llvm-project/llvm/test/Transforms/SampleProfile/branch.ll

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SampleProfileLoader pass. Initial setup. This adds a new scalar pass that reads a file with samples generated by 'perf' during runtime. The samples read from the profile are incorporated and emmited as IR metadata reflecting that profile. The profile file is assumed to have been generated by an external profile source. The profile information is converted into IR metadata, which is later used by the analysis routines to estimate block frequencies, edge weights and other related data. External profile information files have no fixed format, each profiler is free to define its own. This includes both the on-disk representation of the profile and the kind of profile information stored in the file. A common kind of profile is based on sampling (e.g., perf), which essentially counts how many times each line of the program has been executed during the run. The SampleProfileLoader pass is organized as a scalar transformation. On startup, it reads the file given in -sample-profile-file to determine what kind of profile it contains. This file is assumed to contain profile information for the whole application. The profile data in the file is read and incorporated into the internal state of the corresponding profiler. To facilitate testing, I've organized the profilers to support two file formats: text and native. The native format is whatever on-disk representation the profiler wants to support, I think this will mostly be bitcode files, but it could be anything the profiler wants to support. To do this, every profiler must implement the SampleProfile::loadNative() function. The text format is mostly meant for debugging. Records are separated by newlines, but each profiler is free to interpret records as it sees fit. Profilers must implement the SampleProfile::loadText() function. Finally, the pass will call SampleProfile::emitAnnotations() for each function in the current translation unit. This function needs to translate the loaded profile into IR metadata, which the analyzer will later be able to use. This patch implements the first steps towards the above design. I've implemented a sample-based flat profiler. The format of the profile is fairly simplistic. Each sampled function contains a list of relative line locations (from the start of the function) together with a count representing how many samples were collected at that line during execution. I generate this profile using perf and a separate converter tool. Currently, I have only implemented a text format for these profiles. I am interested in initial feedback to the whole approach before I send the other parts of the implementation for review. This patch implements: - The SampleProfileLoader pass. - The base ExternalProfile class with the core interface. - A SampleProfile sub-class using the above interface. The profiler generates branch weight metadata on every branch instructions that matches the profiles. - A text loader class to assist the implementation of SampleProfile::loadText(). - Basic unit tests for the pass. Additionally, the patch uses profile information to compute branch weights based on instruction samples. This patch converts instruction samples into branch weights. It does a fairly simplistic conversion: Given a multi-way branch instruction, it calculates the weight of each branch based on the maximum sample count gathered from each target basic block. Note that this assignment of branch weights is somewhat lossy and can be misleading. If a basic block has more than one incoming branch, all the incoming branches will get the same weight. In reality, it may be that only one of them is the most heavily taken branch. I will adjust this assignment in subsequent patches. llvm-svn: 194566
2013-11-13 20:22:21 +08:00
; RUN: opt < %s -sample-profile -sample-profile-file=%S/Inputs/branch.prof | opt -analyze -branch-prob | FileCheck %s
; Original C++ code for this test case:
;
; #include <stdio.h>
; #include <stdlib.h>
;
; int main(int argc, char *argv[]) {
; if (argc < 2)
; return 1;
; double result;
; int limit = atoi(argv[1]);
; if (limit > 100) {
; double s = 23.041968;
; for (int u = 0; u < limit; u++) {
; double x = s;
; s = x + 3.049 + (double)u;
; s -= s + 3.94 / x * 0.32;
; }
; result = s;
; } else {
; result = 0;
; }
; printf("result is %lf\n", result);
; return 0;
; }
@.str = private unnamed_addr constant [15 x i8] c"result is %lf\0A\00", align 1
; Function Attrs: nounwind uwtable
define i32 @main(i32 %argc, i8** nocapture readonly %argv) #0 {
; CHECK: Printing analysis 'Branch Probability Analysis' for function 'main':
entry:
tail call void @llvm.dbg.value(metadata !{i32 %argc}, i64 0, metadata !13), !dbg !27
tail call void @llvm.dbg.value(metadata !{i8** %argv}, i64 0, metadata !14), !dbg !27
%cmp = icmp slt i32 %argc, 2, !dbg !28
br i1 %cmp, label %return, label %if.end, !dbg !28
; CHECK: edge entry -> return probability is 1 / 2 = 50%
; CHECK: edge entry -> if.end probability is 1 / 2 = 50%
if.end: ; preds = %entry
%arrayidx = getelementptr inbounds i8** %argv, i64 1, !dbg !30
%0 = load i8** %arrayidx, align 8, !dbg !30, !tbaa !31
%call = tail call i32 @atoi(i8* %0) #4, !dbg !30
tail call void @llvm.dbg.value(metadata !{i32 %call}, i64 0, metadata !17), !dbg !30
%cmp1 = icmp sgt i32 %call, 100, !dbg !35
br i1 %cmp1, label %for.body, label %if.end6, !dbg !35
; CHECK: edge if.end -> for.body probability is 2243 / 2244 = 99.9554% [HOT edge]
; CHECK: edge if.end -> if.end6 probability is 1 / 2244 = 0.0445633%
for.body: ; preds = %if.end, %for.body
%u.016 = phi i32 [ %inc, %for.body ], [ 0, %if.end ]
%s.015 = phi double [ %sub, %for.body ], [ 0x40370ABE6A337A81, %if.end ]
%add = fadd double %s.015, 3.049000e+00, !dbg !36
%conv = sitofp i32 %u.016 to double, !dbg !36
%add4 = fadd double %add, %conv, !dbg !36
tail call void @llvm.dbg.value(metadata !{double %add4}, i64 0, metadata !18), !dbg !36
