-
Notifications
You must be signed in to change notification settings - Fork 408
[MicroBenchmarks] Add benchmark for control-flow-vectorization. #345
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
base: main
Are you sure you want to change the base?
Changes from 2 commits
File filter
Filter by extension
Conversations
Jump to
Diff view
Diff view
There are no files selected for viewing
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,177 @@ | ||
| #include <iostream> | ||
| #include <memory> | ||
| #include <random> | ||
|
|
||
| #include "benchmark/benchmark.h" | ||
|
|
||
| #define ITERATIONS 100000 | ||
|
|
||
| template <typename T> using CFVFunc = void (*)(T *, unsigned); | ||
|
|
||
| // Define conditional increment loop with given stride. | ||
| #define DEF_COND_INC_LOOP(name, stride) \ | ||
| template <typename T> \ | ||
| __attribute__((noinline)) static void run_##name##_autovec(T *A, \ | ||
|
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. What is the meaning of this benchmark ? Just track current state of cf vectorization of novec and autovec or help to identify better LMUL to vectorize the loop ? If latter, it does make sense to add similar functions with forced vectorization for default LMUL and specified LMULs
Author
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. IIUC, this benchmark serves as a test suite for other targets to measure the performance impact of enabling control-flow vectorization. I've updated the PR description to make it more clear. |
||
| unsigned N) { \ | ||
| for (unsigned i = 0; i < N; i++) { \ | ||
| if (i % stride == 0) { \ | ||
|
Contributor
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Stride may be a bit mis-leading here, maybe to be confused with the stride by which pointers increment?
Author
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Yes. Update the naming to the |
||
| A[i] = A[i] + 1; \ | ||
| } \ | ||
| } \ | ||
| } \ | ||
| template <typename T> \ | ||
| __attribute__((noinline)) static void run_##name##_novec(T *A, unsigned N) { \ | ||
| _Pragma("clang loop vectorize(disable) interleave(disable)") \ | ||
| for (unsigned i = 0; i < N; i++) { \ | ||
| if (i % stride == 0) { \ | ||
| A[i] = A[i] + 1; \ | ||
| } \ | ||
| } \ | ||
| } | ||
|
|
||
| // Define conditional increment by value loop. | ||
| #define DEF_COND_INC_VALUE_LOOP(name, marker) \ | ||
| template <typename T> \ | ||
| __attribute__((noinline)) static void run_##name##_autovec(T *A, \ | ||
| unsigned N) { \ | ||
| for (unsigned i = 0; i < N; i++) { \ | ||
| if (A[i] == marker) { \ | ||
| A[i] = A[i] + 1; \ | ||
| } \ | ||
| } \ | ||
| } \ | ||
| template <typename T> \ | ||
| __attribute__((noinline)) static void run_##name##_novec(T *A, unsigned N) { \ | ||
| _Pragma("clang loop vectorize(disable) interleave(disable)") \ | ||
| for (unsigned i = 0; i < N; i++) { \ | ||
| if (A[i] == marker) { \ | ||
| A[i] = A[i] + 1; \ | ||
| } \ | ||
| } \ | ||
| } | ||
|
|
||
| // Define unconditional increment loop. | ||
| template <typename T> | ||
| __attribute__((noinline)) static void run_uncond_inc_autovec(T *A, unsigned N) { | ||
| for (unsigned i = 0; i < N; i++) { | ||
| A[i] = A[i] + 1; | ||
| } | ||
| } | ||
|
|
||
| template <typename T> | ||
| __attribute__((noinline)) static void run_uncond_inc_novec(T *A, unsigned N) { | ||
| _Pragma("clang loop vectorize(disable) interleave(disable)") | ||
| for (unsigned i = 0; i < N; i++) { | ||
| A[i] = A[i] + 1; | ||
| } | ||
| } | ||
|
|
||
| // Define loops with different strides. | ||
| // Stride 16 usually big enough to accross single vector which can test if | ||
| // control-flow-vectorization is profitable on these loops. | ||
| DEF_COND_INC_LOOP(cond_inc_stride_16, 16) | ||
|
Contributor
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. This variant roughly executes the conditional code every 16 iterations, right? Would be good to also add variations where conditional code executes more frequently, including extreme case (every iteration, every other iteration)?
