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
Propagation of profile samples through the CFG. This adds a propagation heuristic to convert instruction samples into branch weights. It implements a similar heuristic to the one implemented by Dehao Chen on GCC. The propagation proceeds in 3 phases: 1- Assignment of block weights. All the basic blocks in the function are initial assigned the same weight as their most frequently executed instruction. 2- Creation of equivalence classes. Since samples may be missing from blocks, we can fill in the gaps by setting the weights of all the blocks in the same equivalence class to the same weight. To compute the concept of equivalence, we use dominance and loop information. Two blocks B1 and B2 are in the same equivalence class if B1 dominates B2, B2 post-dominates B1 and both are in the same loop. 3- Propagation of block weights into edges. This uses a simple propagation heuristic. The following rules are applied to every block B in the CFG: - If B has a single predecessor/successor, then the weight of that edge is the weight of the block. - If all the edges are known except one, and the weight of the block is already known, the weight of the unknown edge will be the weight of the block minus the sum of all the known edges. If the sum of all the known edges is larger than B's weight, we set the unknown edge weight to zero. - If there is a self-referential edge, and the weight of the block is known, the weight for that edge is set to the weight of the block minus the weight of the other incoming edges to that block (if known). Since this propagation is not guaranteed to finalize for every CFG, we only allow it to proceed for a limited number of iterations (controlled by -sample-profile-max-propagate-iterations). It currently uses the same GCC default of 100. Before propagation starts, the pass builds (for each block) a list of unique predecessors and successors. This is necessary to handle identical edges in multiway branches. Since we visit all blocks and all edges of the CFG, it is cleaner to build these lists once at the start of the pass. Finally, the patch fixes the computation of relative line locations. The profiler emits lines relative to the function header. To discover it, we traverse the compilation unit looking for the subprogram corresponding to the function. The line number of that subprogram is the line where the function begins. That becomes line zero for all the relative locations. llvm-svn: 198972
2014-01-11 07:23:46 +08:00
; CHECK: edge if.end -> for.body probability is 1 / 2 = 50%
; CHECK: edge if.end -> if.end6 probability is 1 / 2 = 50%
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
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
Propagation of profile samples through the CFG. This adds a propagation heuristic to convert instruction samples into branch weights. It implements a similar heuristic to the one implemented by Dehao Chen on GCC. The propagation proceeds in 3 phases: 1- Assignment of block weights. All the basic blocks in the function are initial assigned the same weight as their most frequently executed instruction. 2- Creation of equivalence classes. Since samples may be missing from blocks, we can fill in the gaps by setting the weights of all the blocks in the same equivalence class to the same weight. To compute the concept of equivalence, we use dominance and loop information. Two blocks B1 and B2 are in the same equivalence class if B1 dominates B2, B2 post-dominates B1 and both are in the same loop. 3- Propagation of block weights into edges. This uses a simple propagation heuristic. The following rules are applied to every block B in the CFG: - If B has a single predecessor/successor, then the weight of that edge is the weight of the block. - If all the edges are known except one, and the weight of the block is already known, the weight of the unknown edge will be the weight of the block minus the sum of all the known edges. If the sum of all the known edges is larger than B's weight, we set the unknown edge weight to zero. - If there is a self-referential edge, and the weight of the block is known, the weight for that edge is set to the weight of the block minus the weight of the other incoming edges to that block (if known). Since this propagation is not guaranteed to finalize for every CFG, we only allow it to proceed for a limited number of iterations (controlled by -sample-profile-max-propagate-iterations). It currently uses the same GCC default of 100. Before propagation starts, the pass builds (for each block) a list of unique predecessors and successors. This is necessary to handle identical edges in multiway branches. Since we visit all blocks and all edges of the CFG, it is cleaner to build these lists once at the start of the pass. Finally, the patch fixes the computation of relative line locations. The profiler emits lines relative to the function header. To discover it, we traverse the compilation unit looking for the subprogram corresponding to the function. The line number of that subprogram is the line where the function begins. That becomes line zero for all the relative locations. llvm-svn: 198972
2014-01-11 07:23:46 +08:00
; CHECK: edge for.body -> if.end6 probability is 1 / 10227 = 0.00977804
; CHECK: edge for.body -> for.body probability is 10226 / 10227 = 99.9902% [HOT edge]
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
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
!llvm.ident = !{!26}
!0 = metadata !{i32 786449, metadata !1, i32 4, metadata !"clang version 3.4 (trunk 192896) (llvm/trunk 192895)", i1 true, metadata !"", i32 0, metadata !2, metadata !2, metadata !3, metadata !2, metadata !2, metadata !""} ; [ DW_TAG_compile_unit ] [./branch.cc] [DW_LANG_C_plus_plus]
!1 = metadata !{metadata !"branch.cc", metadata !"."}
!2 = metadata !{i32 0}
!3 = metadata !{metadata !4}
!4 = metadata !{i32 786478, metadata !1, metadata !5, metadata !"main", metadata !"main", metadata !"", i32 4, metadata !6, i1 false, i1 true, i32 0, i32 0, null, i32 256, i1 true, i32 (i32, i8**)* @main, null, null, metadata !12, i32 4} ; [ DW_TAG_subprogram ] [line 4] [def] [main]
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!6 = metadata !{i32 786453, i32 0, null, metadata !"", i32 0, i64 0, i64 0, i64 0, i32 0, null, metadata !7, i32 0, null, null, null} ; [ DW_TAG_subroutine_type ] [line 0, size 0, align 0, offset 0] [from ]
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