rejected from other compilers.
//
// Most of this implementation is straight copied from LLVM. At the time of
// this writing it wasn't *quite* suitable to reuse more code from upstream
// for our purposes, but we should strive to upstream this support once it's
// ready to go! I figure we may want a bit of testing locally first before
// sending this upstream to LLVM. I hear though they're quite eager to receive
// feedback like this!
//
// If you're reading this code and wondering "what in the world" or you're
// working "good lord by LLVM upgrade is *still* failing due to these bindings"
// then fear not! (ok maybe fear a little). All code here is mostly based
// on `lib/LTO/ThinLTOCodeGenerator.cpp` in LLVM.
//
// You'll find that the general layout here roughly corresponds to the `run`
// method in that file as well as `ProcessThinLTOModule`. Functions are
// specifically commented below as well, but if you're updating this code
// or otherwise trying to understand it, the LLVM source will be useful in
// interpreting the mysteries within.
//
// Otherwise I'll apologize in advance, it probably requires a relatively
// significant investment on your part to "truly understand" what's going on
// here. Not saying I do myself, but it took me awhile staring at LLVM's source
// and various online resources about ThinLTO to make heads or tails of all
// this.
extern "C" bool
LLVMRustWriteThinBitcodeToFile(LLVMPassManagerRef PMR,
LLVMModuleRef M,
const char *BcFile) {
llvm::legacy::PassManager *PM = unwrap<llvm::legacy::PassManager>(PMR);
std::error_code EC;
llvm::raw_fd_ostream bc(BcFile, EC, llvm::sys::fs::F_None);
if (EC) {
LLVMRustSetLastError(EC.message().c_str());
return false;
}
PM->add(createWriteThinLTOBitcodePass(bc));
PM->run(*unwrap(M));
delete PM;
return true;
}
// This is a shared data structure which *must* be threadsafe to share
// read-only amongst threads. This also corresponds basically to the arguments
// of the `ProcessThinLTOModule` function in the LLVM source.
struct LLVMRustThinLTOData {
// The combined index that is the global analysis over all modules we're
// performing ThinLTO for. This is mostly managed by LLVM.
ModuleSummaryIndex Index;
// All modules we may look at, stored as in-memory serialized versions. This
// is later used when inlining to ensure we can extract any module to inline
// from.
StringMap<MemoryBufferRef> ModuleMap;
// A set that we manage of everything we *don't* want internalized. Note that
// this includes all transitive references right now as well, but it may not
// always!
DenseSet<GlobalValue::GUID> GUIDPreservedSymbols;
// Not 100% sure what these are, but they impact what's internalized and
// what's inlined across modules, I believe.
StringMap<FunctionImporter::ImportMapTy> ImportLists;
StringMap<FunctionImporter::ExportSetTy> ExportLists;
StringMap<GVSummaryMapTy> ModuleToDefinedGVSummaries;
};
// Just an argument to the `LLVMRustCreateThinLTOData` function below.
struct LLVMRustThinLTOModule {
const char *identifier;
const char *data;
size_t len;
};
// This is copied from `lib/LTO/ThinLTOCodeGenerator.cpp`, not sure what it
// does.
static const GlobalValueSummary *
getFirstDefinitionForLinker(const GlobalValueSummaryList &GVSummaryList) {
auto StrongDefForLinker = llvm::find_if(
GVSummaryList, [](const std::unique_ptr<GlobalValueSummary> &Summary) {
auto Linkage = Summary->linkage();
return !GlobalValue::isAvailableExternallyLinkage(Linkage) &&
!GlobalValue::isWeakForLinker(Linkage);
});
if (StrongDefForLinker != GVSummaryList.end())
return StrongDefForLinker->get();
auto FirstDefForLinker = llvm::find_if(
GVSummaryList, [](const std::unique_ptr<GlobalValueSummary> &Summary) {
auto Linkage = Summary->linkage();
return !GlobalValue::isAvailableExternallyLinkage(Linkage);
});
if (FirstDefForLinker == GVSummaryList.end())
return nullptr;
return FirstDefForLinker->get();
}
// The main entry point for creating the global ThinLTO analysis. The structure
// here is basically the same as before threads are spawned in the `run`
// function of `lib/LTO/ThinLTOCodeGenerator.cpp`.
extern "C" LLVMRustThinLTOData*
LLVMRustCreateThinLTOData(LLVMRustThinLTOModule *modules,
int num_modules,
const char **preserved_symbols,
int num_symbols) {
auto Ret = llvm::make_unique<LLVMRustThinLTOData>();
// Load each module's summary and merge it into one combined index
for (int i = 0; i < num_modules; i++) {
auto module = &modules[i];
StringRef buffer(module->data, module->len);
MemoryBufferRef mem_buffer(buffer, module->identifier);
Ret->ModuleMap[module->identifier] = mem_buffer;
2017-10-10 19:29:14 +00:00
#if LLVM_VERSION_GE(5, 0)
if (Error Err = readModuleSummaryIndex(mem_buffer, Ret->Index, i)) {
LLVMRustSetLastError(toString(std::move(Err)).c_str());
return nullptr;
}
#else
rustc: Implement ThinLTO This commit is an implementation of LLVM's ThinLTO for consumption in rustc itself. Currently today LTO works by merging all relevant LLVM modules into one and then running optimization passes. "Thin" LTO operates differently by having more sharded work and allowing parallelism opportunities between optimizing codegen units. Further down the road Thin LTO also allows *incremental* LTO which should enable even faster release builds without compromising on the performance we have today. This commit uses a `-Z thinlto` flag to gate whether ThinLTO is enabled. It then also implements two forms of ThinLTO: * In one mode we'll *only* perform ThinLTO over the codegen units produced in a single compilation. That is, we won't load upstream rlibs, but we'll instead just perform ThinLTO amongst all codegen units produced by the compiler for the local crate. This is intended to emulate a desired end point where we have codegen units turned on by default for all crates and ThinLTO allows us to do this without performance loss. * In anther mode, like full LTO today, we'll optimize all upstream dependencies in "thin" mode. Unlike today, however, this LTO step is fully parallelized so should finish much more quickly. There's a good bit of comments about what the implementation is doing and where it came from, but the tl;dr; is that currently most of the support here is copied from upstream LLVM. This code duplication is done for a number of reasons: * Controlling parallelism means we can use the existing jobserver support to avoid overloading machines. * We will likely want a slightly different form of incremental caching which integrates with our own incremental strategy, but this is yet to be determined. * This buys us some flexibility about when/where we run ThinLTO, as well as having it tailored to fit our needs for the time being. * Finally this allows us to reuse some artifacts such as our `TargetMachine` creation, where all our options we used today aren't necessarily supported by upstream LLVM yet. My hope is that we can get some experience with this copy/paste in tree and then eventually upstream some work to LLVM itself to avoid the duplication while still ensuring our needs are met. Otherwise I fear that maintaining these bindings may be quite costly over the years with LLVM updates!
2017-07-23 15:14:38 +00:00
Expected<std::unique_ptr<object::ModuleSummaryIndexObjectFile>> ObjOrErr =
object::ModuleSummaryIndexObjectFile::create(mem_buffer);
if (!ObjOrErr) {
LLVMRustSetLastError(toString(ObjOrErr.takeError()).c_str());
return nullptr;
}
auto Index = (*ObjOrErr)->takeIndex();
Ret->Index.mergeFrom(std::move(Index), i);
2017-10-10 19:29:14 +00:00
#endif
rustc: Implement ThinLTO This commit is an implementation of LLVM's ThinLTO for consumption in rustc itself. Currently today LTO works by merging all relevant LLVM modules into one and then running optimization passes. "Thin" LTO operates differently by having more sharded work and allowing parallelism opportunities between optimizing codegen units. Further down the road Thin LTO also allows *incremental* LTO which should enable even faster release builds without compromising on the performance we have today. This commit uses a `-Z thinlto` flag to gate whether ThinLTO is enabled. It then also implements two forms of ThinLTO: * In one mode we'll *only* perform ThinLTO over the codegen units produced in a single compilation. That is, we won't load upstream rlibs, but we'll instead just perform ThinLTO amongst all codegen units produced by the compiler for the local crate. This is intended to emulate a desired end point where we have codegen units turned on by default for all crates and ThinLTO allows us to do this without performance loss. * In anther mode, like full LTO today, we'll optimize all upstream dependencies in "thin" mode. Unlike today, however, this LTO step is fully parallelized so should finish much more quickly. There's a good bit of comments about what the implementation is doing and where it came from, but the tl;dr; is that currently most of the support here is copied from upstream LLVM. This code duplication is done for a number of reasons: * Controlling parallelism means we can use the existing jobserver support to avoid overloading machines. * We will likely want a slightly different form of incremental caching which integrates with our own incremental strategy, but this is yet to be determined. * This buys us some flexibility about when/where we run ThinLTO, as well as having it tailored to fit our needs for the time being. * Finally this allows us to reuse some artifacts such as our `TargetMachine` creation, where all our options we used today aren't necessarily supported by upstream LLVM yet. My hope is that we can get some experience with this copy/paste in tree and then eventually upstream some work to LLVM itself to avoid the duplication while still ensuring our needs are met. Otherwise I fear that maintaining these bindings may be quite costly over the years with LLVM updates!
