b9d40a7ae4
The profile density feature(the amount of samples in the profile relative to the program size) is used to identify insufficient sample issue and provide hints for user to increase sample count. A low-density profile can be inaccurate due to statistical noise, which can hurt FDO performance. This change introduces two improvements to the current density work. 1. The density calculation/definition is changed. Previously, the density of a profile was calculated as the minimum density for all warm functions (a function was considered warm if its total samples were within the top N percent of the profile). However, there is a problem that a high total sample profile can have a very low density, which makes the density value unstable. - Instead, we want to find a density number such that if a function's density is below this value, it is considered low-density function. We consider the whole profile is bad if a group of low-density functions have the sum of samples that exceeds N percent cut-off of the total samples. - In implementation, we sort the function profiles by density, iterate them in descending order and keep accumulating the body samples until the sum exceeds the (100% - N) percentage of the total_samples, the profile-density is the last(minimum) function-density of processed functions. We introduce the a flag(`--profile-density-threshold`) for this percentage threshold. 2. The density is now calculated based on final(compiler used) profiles instead of merged context-less profiles.
69 lines
2.9 KiB
Plaintext
69 lines
2.9 KiB
Plaintext
; RUN: llvm-profgen --format=text --unsymbolized-profile=%S/Inputs/profile-density.raw.prof --binary=%S/Inputs/inline-noprobe2.perfbin --output=%t1 --use-offset=0 --show-density -profile-density-threshold=10 --trim-cold-profile=0 &> %t2
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; RUN: FileCheck %s --input-file %t2 --check-prefix=CHECK-DENSITY
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; RUN: llvm-profgen --format=text --unsymbolized-profile=%S/Inputs/profile-density-cs.raw.prof --binary=%S/Inputs/inline-noprobe2.perfbin --output=%t3 --show-density -profile-density-threshold=1 -profile-density-threshold=10000 &> %t4
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; RUN: FileCheck %s --input-file %t4 --check-prefix=CHECK-DENSITY-CS
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; RUN: llvm-profgen --format=text --unsymbolized-profile=%S/Inputs/profile-density-cs.raw.prof --binary=%S/Inputs/inline-noprobe2.perfbin --output=%t5 --show-density -profile-density-threshold=1 -profile-density-cutoff-hot=800000 &> %t6
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; RUN: FileCheck %s --input-file %t6 --check-prefix=CHECK-DENSITY-CS-80
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;CHECK-DENSITY: Sample PGO is estimated to optimize better with 2.9x more samples. Please consider increasing sampling rate or profiling for longer duration to get more samples.
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;CHECK-DENSITY: Functions with density >= 3.5 account for 99.00% total sample counts.
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;CHECK-DENSITY-CS: Sample PGO is estimated to optimize better with 12.5x more samples. Please consider increasing sampling rate or profiling for longer duration to get more samples.
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;CHECK-DENSITY-CS: Functions with density >= 800.1 account for 99.00% total sample counts.
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;CHECK-DENSITY-CS-80: Functions with density >= 1886.2 account for 80.00% total sample counts.
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; original code:
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; clang -O3 -g -fno-optimize-sibling-calls -fdebug-info-for-profiling qsort.c -o a.out
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#include <stdio.h>
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#include <stdlib.h>
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void swap(int *a, int *b) {
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int t = *a;
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*a = *b;
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*b = t;
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}
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int partition_pivot_last(int* array, int low, int high) {
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int pivot = array[high];
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int i = low - 1;
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for (int j = low; j < high; j++)
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if (array[j] < pivot)
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swap(&array[++i], &array[j]);
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swap(&array[i + 1], &array[high]);
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return (i + 1);
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}
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int partition_pivot_first(int* array, int low, int high) {
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int pivot = array[low];
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int i = low + 1;
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for (int j = low + 1; j <= high; j++)
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if (array[j] < pivot) { if (j != i) swap(&array[i], &array[j]); i++;}
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swap(&array[i - 1], &array[low]);
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return i - 1;
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}
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void quick_sort(int* array, int low, int high, int (*partition_func)(int *, int, int)) {
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if (low < high) {
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int pi = (*partition_func)(array, low, high);
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quick_sort(array, low, pi - 1, partition_func);
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quick_sort(array, pi + 1, high, partition_func);
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}
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}
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int main() {
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const int size = 200;
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int sum = 0;
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int *array = malloc(size * sizeof(int));
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for(int i = 0; i < 100 * 1000; i++) {
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for(int j = 0; j < size; j++)
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array[j] = j % 10 ? rand() % size: j;
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int (*fptr)(int *, int, int) = i % 3 ? partition_pivot_last : partition_pivot_first;
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quick_sort(array, 0, size - 1, fptr);
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sum += array[i % size];
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}
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printf("sum=%d\n", sum);
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return 0;
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}
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