Finer grained precompile native code cache (part 1)#58592
Finer grained precompile native code cache (part 1)#58592xal-0 wants to merge 10 commits intoJuliaLang:masterfrom
Conversation
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This is fantastic! I have long been wanting to explore more fine-grained compilation caching using approaches like My big picture questions would be:
Another concern is the many small files since they often perform very badly, so something along the line of |
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It's a little different from the GPUCompiler approach, since it makes no attempt The idea with this PR is to do the minimum thing that will give a correct llvm-cas possibly being merged soon is the reason I have so far avoided pulling So far, there is no invalidation, pending a switch to a real KV store. |
This confusingly sounds like something we already have. It might be good to make it clearer in the title and top comment how this differentiates from the current situation. |
It sounds like that isn't an issue for this approach, but it could be possible to have a cache keyed by CodeInstances that is only used during precompilation, where uniqueness is guaranteed. Yes, precompilation is already generating a cached code, but we can have multiple layers of caching, and this could be used to speed up precompilation. |
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Reverted two commits that were an attempt at getting better cache hit rates with the simplest possible change, in favour of doing a link-time rename step. |
src/codegen.cpp
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| static StringMap<uint64_t> fresh_name_map; | ||
| static std::mutex fresh_name_lock; | ||
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| static void freshen_name(std::string &name) | ||
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| uint64_t n; | ||
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| std::lock_guard guard{fresh_name_lock}; | ||
| n = fresh_name_map[name]++; | ||
| } | ||
| raw_string_ostream(name) << "_" << n; | ||
| } |
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I am worried that this map could grow big. What issue are you trying to solve here? Just that the order of generation causes different names?
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Yes, this was an attempt at getting reasonable hit rates with the minimum amount of work; it turned out not to be worth it. The new plan is to abandon globally unique names at this stage and resolve things after code generation, but before linking.
# Overview This PR overhauls the way linking works in Julia, both in the JIT and AOT. The point is to enable us to generate LLVM IR that depends only on the source IR, eliminating both nondeterminism and statefulness. This serves two purposes. First, if the IR is predictable, we can cache compile objects using the bitcode hash as a key, like how the ThinLTO cache works. #58592 was an early experiment along these lines. Second, we can reuse work that was done in a previous session, like pkgimages, but for the JIT. We accomplish this by generating names that are unique only within the current LLVM module, removing most uses of the `globalUniqueGeneratedNames` counter. The replacement for `jl_codegen_params_t`, `jl_codegen_output_t`, represents a Julia "translation unit", and tracks the information we'll need to link the compiled module into the running session. When linking, we manipulate the JITLink [LinkGraph](https://llvm.org/docs/JITLink.html#linkgraph) (after compilation) instead of renaming functions in the LLVM IR (before). ## Example ``` julia> @noinline foo(x) = x + 2.0 baz(x) = foo(foo(x)) code_llvm(baz, (Int64,); dump_module=true, optimize=false) ``` Nightly: ```llvm [...] @"+Core.Float64#774" = private unnamed_addr constant ptr @"+Core.Float64#774.jit" @"+Core.Float64#774.jit" = private alias ptr, inttoptr (i64 4797624416 to ptr) ; Function Signature: baz(Int64) ; @ REPL[1]:2 within `baz` define double @julia_baz_772(i64 signext %"x::Int64") #0 { top: %pgcstack = call ptr @julia.get_pgcstack() %0 = call double @j_foo_775(i64 signext %"x::Int64") %1 = call double @j_foo_776(double %0) ret double %1 } ; Function Attrs: noinline optnone define nonnull ptr @jfptr_baz_773(ptr %"function::Core.Function", ptr noalias nocapture noundef readonly %"args::Any[]", i32 %"nargs::UInt32") #1 { top: %pgcstack = call ptr @julia.get_pgcstack() %0 = getelementptr inbounds i8, ptr %"args::Any[]", i32 0 %1 = load ptr, ptr %0, align 8 %.unbox = load i64, ptr %1, align 8 %2 = call double @julia_baz_772(i64 signext %.unbox) %"+Core.Float64#774" = load ptr, ptr @"+Core.Float64#774", align 8 %Float64 = ptrtoint ptr %"+Core.Float64#774" to i64 %3 = inttoptr i64 %Float64 to ptr %current_task = getelementptr inbounds i8, ptr %pgcstack, i32 -152 %"box::Float64" = call noalias nonnull align 8 dereferenceable(8) ptr @julia.gc_alloc_obj(ptr %current_task, i64 8, ptr %3) #5 store double %2, ptr %"box::Float64", align 8 ret ptr %"box::Float64" } [...] ``` Diff after this PR. Notice how each symbol gets the lowest possible integer suffix that will make it unique to the module, and how the two specializations for `foo` get different names: ```diff @@ -4,18 +4,18 @@ target triple = "arm64-apple-darwin24.6.0" -@"+Core.Float64#774" = external global ptr +@"+Core.Float64#_0" = external global ptr ; Function Signature: baz(Int64) ; @ REPL[1]:2 within `baz` -define double @julia_baz_772(i64 signext %"x::Int64") #0 { +define double @julia_baz_0(i64 signext %"x::Int64") #0 { top: %pgcstack = call ptr @julia.get_pgcstack() - %0 = call double @j_foo_775(i64 signext %"x::Int64") - %1 = call double @j_foo_776(double %0) + %0 = call double @j_foo_0(i64 signext %"x::Int64") + %1 = call double @j_foo_1(double %0) ret double %1 } ; Function Attrs: noinline optnone -define nonnull ptr @jfptr_baz_773(ptr %"function::Core.Function", ptr noalias nocapture noundef readonly %"args::Any[]", i32 %"nargs::UInt32") #1 { +define nonnull ptr @jfptr_baz_0(ptr %"function::Core.Function", ptr noalias nocapture noundef readonly %"args::Any[]", i32 %"nargs::UInt32") #1 { top: %pgcstack = call ptr @julia.get_pgcstack() @@ -23,7 +23,7 @@ %1 = load ptr, ptr %0, align 8 %.unbox = load i64, ptr %1, align 8 - %2 = call double @julia_baz_772(i64 signext %.unbox) - %"+Core.Float64#774" = load ptr, ptr @"+Core.Float64#774", align 8 - %Float64 = ptrtoint ptr %"+Core.Float64#774" to i64 + %2 = call double @julia_baz_0(i64 signext %.unbox) + %"+Core.Float64#_0" = load ptr, ptr @"+Core.Float64#_0", align 8 + %Float64 = ptrtoint ptr %"+Core.Float64#_0" to i64 %3 = inttoptr i64 %Float64 to ptr %current_task = getelementptr inbounds i8, ptr %pgcstack, i32 -152 @@ -39,8 +39,8 @@ ; Function Signature: foo(Int64) -declare double @j_foo_775(i64 signext) #3 +declare double @j_foo_0(i64 signext) #3 ; Function Signature: foo(Float64) -declare double @j_foo_776(double) #4 +declare double @j_foo_1(double) #4 attributes #0 = { "frame-pointer"="all" "julia.fsig"="baz(Int64)" "probe-stack"="inline-asm" } ``` ## List of changes - Many sources of statefulness and nondeterminism in the emitted LLVM IR have been eliminated, namely: - Function symbols defined for CodeInstances - Global symbols referring to data on the Julia heap - Undefined function symbols referring to invoked external CodeInstances - `jl_codeinst_params_t` has become `jl_codegen_output_t`. It now represents one Julia "translation unit". More than one CodeInstance can be emitted to the same `jl_codegen_output_t`, if desired, though in the JIT every CI gets its own right now. One motivation behind this is to allow us to emit code on multiple threads and avoid the bitcode serialize/deserialize step we currently do, if that proves worthwhile. When we are done emitting to a `jl_codegen_output_t`, we call `.finish()`, which discards the intermediate state and returns only the LLVM module and the info needed for linking (`jl_linker_info_t`). - The new `JLMaterializationUnit` wraps emitting Julia LLVM modules and