2017-07-23 15:14:38 +00:00
}
// Collect for each module the list of function it defines (GUID -> Summary)
Ret->Index.collectDefinedGVSummariesPerModule(Ret->ModuleToDefinedGVSummaries);
// Convert the preserved symbols set from string to GUID, this is then needed
// for internalization.
rustc: Implement ThinLTO This commit is an implementation of LLVM's ThinLTO for consumption in rustc itself. Currently today LTO works by merging all relevant LLVM modules into one and then running optimization passes. "Thin" LTO operates differently by having more sharded work and allowing parallelism opportunities between optimizing codegen units. Further down the road Thin LTO also allows *incremental* LTO which should enable even faster release builds without compromising on the performance we have today. This commit uses a `-Z thinlto` flag to gate whether ThinLTO is enabled. It then also implements two forms of ThinLTO: * In one mode we'll *only* perform ThinLTO over the codegen units produced in a single compilation. That is, we won't load upstream rlibs, but we'll instead just perform ThinLTO amongst all codegen units produced by the compiler for the local crate. This is intended to emulate a desired end point where we have codegen units turned on by default for all crates and ThinLTO allows us to do this without performance loss. * In anther mode, like full LTO today, we'll optimize all upstream dependencies in "thin" mode. Unlike today, however, this LTO step is fully parallelized so should finish much more quickly. There's a good bit of comments about what the implementation is doing and where it came from, but the tl;dr; is that currently most of the support here is copied from upstream LLVM. This code duplication is done for a number of reasons: * Controlling parallelism means we can use the existing jobserver support to avoid overloading machines. * We will likely want a slightly different form of incremental caching which integrates with our own incremental strategy, but this is yet to be determined. * This buys us some flexibility about when/where we run ThinLTO, as well as having it tailored to fit our needs for the time being. * Finally this allows us to reuse some artifacts such as our `TargetMachine` creation, where all our options we used today aren't necessarily supported by upstream LLVM yet. My hope is that we can get some experience with this copy/paste in tree and then eventually upstream some work to LLVM itself to avoid the duplication while still ensuring our needs are met. Otherwise I fear that maintaining these bindings may be quite costly over the years with LLVM updates!
2017-07-23 15:14:38 +00:00
for (int i = 0; i < num_symbols; i++) {
auto GUID = GlobalValue::getGUID(preserved_symbols[i]);
Ret->GUIDPreservedSymbols.insert(GUID);
rustc: Implement ThinLTO This commit is an implementation of LLVM's ThinLTO for consumption in rustc itself. Currently today LTO works by merging all relevant LLVM modules into one and then running optimization passes. "Thin" LTO operates differently by having more sharded work and allowing parallelism opportunities between optimizing codegen units. Further down the road Thin LTO also allows *incremental* LTO which should enable even faster release builds without compromising on the performance we have today. This commit uses a `-Z thinlto` flag to gate whether ThinLTO is enabled. It then also implements two forms of ThinLTO: * In one mode we'll *only* perform ThinLTO over the codegen units produced in a single compilation. That is, we won't load upstream rlibs, but we'll instead just perform ThinLTO amongst all codegen units produced by the compiler for the local crate. This is intended to emulate a desired end point where we have codegen units turned on by default for all crates and ThinLTO allows us to do this without performance loss. * In anther mode, like full LTO today, we'll optimize all upstream dependencies in "thin" mode. Unlike today, however, this LTO step is fully parallelized so should finish much more quickly. There's a good bit of comments about what the implementation is doing and where it came from, but the tl;dr; is that currently most of the support here is copied from upstream LLVM. This code duplication is done for a number of reasons: * Controlling parallelism means we can use the existing jobserver support to avoid overloading machines. * We will likely want a slightly different form of incremental caching which integrates with our own incremental strategy, but this is yet to be determined. * This buys us some flexibility about when/where we run ThinLTO, as well as having it tailored to fit our needs for the time being. * Finally this allows us to reuse some artifacts such as our `TargetMachine` creation, where all our options we used today aren't necessarily supported by upstream LLVM yet. My hope is that we can get some experience with this copy/paste in tree and then eventually upstream some work to LLVM itself to avoid the duplication while still ensuring our needs are met. Otherwise I fear that maintaining these bindings may be quite costly over the years with LLVM updates!
2017-07-23 15:14:38 +00:00
}
// Collect the import/export lists for all modules from the call-graph in the
// combined index
//
// This is copied from `lib/LTO/ThinLTOCodeGenerator.cpp`
#if LLVM_VERSION_GE(5, 0)
computeDeadSymbols(Ret->Index, Ret->GUIDPreservedSymbols);
ComputeCrossModuleImport(
Ret->Index,
Ret->ModuleToDefinedGVSummaries,
Ret->ImportLists,
Ret->ExportLists
);
#else
auto DeadSymbols = computeDeadSymbols(Ret->Index, Ret->GUIDPreservedSymbols);
rustc: Implement ThinLTO This commit is an implementation of LLVM's ThinLTO for consumption in rustc itself. Currently today LTO works by merging all relevant LLVM modules into one and then running optimization passes. "Thin" LTO operates differently by having more sharded work and allowing parallelism opportunities between optimizing codegen units. Further down the road Thin LTO also allows *incremental* LTO which should enable even faster release builds without compromising on the performance we have today. This commit uses a `-Z thinlto` flag to gate whether ThinLTO is enabled. It then also implements two forms of ThinLTO: * In one mode we'll *only* perform ThinLTO over the codegen units produced in a single compilation. That is, we won't load upstream rlibs, but we'll instead just perform ThinLTO amongst all codegen units produced by the compiler for the local crate. This is intended to emulate a desired end point where we have codegen units turned on by default for all crates and ThinLTO allows us to do this without performance loss. * In anther mode, like full LTO today, we'll optimize all upstream dependencies in "thin" mode. Unlike today, however, this LTO step is fully parallelized so should finish much more quickly. There's a good bit of comments about what the implementation is doing and where it came from, but the tl;dr; is that currently most of the support here is copied from upstream LLVM. This code duplication is done for a number of reasons: * Controlling parallelism means we can use the existing jobserver support to avoid overloading machines. * We will likely want a slightly different form of incremental caching which integrates with our own incremental strategy, but this is yet to be determined. * This buys us some flexibility about when/where we run ThinLTO, as well as having it tailored to fit our needs for the time being. * Finally this allows us to reuse some artifacts such as our `TargetMachine` creation, where all our options we used today aren't necessarily supported by upstream LLVM yet. My hope is that we can get some experience with this copy/paste in tree and then eventually upstream some work to LLVM itself to avoid the duplication while still ensuring our needs are met. Otherwise I fear that maintaining these bindings may be quite costly over the years with LLVM updates!
2017-07-23 15:14:38 +00:00
ComputeCrossModuleImport(
Ret->Index,
Ret->ModuleToDefinedGVSummaries,
Ret->ImportLists,
Ret->ExportLists,
&DeadSymbols
rustc: Implement ThinLTO This commit is an implementation of LLVM's ThinLTO for consumption in rustc itself. Currently today LTO works by merging all relevant LLVM modules into one and then running optimization passes. "Thin" LTO operates differently by having more sharded work and allowing parallelism opportunities between optimizing codegen units. Further down the road Thin LTO also allows *incremental* LTO which should enable even faster release builds without compromising on the performance we have today. This commit uses a `-Z thinlto` flag to gate whether ThinLTO is enabled. It then also implements two forms of ThinLTO: * In one mode we'll *only* perform ThinLTO over the codegen units produced in a single compilation. That is, we won't load upstream rlibs, but we'll instead just perform ThinLTO amongst all codegen units produced by the compiler for the local crate. This is intended to emulate a desired end point where we have codegen units turned on by default for all crates and ThinLTO allows us to do this without performance loss. * In anther mode, like full LTO today, we'll optimize all upstream dependencies in "thin" mode. Unlike today, however, this LTO step is fully parallelized so should finish much more quickly. There's a good bit of comments about what the implementation is doing and where it came from, but the tl;dr; is that currently most of the support here is copied from upstream LLVM. This code duplication is done for a number of reasons: * Controlling parallelism means we can use the existing jobserver support to avoid overloading machines. * We will likely want a slightly different form of incremental caching which integrates with our own incremental strategy, but this is yet to be determined. * This buys us some flexibility about when/where we run ThinLTO, as well as having it tailored to fit our needs for the time being. * Finally this allows us to reuse some artifacts such as our `TargetMachine` creation, where all our options we used today aren't necessarily supported by upstream LLVM yet. My hope is that we can get some experience with this copy/paste in tree and then eventually upstream some work to LLVM itself to avoid the duplication while still ensuring our needs are met. Otherwise I fear that maintaining these bindings may be quite costly over the years with LLVM updates!