%div = fdiv double 3.940000e+00, %s.015, !dbg !37
%mul = fmul double %div, 3.200000e-01, !dbg !37
%add5 = fadd double %add4, %mul, !dbg !37
%sub = fsub double %add4, %add5, !dbg !37
tail call void @llvm.dbg.value(metadata !{double %sub}, i64 0, metadata !18), !dbg !37
%inc = add nsw i32 %u.016, 1, !dbg !38
tail call void @llvm.dbg.value(metadata !{i32 %inc}, i64 0, metadata !21), !dbg !38
%exitcond = icmp eq i32 %inc, %call, !dbg !38
br i1 %exitcond, label %if.end6, label %for.body, !dbg !38
; CHECK: edge for.body -> if.end6 probability is 1 / 2244 = 0.0445633%
; CHECK: edge for.body -> for.body probability is 2243 / 2244 = 99.9554% [HOT edge]
if.end6: ; preds = %for.body, %if.end
%result.0 = phi double [ 0.000000e+00, %if.end ], [ %sub, %for.body ]
%call7 = tail call i32 (i8*, ...)* @printf(i8* getelementptr inbounds ([15 x i8]* @.str, i64 0, i64 0), double %result.0), !dbg !39
br label %return, !dbg !40
; CHECK: edge if.end6 -> return probability is 16 / 16 = 100% [HOT edge]
return: ; preds = %entry, %if.end6
%retval.0 = phi i32 [ 0, %if.end6 ], [ 1, %entry ]
ret i32 %retval.0, !dbg !41
}
; Function Attrs: nounwind readonly
declare i32 @atoi(i8* nocapture) #1
; Function Attrs: nounwind
declare i32 @printf(i8* nocapture readonly, ...) #2
; Function Attrs: nounwind readnone
declare void @llvm.dbg.value(metadata, i64, metadata) #3
attributes #0 = { nounwind uwtable "less-precise-fpmad"="false" "no-frame-pointer-elim"="false" "no-infs-fp-math"="false" "no-nans-fp-math"="false" "stack-protector-buffer-size"="8" "unsafe-fp-math"="false" "use-soft-float"="false" }
attributes #1 = { nounwind readonly "less-precise-fpmad"="false" "no-frame-pointer-elim"="false" "no-infs-fp-math"="false" "no-nans-fp-math"="false" "stack-protector-buffer-size"="8" "unsafe-fp-math"="false" "use-soft-float"="false" }
attributes #2 = { nounwind "less-precise-fpmad"="false" "no-frame-pointer-elim"="false" "no-infs-fp-math"="false" "no-nans-fp-math"="false" "stack-protector-buffer-size"="8" "unsafe-fp-math"="false" "use-soft-float"="false" }
attributes #3 = { nounwind readnone }
attributes #4 = { nounwind readonly }
!llvm.dbg.cu = !{!0}
!llvm.module.flags = !{!25, !42}
SampleProfileLoader pass. Initial setup. This adds a new scalar pass that reads a file with samples generated by 'perf' during runtime. The samples read from the profile are incorporated and emmited as IR metadata reflecting that profile. The profile file is assumed to have been generated by an external profile source. The profile information is converted into IR metadata, which is later used by the analysis routines to estimate block frequencies, edge weights and other related data. External profile information files have no fixed format, each profiler is free to define its own. This includes both the on-disk representation of the profile and the kind of profile information stored in the file. A common kind of profile is based on sampling (e.g., perf), which essentially counts how many times each line of the program has been executed during the run. The SampleProfileLoader pass is organized as a scalar transformation. On startup, it reads the file given in -sample-profile-file to determine what kind of profile it contains. This file is assumed to contain profile information for the whole application. The profile data in the file is read and incorporated into the internal state of the corresponding profiler. To facilitate testing, I've organized the profilers to support two file formats: text and native. The native format is whatever on-disk representation the profiler wants to support, I think this will mostly be bitcode files, but it could be anything the profiler wants to support. To do this, every profiler must implement the SampleProfile::loadNative() function. The text format is mostly meant for debugging. Records are separated by newlines, but each profiler is free to interpret records as it sees fit. Profilers must implement the SampleProfile::loadText() function. Finally, the pass will call SampleProfile::emitAnnotations() for each function in the current translation unit. This function needs to translate the loaded profile into IR metadata, which the analyzer will later be able to use. This patch implements the first steps towards the above design. I've implemented a sample-based flat profiler. The format of the profile is fairly simplistic. Each sampled function contains a list of relative line locations (from the start of the function) together with a count representing how many samples were collected at that line during execution. I generate this profile using perf and a separate converter tool. Currently, I have only implemented a text format for these profiles. I am interested in initial feedback to the whole approach before I send the other parts of the implementation for review. This patch implements: - The SampleProfileLoader pass. - The base ExternalProfile class with the core interface. - A SampleProfile sub-class using the above interface. The profiler generates branch weight metadata on every branch instructions that matches the profiles. - A text loader class to assist the implementation of SampleProfile::loadText(). - Basic unit tests for the pass. Additionally, the patch uses profile information to compute branch weights based on instruction samples. This patch converts instruction samples into branch weights. It does a fairly simplistic conversion: Given a multi-way branch instruction, it calculates the weight of each branch based on the maximum sample count gathered from each target basic block. Note that this assignment of branch weights is somewhat lossy and can be misleading. If a basic block has more than one incoming branch, all the incoming branches will get the same weight. In reality, it may be that only one of them is the most heavily taken branch. I will adjust this assignment in subsequent patches. llvm-svn: 194566
2013-11-13 20:22:21 +08:00
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