the associated `jl_linker_info_t`. It informs ORC that we can materialize symbols for the CIs defined by that output, and picks globally unique names for them. When it is materialized, it resolves all the call targets and generates trampolines for CodeInstances that are invoked but have the wrong calling convention, or are not yet compiled. - We now postpone linking decisions to after codegen whenever possible. For example, `emit_invoke` no longer tries to find a compiled version of the CodeInstance, and it no longer generates trampolines to adapt calling conventions. `jl_analyze_workqueue`'s job has been absorbed into `JuliaOJIT::linkOutput`. - Some `image_codegen` differences have been removed: - Codegen no longer cares if a compiled CodeInstance came from an image. During ahead-of-time linking, we generate thunk functions that load the address from the fvars table. - In `jl_emit_native_impl`, emit every CodeInstance into one `jl_codegen_output_t`. We now defer the creation of the `llvm::Linker` for llvmcalls, which has construction cost that grows with the size of the destination module, until the very end. - RTDyld is removed completely, since we cannot control linking like we can with JITLink. Since #60105, platforms that previous used the optimized memory manager now use the new one. ### General refactoring - Adapt the `jl_callingconv_t` enum from `staticdata.c` into `jl_invoke_api_t` and use it in more places. There is one enumerator for each special `jl_callptr_t` function that can go in a CodeInstance's `invoke` field, as well as one that indicates an invoke wrapper should be there. There is a convenience function for reading an invoke pointer and getting the API type, and vice versa. - Avoid using magic string values, and try to directly pass pointers to LLVM `Function *` or ORC string pool entries when possible. ## Future work - `DLSymOptimizer` should be mostly removed, in favour of emitting raw ccalls and redirecting them to the appropriate target during linking. - We should support ahead-of-time linking multiple `jl_codegen_output_t`s together, in order to parallelize LLVM IR emission when compiling a system image. - We still pass strings to `emit_call_specfun_other`, even though the prototype for the function is now created by `jl_codegen_output_t::get_call_target`. We should hold on to the calling convention info so it doesn't have to be recomputed.
# Overview This PR overhauls the way linking works in Julia, both in the JIT and AOT. The point is to enable us to generate LLVM IR that depends only on the source IR, eliminating both nondeterminism and statefulness. This serves two purposes. First, if the IR is predictable, we can cache compile objects using the bitcode hash as a key, like how the ThinLTO cache works. JuliaLang#58592 was an early experiment along these lines. Second, we can reuse work that was done in a previous session, like pkgimages, but for the JIT. We accomplish this by generating names that are unique only within the current LLVM module, removing most uses of the `globalUniqueGeneratedNames` counter. The replacement for `jl_codegen_params_t`, `jl_codegen_output_t`, represents a Julia "translation unit", and tracks the information we'll need to link the compiled module into the running session. When linking, we manipulate the JITLink [LinkGraph](https://llvm.org/docs/JITLink.html#linkgraph) (after compilation) instead of renaming functions in the LLVM IR (before). ## Example ``` julia> @noinline foo(x) = x + 2.0 baz(x) = foo(foo(x)) code_llvm(baz, (Int64,); dump_module=true, optimize=false) ``` Nightly: ```llvm [...] @"+Core.Float64#774" = private unnamed_addr constant ptr @"+Core.Float64#774.jit" @"+Core.Float64#774.jit" = private alias ptr, inttoptr (i64 4797624416 to ptr) ; Function Signature: baz(Int64) ; @ REPL[1]:2 within `baz` define double @julia_baz_772(i64 signext %"x::Int64") #0 { top: %pgcstack = call ptr @julia.get_pgcstack() %0 = call double @j_foo_775(i64 signext %"x::Int64") %1 = call double @j_foo_776(double %0) ret double %1 } ; Function Attrs: noinline optnone define nonnull ptr @jfptr_baz_773(ptr %"function::Core.Function", ptr noalias nocapture noundef readonly %"args::Any[]", i32 %"nargs::UInt32") JuliaLang#1 { top: %pgcstack = call ptr @julia.get_pgcstack() %0 = getelementptr inbounds i8, ptr %"args::Any[]", i32 0 %1 = load ptr, ptr %0, align 8 %.unbox = load i64, ptr %1, align 8 %2 = call double @julia_baz_772(i64 signext %.unbox) %"+Core.Float64#774" = load ptr, ptr @"+Core.Float64#774", align 8 %Float64 = ptrtoint ptr %"+Core.Float64#774" to i64 %3 = inttoptr i64 %Float64 to ptr %current_task = getelementptr inbounds i8, ptr %pgcstack, i32 -152 %"box::Float64" = call noalias nonnull align 8 dereferenceable(8) ptr @julia.gc_alloc_obj(ptr %current_task, i64 8, ptr %3) JuliaLang#5 store double %2, ptr %"box::Float64", align 8 ret ptr %"box::Float64" } [...] ``` Diff after this PR. Notice how each symbol gets the lowest possible integer suffix that will make it unique to the module, and how the two specializations for `foo` get different names: ```diff @@ -4,18 +4,18 @@ target triple = "arm64-apple-darwin24.6.0" -@"+Core.Float64#774" = external global ptr +@"+Core.Float64#_0" = external global ptr ; Function Signature: baz(Int64) ; @ REPL[1]:2 within `baz` -define double @julia_baz_772(i64 signext %"x::Int64") #0 { +define double @julia_baz_0(i64 signext %"x::Int64") #0 { top: %pgcstack = call ptr @julia.get_pgcstack() - %0 = call double @j_foo_775(i64 signext %"x::Int64") - %1 = call double @j_foo_776(double %0) + %0 = call double @j_foo_0(i64 signext %"x::Int64") + %1 = call double @j_foo_1(double %0) ret double %1 } ; Function Attrs: noinline optnone -define nonnull ptr @jfptr_baz_773(ptr %"function::Core.Function", ptr noalias nocapture noundef readonly %"args::Any[]", i32 %"nargs::UInt32") JuliaLang#1 { +define nonnull ptr @jfptr_baz_0(ptr %"function::Core.Function", ptr noalias nocapture noundef readonly %"args::Any[]", i32 %"nargs::UInt32") JuliaLang#1 { top: %pgcstack = call ptr @julia.get_pgcstack() @@ -23,7 +23,7 @@ %1 = load ptr, ptr %0, align 8 %.unbox = load i64, ptr %1, align 8 - %2 = call double @julia_baz_772(i64 signext %.unbox) - %"+Core.Float64#774" = load ptr, ptr @"+Core.Float64#774", align 8 - %Float64 = ptrtoint ptr %"+Core.Float64#774" to i64 + %2 = call double @julia_baz_0(i64 signext %.unbox) + %"+Core.Float64#_0" = load ptr, ptr @"+Core.Float64#_0", align 8 + %Float64 = ptrtoint ptr %"+Core.Float64#_0" to i64 %3 = inttoptr i64 %Float64 to ptr %current_task = getelementptr inbounds i8, ptr %pgcstack, i32 -152 @@ -39,8 +39,8 @@ ; Function Signature: foo(Int64) -declare double @j_foo_775(i64 signext) JuliaLang#3 +declare double @j_foo_0(i64 signext) JuliaLang#3 ; Function Signature: foo(Float64) -declare double @j_foo_776(double) JuliaLang#4 +declare double @j_foo_1(double) JuliaLang#4 attributes #0 = { "frame-pointer"="all" "julia.fsig"="baz(Int64)" "probe-stack"="inline-asm" } ``` ## List of changes - Many sources of statefulness and nondeterminism in the emitted LLVM IR have been eliminated, namely: - Function symbols defined for CodeInstances - Global symbols referring to data on the Julia heap - Undefined function symbols referring to invoked external CodeInstances - `jl_codeinst_params_t` has become `jl_codegen_output_t`. It now represents one Julia "translation unit". More than one CodeInstance can be emitted to the same `jl_codegen_output_t`, if desired, though in the JIT every CI gets its own right now. One motivation behind this is to allow us to emit code on multiple threads and avoid the bitcode serialize/deserialize step we currently do, if that proves worthwhile. When we are done emitting to a `jl_codegen_output_t`, we call `.finish()`, which discards the intermediate state and returns only the LLVM module and the info needed for linking (`jl_linker_info_t`). - The new `JLMaterializationUnit` wraps emitting Julia LLVM modules and the associated `jl_linker_info_t`. It informs ORC that we can materialize symbols for the CIs defined by that output, and picks