2017-07-23 15:14:38 +00:00
);
#endif
rustc: Implement ThinLTO This commit is an implementation of LLVM's ThinLTO for consumption in rustc itself. Currently today LTO works by merging all relevant LLVM modules into one and then running optimization passes. "Thin" LTO operates differently by having more sharded work and allowing parallelism opportunities between optimizing codegen units. Further down the road Thin LTO also allows *incremental* LTO which should enable even faster release builds without compromising on the performance we have today. This commit uses a `-Z thinlto` flag to gate whether ThinLTO is enabled. It then also implements two forms of ThinLTO: * In one mode we'll *only* perform ThinLTO over the codegen units produced in a single compilation. That is, we won't load upstream rlibs, but we'll instead just perform ThinLTO amongst all codegen units produced by the compiler for the local crate. This is intended to emulate a desired end point where we have codegen units turned on by default for all crates and ThinLTO allows us to do this without performance loss. * In anther mode, like full LTO today, we'll optimize all upstream dependencies in "thin" mode. Unlike today, however, this LTO step is fully parallelized so should finish much more quickly. There's a good bit of comments about what the implementation is doing and where it came from, but the tl;dr; is that currently most of the support here is copied from upstream LLVM. This code duplication is done for a number of reasons: * Controlling parallelism means we can use the existing jobserver support to avoid overloading machines. * We will likely want a slightly different form of incremental caching which integrates with our own incremental strategy, but this is yet to be determined. * This buys us some flexibility about when/where we run ThinLTO, as well as having it tailored to fit our needs for the time being. * Finally this allows us to reuse some artifacts such as our `TargetMachine` creation, where all our options we used today aren't necessarily supported by upstream LLVM yet. My hope is that we can get some experience with this copy/paste in tree and then eventually upstream some work to LLVM itself to avoid the duplication while still ensuring our needs are met. Otherwise I fear that maintaining these bindings may be quite costly over the years with LLVM updates!
2017-07-23 15:14:38 +00:00
// Resolve LinkOnce/Weak symbols, this has to be computed early be cause it
// impacts the caching.
//
// This is copied from `lib/LTO/ThinLTOCodeGenerator.cpp` with some of this
// being lifted from `lib/LTO/LTO.cpp` as well
rustc: Implement ThinLTO This commit is an implementation of LLVM's ThinLTO for consumption in rustc itself. Currently today LTO works by merging all relevant LLVM modules into one and then running optimization passes. "Thin" LTO operates differently by having more sharded work and allowing parallelism opportunities between optimizing codegen units. Further down the road Thin LTO also allows *incremental* LTO which should enable even faster release builds without compromising on the performance we have today. This commit uses a `-Z thinlto` flag to gate whether ThinLTO is enabled. It then also implements two forms of ThinLTO: * In one mode we'll *only* perform ThinLTO over the codegen units produced in a single compilation. That is, we won't load upstream rlibs, but we'll instead just perform ThinLTO amongst all codegen units produced by the compiler for the local crate. This is intended to emulate a desired end point where we have codegen units turned on by default for all crates and ThinLTO allows us to do this without performance loss. * In anther mode, like full LTO today, we'll optimize all upstream dependencies in "thin" mode. Unlike today, however, this LTO step is fully parallelized so should finish much more quickly. There's a good bit of comments about what the implementation is doing and where it came from, but the tl;dr; is that currently most of the support here is copied from upstream LLVM. This code duplication is done for a number of reasons: * Controlling parallelism means we can use the existing jobserver support to avoid overloading machines. * We will likely want a slightly different form of incremental caching which integrates with our own incremental strategy, but this is yet to be determined. * This buys us some flexibility about when/where we run ThinLTO, as well as having it tailored to fit our needs for the time being. * Finally this allows us to reuse some artifacts such as our `TargetMachine` creation, where all our options we used today aren't necessarily supported by upstream LLVM yet. My hope is that we can get some experience with this copy/paste in tree and then eventually upstream some work to LLVM itself to avoid the duplication while still ensuring our needs are met. Otherwise I fear that maintaining these bindings may be quite costly over the years with LLVM updates!
2017-07-23 15:14:38 +00:00
StringMap<std::map<GlobalValue::GUID, GlobalValue::LinkageTypes>> ResolvedODR;
DenseMap<GlobalValue::GUID, const GlobalValueSummary *> PrevailingCopy;
for (auto &I : Ret->Index) {
2017-10-10 19:29:14 +00:00
#if LLVM_VERSION_GE(5, 0)
if (I.second.SummaryList.size() > 1)
PrevailingCopy[I.first] = getFirstDefinitionForLinker(I.second.SummaryList);
#else
rustc: Implement ThinLTO This commit is an implementation of LLVM's ThinLTO for consumption in rustc itself. Currently today LTO works by merging all relevant LLVM modules into one and then running optimization passes. "Thin" LTO operates differently by having more sharded work and allowing parallelism opportunities between optimizing codegen units. Further down the road Thin LTO also allows *incremental* LTO which should enable even faster release builds without compromising on the performance we have today. This commit uses a `-Z thinlto` flag to gate whether ThinLTO is enabled. It then also implements two forms of ThinLTO: * In one mode we'll *only* perform ThinLTO over the codegen units produced in a single compilation. That is, we won't load upstream rlibs, but we'll instead just perform ThinLTO amongst all codegen units produced by the compiler for the local crate. This is intended to emulate a desired end point where we have codegen units turned on by default for all crates and ThinLTO allows us to do this without performance loss. * In anther mode, like full LTO today, we'll optimize all upstream dependencies in "thin" mode. Unlike today, however, this LTO step is fully parallelized so should finish much more quickly. There's a good bit of comments about what the implementation is doing and where it came from, but the tl;dr; is that currently most of the support here is copied from upstream LLVM. This code duplication is done for a number of reasons: * Controlling parallelism means we can use the existing jobserver support to avoid overloading machines. * We will likely want a slightly different form of incremental caching which integrates with our own incremental strategy, but this is yet to be determined. * This buys us some flexibility about when/where we run ThinLTO, as well as having it tailored to fit our needs for the time being. * Finally this allows us to reuse some artifacts such as our `TargetMachine` creation, where all our options we used today aren't necessarily supported by upstream LLVM yet. My hope is that we can get some experience with this copy/paste in tree and then eventually upstream some work to LLVM itself to avoid the duplication while still ensuring our needs are met. Otherwise I fear that maintaining these bindings may be quite costly over the years with LLVM updates!
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if (I.second.size() > 1)
PrevailingCopy[I.first] = getFirstDefinitionForLinker(I.second);
2017-10-10 19:29:14 +00:00
#endif
rustc: Implement ThinLTO This commit is an implementation of LLVM's ThinLTO for consumption in rustc itself. Currently today LTO works by merging all relevant LLVM modules into one and then running optimization passes. "Thin" LTO operates differently by having more sharded work and allowing parallelism opportunities between optimizing codegen units. Further down the road Thin LTO also allows *incremental* LTO which should enable even faster release builds without compromising on the performance we have today. This commit uses a `-Z thinlto` flag to gate whether ThinLTO is enabled. It then also implements two forms of ThinLTO: * In one mode we'll *only* perform ThinLTO over the codegen units produced in a single compilation. That is, we won't load upstream rlibs, but we'll instead just perform ThinLTO amongst all codegen units produced by the compiler for the local crate. This is intended to emulate a desired end point where we have codegen units turned on by default for all crates and ThinLTO allows us to do this without performance loss. * In anther mode, like full LTO today, we'll optimize all upstream dependencies in "thin" mode. Unlike today, however, this LTO step is fully parallelized so should finish much more quickly. There's a good bit of comments about what the implementation is doing and where it came from, but the tl;dr; is that currently most of the support here is copied from upstream LLVM. This code duplication is done for a number of reasons: * Controlling parallelism means we can use the existing jobserver support to avoid overloading machines. * We will likely want a slightly different form of incremental caching which integrates with our own incremental strategy, but this is yet to be determined. * This buys us some flexibility about when/where we run ThinLTO, as well as having it tailored to fit our needs for the time being. * Finally this allows us to reuse some artifacts such as our `TargetMachine` creation, where all our options we used today aren't necessarily supported by upstream LLVM yet. My hope is that we can get some experience with this copy/paste in tree and then eventually upstream some work to LLVM itself to avoid the duplication while still ensuring our needs are met. Otherwise I fear that maintaining these bindings may be quite costly over the years with LLVM updates!
2017-07-23 15:14:38 +00:00
}
auto isPrevailing = [&](GlobalValue::GUID GUID, const GlobalValueSummary *S) {
const auto &Prevailing = PrevailingCopy.find(GUID);
if (Prevailing == PrevailingCopy.end())
return true;
return Prevailing->second == S;
};
auto recordNewLinkage = [&](StringRef ModuleIdentifier,
GlobalValue::GUID GUID,
GlobalValue::LinkageTypes NewLinkage) {
ResolvedODR[ModuleIdentifier][GUID] = NewLinkage;
};
thinLTOResolveWeakForLinkerInIndex(Ret->Index, isPrevailing, recordNewLinkage);
// Here we calculate an `ExportedGUIDs` set for use in the `isExported`
// callback below. This callback below will dictate the linkage for all
// summaries in the index, and we basically just only want to ensure that dead
// symbols are internalized. Otherwise everything that's already external
// linkage will stay as external, and internal will stay as internal.
std::set<GlobalValue::GUID> ExportedGUIDs;
for (auto &List : Ret->Index) {
#if LLVM_VERSION_GE(5, 0)
for (auto &GVS: List.second.SummaryList) {
#else
for (auto &GVS: List.second) {
#endif
if (GlobalValue::isLocalLinkage(GVS->linkage()))
continue;
auto GUID = GVS->getOriginalName();
#if LLVM_VERSION_GE(5, 0)
if (GVS->flags().Live)
#else
if (!DeadSymbols.count(GUID))
#endif
ExportedGUIDs.insert(GUID);
}
}
rustc: Implement ThinLTO This commit is an implementation of LLVM's ThinLTO for consumption in rustc itself. Currently today LTO works by merging all relevant LLVM modules into one and then running optimization passes. "Thin" LTO operates differently by having more sharded work and allowing parallelism opportunities between optimizing codegen units. Further down the road Thin LTO also allows *incremental* LTO which should enable even faster release builds without compromising on the performance we have today. This commit uses a `-Z thinlto` flag to gate whether ThinLTO is enabled. It then also implements two forms of ThinLTO: * In one mode we'll *only* perform ThinLTO over the codegen units produced in a single compilation. That is, we won't load upstream rlibs, but we'll instead just perform ThinLTO amongst all codegen units produced by the compiler for the local crate. This is intended to emulate a desired end point where we have codegen units turned on by default for all crates and ThinLTO allows us to do this without performance loss. * In anther mode, like full LTO today, we'll optimize all upstream dependencies in "thin" mode. Unlike today, however, this LTO step is fully parallelized so should finish much more quickly. There's a good bit of comments about what the implementation is doing and where it came from, but the tl;dr; is that currently most of the support here is copied from upstream LLVM. This code duplication is done for a number of reasons: * Controlling parallelism means we can use the existing jobserver support to avoid overloading machines. * We will likely want a slightly different form of incremental caching which integrates with our own incremental strategy, but this is yet to be determined. * This buys us some flexibility about when/where we run ThinLTO, as well as having it tailored to fit our needs for the time being. * Finally this allows us to reuse some artifacts such as our `TargetMachine` creation, where all our options we used today aren't necessarily supported by upstream LLVM yet. My hope is that we can get some experience with this copy/paste in tree and then eventually upstream some work to LLVM itself to avoid the duplication while still ensuring our needs are met. Otherwise I fear that maintaining these bindings may be quite costly over the years with LLVM updates!
2017-07-23 15:14:38 +00:00
auto isExported = [&](StringRef ModuleIdentifier, GlobalValue::GUID GUID) {
const auto &ExportList = Ret->ExportLists.find(ModuleIdentifier);
return (ExportList != Ret->ExportLists.end() &&
ExportList->second.count(GUID)) ||
ExportedGUIDs.count(GUID);
rustc: Implement ThinLTO This commit is an implementation of LLVM's ThinLTO for consumption in rustc itself. Currently today LTO works by merging all relevant LLVM modules into one and then running optimization passes. "Thin" LTO operates differently by having more sharded work and allowing parallelism opportunities between optimizing codegen units. Further down the road Thin LTO also allows *incremental* LTO which should enable even faster release builds without compromising on the performance we have today. This commit uses a `-Z thinlto` flag to gate whether ThinLTO is enabled. It then also implements two forms of ThinLTO: * In one mode we'll *only* perform ThinLTO over the codegen units produced in a single compilation. That is, we won't load upstream rlibs, but we'll instead just perform ThinLTO amongst all codegen units produced by the compiler for the local crate. This is intended to emulate a desired end point where we have codegen units turned on by default for all crates and ThinLTO allows us to do this without performance loss. * In anther mode, like full LTO today, we'll optimize all upstream dependencies in "thin" mode. Unlike today, however, this LTO step is fully parallelized so should finish much more quickly. There's a good bit of comments about what the implementation is doing and where it came from, but the tl;dr; is that currently most of the support here is copied from upstream LLVM. This code duplication is done for a number of reasons: * Controlling parallelism means we can use the existing jobserver support to avoid overloading machines. * We will likely want a slightly different form of incremental caching which integrates with our own incremental strategy, but this is yet to be determined. * This buys us some flexibility about when/where we run ThinLTO, as well as having it tailored to fit our needs for the time being. * Finally this allows us to reuse some artifacts such as our `TargetMachine` creation, where all our options we used today aren't necessarily supported by upstream LLVM yet. My hope is that we can get some experience with this copy/paste in tree and then eventually upstream some work to LLVM itself to avoid the duplication while still ensuring our needs are met. Otherwise I fear that maintaining these bindings may be quite costly over the years with LLVM updates!
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};
thinLTOInternalizeAndPromoteInIndex(Ret->Index, isExported);
return Ret.release();
}
extern "C" void
LLVMRustFreeThinLTOData(LLVMRustThinLTOData *Data) {
delete Data;
}
// Below are the various passes that happen *per module* when doing ThinLTO.
//
// In other words, these are the functions that are all run concurrently
// with one another, one per module. The passes here correspond to the analysis
// passes in `lib/LTO/ThinLTOCodeGenerator.cpp`, currently found in the
// `ProcessThinLTOModule` function. Here they're split up into separate steps
// so rustc can save off the intermediate bytecode between each step.
extern "C" bool
LLVMRustPrepareThinLTORename(const LLVMRustThinLTOData *Data, LLVMModuleRef M) {
Module &Mod = *unwrap(M);
if (renameModuleForThinLTO(Mod, Data->Index)) {
LLVMRustSetLastError("renameModuleForThinLTO failed");
return false;
}
return true;
}
extern "C" bool
LLVMRustPrepareThinLTOResolveWeak(const LLVMRustThinLTOData *Data, LLVMModuleRef M) {
Module &Mod = *unwrap(M);
const auto &DefinedGlobals = Data->ModuleToDefinedGVSummaries.lookup(Mod.getModuleIdentifier());
thinLTOResolveWeakForLinkerModule(Mod, DefinedGlobals);
return true;
}
extern "C" bool
LLVMRustPrepareThinLTOInternalize(const LLVMRustThinLTOData *Data, LLVMModuleRef M) {
Module &Mod = *unwrap(M);
const auto &DefinedGlobals = Data->ModuleToDefinedGVSummaries.lookup(Mod.getModuleIdentifier());
thinLTOInternalizeModule(Mod, DefinedGlobals);
return true;
}
extern "C" bool
LLVMRustPrepareThinLTOImport(const LLVMRustThinLTOData *Data, LLVMModuleRef M) {
Module &Mod = *unwrap(M);
const auto &ImportList = Data->ImportLists.lookup(Mod.getModuleIdentifier());
auto Loader = [&](StringRef Identifier) {
const auto &Memory = Data->ModuleMap.lookup(Identifier);
auto &Context = Mod.getContext();
return getLazyBitcodeModule(Memory, Context, true, true);
};
FunctionImporter Importer(Data->Index, Loader);
Expected<bool> Result = Importer.importFunctions(Mod, ImportList);
if (!Result) {
LLVMRustSetLastError(toString(Result.takeError()).c_str());
return false;
}
return true;
}
// This struct and various functions are sort of a hack right now, but the
// problem is that we've got in-memory LLVM modules after we generate and
// optimize all codegen-units for one compilation in rustc. To be compatible
// with the LTO support above we need to serialize the modules plus their
// ThinLTO summary into memory.