globally unique names for them. When it is materialized, it resolves all the call targets and generates trampolines for CodeInstances that are invoked but have the wrong calling convention, or are not yet compiled. - We now postpone linking decisions to after codegen whenever possible. For example, `emit_invoke` no longer tries to find a compiled version of the CodeInstance, and it no longer generates trampolines to adapt calling conventions. `jl_analyze_workqueue`'s job has been absorbed into `JuliaOJIT::linkOutput`. - Some `image_codegen` differences have been removed: - Codegen no longer cares if a compiled CodeInstance came from an image. During ahead-of-time linking, we generate thunk functions that load the address from the fvars table. - In `jl_emit_native_impl`, emit every CodeInstance into one `jl_codegen_output_t`. We now defer the creation of the `llvm::Linker` for llvmcalls, which has construction cost that grows with the size of the destination module, until the very end. - RTDyld is removed completely, since we cannot control linking like we can with JITLink. Since JuliaLang#60105, platforms that previous used the optimized memory manager now use the new one. ### General refactoring - Adapt the `jl_callingconv_t` enum from `staticdata.c` into `jl_invoke_api_t` and use it in more places. There is one enumerator for each special `jl_callptr_t` function that can go in a CodeInstance's `invoke` field, as well as one that indicates an invoke wrapper should be there. There is a convenience function for reading an invoke pointer and getting the API type, and vice versa. - Avoid using magic string values, and try to directly pass pointers to LLVM `Function *` or ORC string pool entries when possible. ## Future work - `DLSymOptimizer` should be mostly removed, in favour of emitting raw ccalls and redirecting them to the appropriate target during linking. - We should support ahead-of-time linking multiple `jl_codegen_output_t`s together, in order to parallelize LLVM IR emission when compiling a system image. - We still pass strings to `emit_call_specfun_other`, even though the prototype for the function is now created by `jl_codegen_output_t::get_call_target`. We should hold on to the calling convention info so it doesn't have to be recomputed.
Overview
This pull request adds a new mode for precompiling sysimages and pkgimages that caches the results of compiling each LLVM module, reducing the time spent emitting native code for CodeInstances that generate identical LLVM IR. For now, it works only when using the ahead-of-time compiler, but the approach is also valid for JITed code.
Usage
Set
JULIA_NATIVE_CACHE=<dir>to look for and store compiled objects in<dir>. WhenJULIA_IMAGE_TIMINGS=1is also set, the cache hit rate will be printed, like:Internals
Normally,
jl_emit_nativeemits every CodeInstance into a separate LLVM module before combining everything into a single module. When the fine-grained cache is enabled, the modules are serialized to bitcode separately. The cache key for each module is computed from the hash of the serialized bitcode and the LLVM version, and the compiled object file is the value.The
partitionModulepass is not run, since multi-threaded compilation is done by havingJULIA_IMAGE_THREADSworker threads take from the queue of serialized modules.When the fine-grained cache is used, we generate a single
jl_image_shard_ttable for the entire image. Thegvar_offsetsare resolved by the linker.Currently, the cache uses LLVM's
FileCache, a thread safe key-value store that uses one file per key and write-and-rename to implement atomic updates. It's a convenient choice for development because the contents can be easilyobjdumped, but the long term plan is to switch to a more appropriate database, be it LLVMCAS when it is merged, or sqlite.Current limitations
.ooutputs are cached. The fine-grained cache cannot be used if--output-bc,--output-unopt-bcor--output-asmare specified.jl_get_llvm_module_impl,jl_get_llvm_function_impl,jl_emit_native_implwithllvmmodset).Plan