//
// This structure is basically an owned version of a serialize module, with
// a ThinLTO summary attached.
struct LLVMRustThinLTOBuffer {
std::string data;
};
extern "C" LLVMRustThinLTOBuffer*
LLVMRustThinLTOBufferCreate(LLVMModuleRef M) {
auto Ret = llvm::make_unique<LLVMRustThinLTOBuffer>();
{
raw_string_ostream OS(Ret->data);
{
legacy::PassManager PM;
PM.add(createWriteThinLTOBitcodePass(OS));
PM.run(*unwrap(M));
}
}
return Ret.release();
}
extern "C" void
LLVMRustThinLTOBufferFree(LLVMRustThinLTOBuffer *Buffer) {
delete Buffer;
}
extern "C" const void*
LLVMRustThinLTOBufferPtr(const LLVMRustThinLTOBuffer *Buffer) {
return Buffer->data.data();
}
extern "C" size_t
LLVMRustThinLTOBufferLen(const LLVMRustThinLTOBuffer *Buffer) {
return Buffer->data.length();
}
// This is what we used to parse upstream bitcode for actual ThinLTO
// processing. We'll call this once per module optimized through ThinLTO, and
// it'll be called concurrently on many threads.
extern "C" LLVMModuleRef
LLVMRustParseBitcodeForThinLTO(LLVMContextRef Context,
const char *data,
size_t len,
const char *identifier) {
StringRef Data(data, len);
MemoryBufferRef Buffer(Data, identifier);
unwrap(Context)->enableDebugTypeODRUniquing();
Expected<std::unique_ptr<Module>> SrcOrError =
parseBitcodeFile(Buffer, *unwrap(Context));
if (!SrcOrError) {
LLVMRustSetLastError(toString(SrcOrError.takeError()).c_str());
return nullptr;
}
return wrap(std::move(*SrcOrError).release());
}
// Rewrite all `DICompileUnit` pointers to the `DICompileUnit` specified. See
// the comment in `back/lto.rs` for why this exists.
extern "C" void
LLVMRustThinLTOGetDICompileUnit(LLVMModuleRef Mod,
DICompileUnit **A,
DICompileUnit **B) {
Module *M = unwrap(Mod);
DICompileUnit **Cur = A;
DICompileUnit **Next = B;
for (DICompileUnit *CU : M->debug_compile_units()) {
*Cur = CU;
Cur = Next;
Next = nullptr;
if (Cur == nullptr)
break;
}
}
// Rewrite all `DICompileUnit` pointers to the `DICompileUnit` specified. See
// the comment in `back/lto.rs` for why this exists.
extern "C" void
LLVMRustThinLTOPatchDICompileUnit(LLVMModuleRef Mod, DICompileUnit *Unit) {
Module *M = unwrap(Mod);
// If the original source module didn't have a `DICompileUnit` then try to
// merge all the existing compile units. If there aren't actually any though
// then there's not much for us to do so return.
if (Unit == nullptr) {
for (DICompileUnit *CU : M->debug_compile_units()) {
Unit = CU;
break;
}
if (Unit == nullptr)
return;
}
// Use LLVM's built-in `DebugInfoFinder` to find a bunch of debuginfo and
// process it recursively. Note that we specifically iterate over instructions
// to ensure we feed everything into it.
DebugInfoFinder Finder;
Finder.processModule(*M);
for (Function &F : M->functions()) {
for (auto &FI : F) {
for (Instruction &BI : FI) {
if (auto Loc = BI.getDebugLoc())
Finder.processLocation(*M, Loc);
if (auto DVI = dyn_cast<DbgValueInst>(&BI))
Finder.processValue(*M, DVI);
if (auto DDI = dyn_cast<DbgDeclareInst>(&BI))
Finder.processDeclare(*M, DDI);
}
}
}
// After we've found all our debuginfo, rewrite all subprograms to point to
// the same `DICompileUnit`.
for (auto &F : Finder.subprograms()) {
F->replaceUnit(Unit);
}
// Erase any other references to other `DICompileUnit` instances, the verifier
// will later ensure that we don't actually have any other stale references to
// worry about.
auto *MD = M->getNamedMetadata("llvm.dbg.cu");
MD->clearOperands();
MD->addOperand(Unit);
}
extern "C" void
LLVMRustThinLTORemoveAvailableExternally(LLVMModuleRef Mod) {
Module *M = unwrap(Mod);
for (Function &F : M->functions()) {
if (F.hasAvailableExternallyLinkage())
F.deleteBody();
}
}
rustc: Implement ThinLTO This commit is an implementation of LLVM's ThinLTO for consumption in rustc itself. Currently today LTO works by merging all relevant LLVM modules into one and then running optimization passes. "Thin" LTO operates differently by having more sharded work and allowing parallelism opportunities between optimizing codegen units. Further down the road Thin LTO also allows *incremental* LTO which should enable even faster release builds without compromising on the performance we have today. This commit uses a `-Z thinlto` flag to gate whether ThinLTO is enabled. It then also implements two forms of ThinLTO: * In one mode we'll *only* perform ThinLTO over the codegen units produced in a single compilation. That is, we won't load upstream rlibs, but we'll instead just perform ThinLTO amongst all codegen units produced by the compiler for the local crate. This is intended to emulate a desired end point where we have codegen units turned on by default for all crates and ThinLTO allows us to do this without performance loss. * In anther mode, like full LTO today, we'll optimize all upstream dependencies in "thin" mode. Unlike today, however, this LTO step is fully parallelized so should finish much more quickly. There's a good bit of comments about what the implementation is doing and where it came from, but the tl;dr; is that currently most of the support here is copied from upstream LLVM. This code duplication is done for a number of reasons: * Controlling parallelism means we can use the existing jobserver support to avoid overloading machines. * We will likely want a slightly different form of incremental caching which integrates with our own incremental strategy, but this is yet to be determined. * This buys us some flexibility about when/where we run ThinLTO, as well as having it tailored to fit our needs for the time being. * Finally this allows us to reuse some artifacts such as our `TargetMachine` creation, where all our options we used today aren't necessarily supported by upstream LLVM yet. My hope is that we can get some experience with this copy/paste in tree and then eventually upstream some work to LLVM itself to avoid the duplication while still ensuring our needs are met. Otherwise I fear that maintaining these bindings may be quite costly over the years with LLVM updates!
2017-07-23 15:14:38 +00:00
#else
extern "C" bool
LLVMRustWriteThinBitcodeToFile(LLVMPassManagerRef PMR,
LLVMModuleRef M,
const char *BcFile) {
report_fatal_error("ThinLTO not available");
rustc: Implement ThinLTO This commit is an implementation of LLVM's ThinLTO for consumption in rustc itself. Currently today LTO works by merging all relevant LLVM modules into one and then running optimization passes. "Thin" LTO operates differently by having more sharded work and allowing parallelism opportunities between optimizing codegen units. Further down the road Thin LTO also allows *incremental* LTO which should enable even faster release builds without compromising on the performance we have today. This commit uses a `-Z thinlto` flag to gate whether ThinLTO is enabled. It then also implements two forms of ThinLTO: * In one mode we'll *only* perform ThinLTO over the codegen units produced in a single compilation. That is, we won't load upstream rlibs, but we'll instead just perform ThinLTO amongst all codegen units produced by the compiler for the local crate. This is intended to emulate a desired end point where we have codegen units turned on by default for all crates and ThinLTO allows us to do this without performance loss. * In anther mode, like full LTO today, we'll optimize all upstream dependencies in "thin" mode. Unlike today, however, this LTO step is fully parallelized so should finish much more quickly. There's a good bit of comments about what the implementation is doing and where it came from, but the tl;dr; is that currently most of the support here is copied from upstream LLVM. This code duplication is done for a number of reasons: * Controlling parallelism means we can use the existing jobserver support to avoid overloading machines. * We will likely want a slightly different form of incremental caching which integrates with our own incremental strategy, but this is yet to be determined. * This buys us some flexibility about when/where we run ThinLTO, as well as having it tailored to fit our needs for the time being. * Finally this allows us to reuse some artifacts such as our `TargetMachine` creation, where all our options we used today aren't necessarily supported by upstream LLVM yet. My hope is that we can get some experience with this copy/paste in tree and then eventually upstream some work to LLVM itself to avoid the duplication while still ensuring our needs are met. Otherwise I fear that maintaining these bindings may be quite costly over the years with LLVM updates!
2017-07-23 15:14:38 +00:00
}
struct LLVMRustThinLTOData {
};
struct LLVMRustThinLTOModule {
};
extern "C" LLVMRustThinLTOData*
LLVMRustCreateThinLTOData(LLVMRustThinLTOModule *modules,
int num_modules,
const char **preserved_symbols,
int num_symbols) {
report_fatal_error("ThinLTO not available");
rustc: Implement ThinLTO This commit is an implementation of LLVM's ThinLTO for consumption in rustc itself. Currently today LTO works by merging all relevant LLVM modules into one and then running optimization passes. "Thin" LTO operates differently by having more sharded work and allowing parallelism opportunities between optimizing codegen units. Further down the road Thin LTO also allows *incremental* LTO which should enable even faster release builds without compromising on the performance we have today. This commit uses a `-Z thinlto` flag to gate whether ThinLTO is enabled. It then also implements two forms of ThinLTO: * In one mode we'll *only* perform ThinLTO over the codegen units produced in a single compilation. That is, we won't load upstream rlibs, but we'll instead just perform ThinLTO amongst all codegen units produced by the compiler for the local crate. This is intended to emulate a desired end point where we have codegen units turned on by default for all crates and ThinLTO allows us to do this without performance loss. * In anther mode, like full LTO today, we'll optimize all upstream dependencies in "thin" mode. Unlike today, however, this LTO step is fully parallelized so should finish much more quickly. There's a good bit of comments about what the implementation is doing and where it came from, but the tl;dr; is that currently most of the support here is copied from upstream LLVM. This code duplication is done for a number of reasons: * Controlling parallelism means we can use the existing jobserver support to avoid overloading machines. * We will likely want a slightly different form of incremental caching which integrates with our own incremental strategy, but this is yet to be determined. * This buys us some flexibility about when/where we run ThinLTO, as well as having it tailored to fit our needs for the time being. * Finally this allows us to reuse some artifacts such as our `TargetMachine` creation, where all our options we used today aren't necessarily supported by upstream LLVM yet. My hope is that we can get some experience with this copy/paste in tree and then eventually upstream some work to LLVM itself to avoid the duplication while still ensuring our needs are met. Otherwise I fear that maintaining these bindings may be quite costly over the years with LLVM updates!
2017-07-23 15:14:38 +00:00
}
extern "C" bool
LLVMRustPrepareThinLTORename(const LLVMRustThinLTOData *Data, LLVMModuleRef M) {
report_fatal_error("ThinLTO not available");
rustc: Implement ThinLTO This commit is an implementation of LLVM's ThinLTO for consumption in rustc itself. Currently today LTO works by merging all relevant LLVM modules into one and then running optimization passes. "Thin" LTO operates differently by having more sharded work and allowing parallelism opportunities between optimizing codegen units. Further down the road Thin LTO also allows *incremental* LTO which should enable even faster release builds without compromising on the performance we have today. This commit uses a `-Z thinlto` flag to gate whether ThinLTO is enabled. It then also implements two forms of ThinLTO: * In one mode we'll *only* perform ThinLTO over the codegen units produced in a single compilation. That is, we won't load upstream rlibs, but we'll instead just perform ThinLTO amongst all codegen units produced by the compiler for the local crate. This is intended to emulate a desired end point where we have codegen units turned on by default for all crates and ThinLTO allows us to do this without performance loss. * In anther mode, like full LTO today, we'll optimize all upstream dependencies in "thin" mode. Unlike today, however, this LTO step is fully parallelized so should finish much more quickly. There's a good bit of comments about what the implementation is doing and where it came from, but the tl;dr; is that currently most of the support here is copied from upstream LLVM. This code duplication is done for a number of reasons: * Controlling parallelism means we can use the existing jobserver support to avoid overloading machines. * We will likely want a slightly different form of incremental caching which integrates with our own incremental strategy, but this is yet to be determined. * This buys us some flexibility about when/where we run ThinLTO, as well as having it tailored to fit our needs for the time being. * Finally this allows us to reuse some artifacts such as our `TargetMachine` creation, where all our options we used today aren't necessarily supported by upstream LLVM yet. My hope is that we can get some experience with this copy/paste in tree and then eventually upstream some work to LLVM itself to avoid the duplication while still ensuring our needs are met. Otherwise I fear that maintaining these bindings may be quite costly over the years with LLVM updates!
2017-07-23 15:14:38 +00:00
}
extern "C" bool
LLVMRustPrepareThinLTOResolveWeak(const LLVMRustThinLTOData *Data, LLVMModuleRef M) {
report_fatal_error("ThinLTO not available");
rustc: Implement ThinLTO This commit is an implementation of LLVM's ThinLTO for consumption in rustc itself. Currently today LTO works by merging all relevant LLVM modules into one and then running optimization passes. "Thin" LTO operates differently by having more sharded work and allowing parallelism opportunities between optimizing codegen units. Further down the road Thin LTO also allows *incremental* LTO which should enable even faster release builds without compromising on the performance we have today. This commit uses a `-Z thinlto` flag to gate whether ThinLTO is enabled. It then also implements two forms of ThinLTO: * In one mode we'll *only* perform ThinLTO over the codegen units produced in a single compilation. That is, we won't load upstream rlibs, but we'll instead just perform ThinLTO amongst all codegen units produced by the compiler for the local crate. This is intended to emulate a desired end point where we have codegen units turned on by default for all crates and ThinLTO allows us to do this without performance loss. * In anther mode, like full LTO today, we'll optimize all upstream dependencies in "thin" mode. Unlike today, however, this LTO step is fully parallelized so should finish much more quickly. There's a good bit of comments about what the implementation is doing and where it came from, but the tl;dr; is that currently most of the support here is copied from upstream LLVM. This code duplication is done for a number of reasons: * Controlling parallelism means we can use the existing jobserver support to avoid overloading machines. * We will likely want a slightly different form of incremental caching which integrates with our own incremental strategy, but this is yet to be determined. * This buys us some flexibility about when/where we run ThinLTO, as well as having it tailored to fit our needs for the time being. * Finally this allows us to reuse some artifacts such as our `TargetMachine` creation, where all our options we used today aren't necessarily supported by upstream LLVM yet. My hope is that we can get some experience with this copy/paste in tree and then eventually upstream some work to LLVM itself to avoid the duplication while still ensuring our needs are met. Otherwise I fear that maintaining these bindings may be quite costly over the years with LLVM updates!
2017-07-23 15:14:38 +00:00
}
extern "C" bool
LLVMRustPrepareThinLTOInternalize(const LLVMRustThinLTOData *Data, LLVMModuleRef M) {
report_fatal_error("ThinLTO not available");
rustc: Implement ThinLTO This commit is an implementation of LLVM's ThinLTO for consumption in rustc itself. Currently today LTO works by merging all relevant LLVM modules into one and then running optimization passes. "Thin" LTO operates differently by having more sharded work and allowing parallelism opportunities between optimizing codegen units. Further down the road Thin LTO also allows *incremental* LTO which should enable even faster release builds without compromising on the performance we have today. This commit uses a `-Z thinlto` flag to gate whether ThinLTO is enabled. It then also implements two forms of ThinLTO: * In one mode we'll *only* perform ThinLTO over the codegen units produced in a single compilation. That is, we won't load upstream rlibs, but we'll instead just perform ThinLTO amongst all codegen units produced by the compiler for the local crate. This is intended to emulate a desired end point where we have codegen units turned on by default for all crates and ThinLTO allows us to do this without performance loss. * In anther mode, like full LTO today, we'll optimize all upstream dependencies in "thin" mode. Unlike today, however, this LTO step is fully parallelized so should finish much more quickly. There's a good bit of comments about what the implementation is doing and where it came from, but the tl;dr; is that currently most of the support here is copied from upstream LLVM. This code duplication is done for a number of reasons: * Controlling parallelism means we can use the existing jobserver support to avoid overloading machines. * We will likely want a slightly different form of incremental caching which integrates with our own incremental strategy, but this is yet to be determined. * This buys us some flexibility about when/where we run ThinLTO, as well as having it tailored to fit our needs for the time being. * Finally this allows us to reuse some artifacts such as our `TargetMachine` creation, where all our options we used today aren't necessarily supported by upstream LLVM yet. My hope is that we can get some experience with this copy/paste in tree and then eventually upstream some work to LLVM itself to avoid the duplication while still ensuring our needs are met. Otherwise I fear that maintaining these bindings may be quite costly over the years with LLVM updates!
2017-07-23 15:14:38 +00:00
}
extern "C" bool
LLVMRustPrepareThinLTOImport(const LLVMRustThinLTOData *Data, LLVMModuleRef M) {
report_fatal_error("ThinLTO not available");
rustc: Implement ThinLTO This commit is an implementation of LLVM's ThinLTO for consumption in rustc itself. Currently today LTO works by merging all relevant LLVM modules into one and then running optimization passes. "Thin" LTO operates differently by having more sharded work and allowing parallelism opportunities between optimizing codegen units. Further down the road Thin LTO also allows *incremental* LTO which should enable even faster release builds without compromising on the performance we have today. This commit uses a `-Z thinlto` flag to gate whether ThinLTO is enabled. It then also implements two forms of ThinLTO: * In one mode we'll *only* perform ThinLTO over the codegen units produced in a single compilation. That is, we won't load upstream rlibs, but we'll instead just perform ThinLTO amongst all codegen units produced by the compiler for the local crate. This is intended to emulate a desired end point where we have codegen units turned on by default for all crates and ThinLTO allows us to do this without performance loss. * In anther mode, like full LTO today, we'll optimize all upstream dependencies in "thin" mode. Unlike today, however, this LTO step is fully parallelized so should finish much more quickly. There's a good bit of comments about what the implementation is doing and where it came from, but the tl;dr; is that currently most of the support here is copied from upstream LLVM. This code duplication is done for a number of reasons: * Controlling parallelism means we can use the existing jobserver support to avoid overloading machines. * We will likely want a slightly different form of incremental caching which integrates with our own incremental strategy, but this is yet to be determined. * This buys us some flexibility about when/where we run ThinLTO, as well as having it tailored to fit our needs for the time being. * Finally this allows us to reuse some artifacts such as our `TargetMachine` creation, where all our options we used today aren't necessarily supported by upstream LLVM yet. My hope is that we can get some experience with this copy/paste in tree and then eventually upstream some work to LLVM itself to avoid the duplication while still ensuring our needs are met. Otherwise I fear that maintaining these bindings may be quite costly over the years with LLVM updates!
2017-07-23 15:14:38 +00:00
}
extern "C" void
LLVMRustFreeThinLTOData(LLVMRustThinLTOData *Data) {
report_fatal_error("ThinLTO not available");
rustc: Implement ThinLTO This commit is an implementation of LLVM's ThinLTO for consumption in rustc itself. Currently today LTO works by merging all relevant LLVM modules into one and then running optimization passes. "Thin" LTO operates differently by having more sharded work and allowing parallelism opportunities between optimizing codegen units. Further down the road Thin LTO also allows *incremental* LTO which should enable even faster release builds without compromising on the performance we have today. This commit uses a `-Z thinlto` flag to gate whether ThinLTO is enabled. It then also implements two forms of ThinLTO: * In one mode we'll *only* perform ThinLTO over the codegen units produced in a single compilation. That is, we won't load upstream rlibs, but we'll instead just perform ThinLTO amongst all codegen units produced by the compiler for the local crate. This is intended to emulate a desired end point where we have codegen units turned on by default for all crates and ThinLTO allows us to do this without performance loss. * In anther mode, like full LTO today, we'll optimize all upstream dependencies in "thin" mode. Unlike today, however, this LTO step is fully parallelized so should finish much more quickly. There's a good bit of comments about what the implementation is doing and where it came from, but the tl;dr; is that currently most of the support here is copied from upstream LLVM. This code duplication is done for a number of reasons: * Controlling parallelism means we can use the existing jobserver support to avoid overloading machines. * We will likely want a slightly different form of incremental caching which integrates with our own incremental strategy, but this is yet to be determined. * This buys us some flexibility about when/where we run ThinLTO, as well as having it tailored to fit our needs for the time being. * Finally this allows us to reuse some artifacts such as our `TargetMachine` creation, where all our options we used today aren't necessarily supported by upstream LLVM yet. My hope is that we can get some experience with this copy/paste in tree and then eventually upstream some work to LLVM itself to avoid the duplication while still ensuring our needs are met. Otherwise I fear that maintaining these bindings may be quite costly over the years with LLVM updates!
2017-07-23 15:14:38 +00:00
}
struct LLVMRustThinLTOBuffer {
};
extern "C" LLVMRustThinLTOBuffer*
LLVMRustThinLTOBufferCreate(LLVMModuleRef M) {
report_fatal_error("ThinLTO not available");
rustc: Implement ThinLTO This commit is an implementation of LLVM's ThinLTO for consumption in rustc itself. Currently today LTO works by merging all relevant LLVM modules into one and then running optimization passes. "Thin" LTO operates differently by having more sharded work and allowing parallelism opportunities between optimizing codegen units. Further down the road Thin LTO also allows *incremental* LTO which should enable even faster release builds without compromising on the performance we have today. This commit uses a `-Z thinlto` flag to gate whether ThinLTO is enabled. It then also implements two forms of ThinLTO: * In one mode we'll *only* perform ThinLTO over the codegen units produced in a single compilation. That is, we won't load upstream rlibs, but we'll instead just perform ThinLTO amongst all codegen units produced by the compiler for the local crate. This is intended to emulate a desired end point where we have codegen units turned on by default for all crates and ThinLTO allows us to do this without performance loss. * In anther mode, like full LTO today, we'll optimize all upstream dependencies in "thin" mode. Unlike today, however, this LTO step is fully parallelized so should finish much more quickly. There's a good bit of comments about what the implementation is doing and where it came from, but the tl;dr; is that currently most of the support here is copied from upstream LLVM. This code duplication is done for a number of reasons: * Controlling parallelism means we can use the existing jobserver support to avoid overloading machines. * We will likely want a slightly different form of incremental caching which integrates with our own incremental strategy, but this is yet to be determined. * This buys us some flexibility about when/where we run ThinLTO, as well as having it tailored to fit our needs for the time being. * Finally this allows us to reuse some artifacts such as our `TargetMachine` creation, where all our options we used today aren't necessarily supported by upstream LLVM yet. My hope is that we can get some experience with this copy/paste in tree and then eventually upstream some work to LLVM itself to avoid the duplication while still ensuring our needs are met. Otherwise I fear that maintaining these bindings may be quite costly over the years with LLVM updates!
2017-07-23 15:14:38 +00:00
}
extern "C" void
LLVMRustThinLTOBufferFree(LLVMRustThinLTOBuffer *Buffer) {
report_fatal_error("ThinLTO not available");
rustc: Implement ThinLTO This commit is an implementation of LLVM's ThinLTO for consumption in rustc itself. Currently today LTO works by merging all relevant LLVM modules into one and then running optimization passes. "Thin" LTO operates differently by having more sharded work and allowing parallelism opportunities between optimizing codegen units. Further down the road Thin LTO also allows *incremental* LTO which should enable even faster release builds without compromising on the performance we have today. This commit uses a `-Z thinlto` flag to gate whether ThinLTO is enabled. It then also implements two forms of ThinLTO: * In one mode we'll *only* perform ThinLTO over the codegen units produced in a single compilation. That is, we won't load upstream rlibs, but we'll instead just perform ThinLTO amongst all codegen units produced by the compiler for the local crate. This is intended to emulate a desired end point where we have codegen units turned on by default for all crates and ThinLTO allows us to do this without performance loss. * In anther mode, like full LTO today, we'll optimize all upstream dependencies in "thin" mode. Unlike today, however, this LTO step is fully parallelized so should finish much more quickly. There's a good bit of comments about what the implementation is doing and where it came from, but the tl;dr; is that currently most of the support here is copied from upstream LLVM. This code duplication is done for a number of reasons: * Controlling parallelism means we can use the existing jobserver support to avoid overloading machines. * We will likely want a slightly different form of incremental caching which integrates with our own incremental strategy, but this is yet to be determined. * This buys us some flexibility about when/where we run ThinLTO, as well as having it tailored to fit our needs for the time being. * Finally this allows us to reuse some artifacts such as our `TargetMachine` creation, where all our options we used today aren't necessarily supported by upstream LLVM yet. My hope is that we can get some experience with this copy/paste in tree and then eventually upstream some work to LLVM itself to avoid the duplication while still ensuring our needs are met. Otherwise I fear that maintaining these bindings may be quite costly over the years with LLVM updates!
2017-07-23 15:14:38 +00:00
}
extern "C" const void*
LLVMRustThinLTOBufferPtr(const LLVMRustThinLTOBuffer *Buffer) {
report_fatal_error("ThinLTO not available");
rustc: Implement ThinLTO This commit is an implementation of LLVM's ThinLTO for consumption in rustc itself. Currently today LTO works by merging all relevant LLVM modules into one and then running optimization passes. "Thin" LTO operates differently by having more sharded work and allowing parallelism opportunities between optimizing codegen units. Further down the road Thin LTO also allows *incremental* LTO which should enable even faster release builds without compromising on the performance we have today. This commit uses a `-Z thinlto` flag to gate whether ThinLTO is enabled. It then also implements two forms of ThinLTO: * In one mode we'll *only* perform ThinLTO over the codegen units produced in a single compilation. That is, we won't load upstream rlibs, but we'll instead just perform ThinLTO amongst all codegen units produced by the compiler for the local crate. This is intended to emulate a desired end point where we have codegen units turned on by default for all crates and ThinLTO allows us to do this without performance loss. * In anther mode, like full LTO today, we'll optimize all upstream dependencies in "thin" mode. Unlike today, however, this LTO step is fully parallelized so should finish much more quickly. There's a good bit of comments about what the implementation is doing and where it came from, but the tl;dr; is that currently most of the support here is copied from upstream LLVM. This code duplication is done for a number of reasons: * Controlling parallelism means we can use the existing jobserver support to avoid overloading machines. * We will likely want a slightly different form of incremental caching which integrates with our own incremental strategy, but this is yet to be determined. * This buys us some flexibility about when/where we run ThinLTO, as well as having it tailored to fit our needs for the time being. * Finally this allows us to reuse some artifacts such as our `TargetMachine` creation, where all our options we used today aren't necessarily supported by upstream LLVM yet. My hope is that we can get some experience with this copy/paste in tree and then eventually upstream some work to LLVM itself to avoid the duplication while still ensuring our needs are met. Otherwise I fear that maintaining these bindings may be quite costly over the years with LLVM updates!
2017-07-23 15:14:38 +00:00
}
extern "C" size_t
LLVMRustThinLTOBufferLen(const LLVMRustThinLTOBuffer *Buffer) {
report_fatal_error("ThinLTO not available");
rustc: Implement ThinLTO This commit is an implementation of LLVM's ThinLTO for consumption in rustc itself. Currently today LTO works by merging all relevant LLVM modules into one and then running optimization passes. "Thin" LTO operates differently by having more sharded work and allowing parallelism opportunities between optimizing codegen units. Further down the road Thin LTO also allows *incremental* LTO which should enable even faster release builds without compromising on the performance we have today. This commit uses a `-Z thinlto` flag to gate whether ThinLTO is enabled. It then also implements two forms of ThinLTO: * In one mode we'll *only* perform ThinLTO over the codegen units produced in a single compilation. That is, we won't load upstream rlibs, but we'll instead just perform ThinLTO amongst all codegen units produced by the compiler for the local crate. This is intended to emulate a desired end point where we have codegen units turned on by default for all crates and ThinLTO allows us to do this without performance loss. * In anther mode, like full LTO today, we'll optimize all upstream dependencies in "thin" mode. Unlike today, however, this LTO step is fully parallelized so should finish much more quickly. There's a good bit of comments about what the implementation is doing and where it came from, but the tl;dr; is that currently most of the support here is copied from upstream LLVM. This code duplication is done for a number of reasons: * Controlling parallelism means we can use the existing jobserver support to avoid overloading machines. * We will likely want a slightly different form of incremental caching which integrates with our own incremental strategy, but this is yet to be determined. * This buys us some flexibility about when/where we run ThinLTO, as well as having it tailored to fit our needs for the time being. * Finally this allows us to reuse some artifacts such as our `TargetMachine` creation, where all our options we used today aren't necessarily supported by upstream LLVM yet. My hope is that we can get some experience with this copy/paste in tree and then eventually upstream some work to LLVM itself to avoid the duplication while still ensuring our needs are met. Otherwise I fear that maintaining these bindings may be quite costly over the years with LLVM updates!
2017-07-23 15:14:38 +00:00
}
extern "C" LLVMModuleRef
LLVMRustParseBitcodeForThinLTO(LLVMContextRef Context,
const char *data,
size_t len,
const char *identifier) {
report_fatal_error("ThinLTO not available");
rustc: Implement ThinLTO This commit is an implementation of LLVM's ThinLTO for consumption in rustc itself. Currently today LTO works by merging all relevant LLVM modules into one and then running optimization passes. "Thin" LTO operates differently by having more sharded work and allowing parallelism opportunities between optimizing codegen units. Further down the road Thin LTO also allows *incremental* LTO which should enable even faster release builds without compromising on the performance we have today. This commit uses a `-Z thinlto` flag to gate whether ThinLTO is enabled. It then also implements two forms of ThinLTO: * In one mode we'll *only* perform ThinLTO over the codegen units produced in a single compilation. That is, we won't load upstream rlibs, but we'll instead just perform ThinLTO amongst all codegen units produced by the compiler for the local crate. This is intended to emulate a desired end point where we have codegen units turned on by default for all crates and ThinLTO allows us to do this without performance loss. * In anther mode, like full LTO today, we'll optimize all upstream dependencies in "thin" mode. Unlike today, however, this LTO step is fully parallelized so should finish much more quickly. There's a good bit of comments about what the implementation is doing and where it came from, but the tl;dr; is that currently most of the support here is copied from upstream LLVM. This code duplication is done for a number of reasons: * Controlling parallelism means we can use the existing jobserver support to avoid overloading machines. * We will likely want a slightly different form of incremental caching which integrates with our own incremental strategy, but this is yet to be determined. * This buys us some flexibility about when/where we run ThinLTO, as well as having it tailored to fit our needs for the time being. * Finally this allows us to reuse some artifacts such as our `TargetMachine` creation, where all our options we used today aren't necessarily supported by upstream LLVM yet. My hope is that we can get some experience with this copy/paste in tree and then eventually upstream some work to LLVM itself to avoid the duplication while still ensuring our needs are met. Otherwise I fear that maintaining these bindings may be quite costly over the years with LLVM updates!
2017-07-23 15:14:38 +00:00
}
extern "C" void
LLVMRustThinLTOGetDICompileUnit(LLVMModuleRef Mod,
DICompileUnit **A,
DICompileUnit **B) {
report_fatal_error("ThinLTO not available");
}
extern "C" void
LLVMRustThinLTOPatchDICompileUnit(LLVMModuleRef Mod) {
report_fatal_error("ThinLTO not available");
}
extern "C" void
LLVMRustThinLTORemoveAvailableExternally(LLVMModuleRef Mod) {
report_fatal_error("ThinLTO not available");
}
rustc: Implement ThinLTO This commit is an implementation of LLVM's ThinLTO for consumption in rustc itself. Currently today LTO works by merging all relevant LLVM modules into one and then running optimization passes. "Thin" LTO operates differently by having more sharded work and allowing parallelism opportunities between optimizing codegen units. Further down the road Thin LTO also allows *incremental* LTO which should enable even faster release builds without compromising on the performance we have today. This commit uses a `-Z thinlto` flag to gate whether ThinLTO is enabled. It then also implements two forms of ThinLTO: * In one mode we'll *only* perform ThinLTO over the codegen units produced in a single compilation. That is, we won't load upstream rlibs, but we'll instead just perform ThinLTO amongst all codegen units produced by the compiler for the local crate. This is intended to emulate a desired end point where we have codegen units turned on by default for all crates and ThinLTO allows us to do this without performance loss. * In anther mode, like full LTO today, we'll optimize all upstream dependencies in "thin" mode. Unlike today, however, this LTO step is fully parallelized so should finish much more quickly. There's a good bit of comments about what the implementation is doing and where it came from, but the tl;dr; is that currently most of the support here is copied from upstream LLVM. This code duplication is done for a number of reasons: * Controlling parallelism means we can use the existing jobserver support to avoid overloading machines. * We will likely want a slightly different form of incremental caching which integrates with our own incremental strategy, but this is yet to be determined. * This buys us some flexibility about when/where we run ThinLTO, as well as having it tailored to fit our needs for the time being. * Finally this allows us to reuse some artifacts such as our `TargetMachine` creation, where all our options we used today aren't necessarily supported by upstream LLVM yet. My hope is that we can get some experience with this copy/paste in tree and then eventually upstream some work to LLVM itself to avoid the duplication while still ensuring our needs are met. Otherwise I fear that maintaining these bindings may be quite costly over the years with LLVM updates!
2017-07-23 15:14:38 +00:00
#endif // LLVM_VERSION_GE(4, 0)