Author
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Yes. Add the cases that branch will taken for every (1, 2, 4, 8) iters. Thanks! |
||
| DEF_COND_INC_LOOP(cond_inc_stride_32, 32) | ||
| DEF_COND_INC_LOOP(cond_inc_stride_64, 64) | ||
| DEF_COND_INC_LOOP(cond_inc_stride_128, 128) | ||
|
|
||
| // Conditional increment by value. | ||
| DEF_COND_INC_VALUE_LOOP(cond_inc_by_value, 40) | ||
|
|
||
| // Initialize array with random numbers. | ||
| template <typename T> static void init_data(T *A) { | ||
| std::uniform_int_distribution<T> dist(0, 100); | ||
| std::mt19937 rng(12345); | ||
| for (unsigned i = 0; i < ITERATIONS; i++) { | ||
| A[i] = dist(rng); | ||
| } | ||
| } | ||
|
|
||
| // Benchmark vectorized version. | ||
| template <typename T> | ||
| static void __attribute__((always_inline)) | ||
| benchmark_cfv_autovec(benchmark::State &state, CFVFunc<T> VecFn, | ||
| CFVFunc<T> NoVecFn) { | ||
| std::unique_ptr<T[]> A(new T[ITERATIONS]); | ||
| std::unique_ptr<T[]> A_vec(new T[ITERATIONS]); | ||
| std::unique_ptr<T[]> A_novec(new T[ITERATIONS]); | ||
| init_data(&A[0]); | ||
|
|
||
| #ifdef BENCH_AND_VERIFY | ||
| // Verify the vectorized and scalar versions produce the same results. | ||
| { | ||
| std::copy(&A[0], &A[0] + ITERATIONS, &A_vec[0]); | ||
| std::copy(&A[0], &A[0] + ITERATIONS, &A_novec[0]); | ||
| VecFn(&A_vec[0], ITERATIONS); | ||
| NoVecFn(&A_novec[0], ITERATIONS); | ||
| for (unsigned i = 0; i < ITERATIONS; i++) { | ||
| if (A_vec[i] != A_novec[i]) { | ||
| std::cerr << "ERROR: vectorization result different at index " << i | ||
| << "; " << A_vec[i] << " != " << A_novec[i] << "\n"; | ||
| exit(1); | ||
| } | ||
| } | ||
| } | ||
| #endif | ||
|
|
||
| for (auto _ : state) { | ||
| std::copy(&A[0], &A[0] + ITERATIONS, &A_vec[0]); | ||
| VecFn(&A_vec[0], ITERATIONS); | ||
| benchmark::DoNotOptimize(A_vec); | ||
| benchmark::ClobberMemory(); | ||
| } | ||
| } | ||
|
|
||
| // Benchmark version with vectorization disabled. | ||
| template <typename T> | ||
| static void __attribute__((always_inline)) | ||
| benchmark_cfv_novec(benchmark::State &state, CFVFunc<T> NoVecFn) { | ||
| std::unique_ptr<T[]> A(new T[ITERATIONS]); | ||
| std::unique_ptr<T[]> A_work(new T[ITERATIONS]); | ||
| init_data(&A[0]); | ||
|
|
||
| for (auto _ : state) { | ||
| std::copy(&A[0], &A[0] + ITERATIONS, &A_work[0]); | ||
| NoVecFn(&A_work[0], ITERATIONS); | ||
| benchmark::DoNotOptimize(A_work); | ||
| benchmark::ClobberMemory(); | ||
| } | ||
| } | ||
|
|
||
| #define BENCHMARK_CFV_CASE(name, ty) \ | ||
| void BENCHMARK_##name##_autovec_##ty##_(benchmark::State &state) { \ | ||
| benchmark_cfv_autovec<ty>(state, run_##name##_autovec, run_##name##_novec);\ | ||
| } \ | ||
| BENCHMARK(BENCHMARK_##name##_autovec_##ty##_)->Unit(benchmark::kNanosecond); \ | ||
| \ | ||
| void BENCHMARK_##name##_novec_##ty##_(benchmark::State &state) { \ | ||
| benchmark_cfv_novec<ty>(state, run_##name##_novec); \ | ||
| } \ | ||
| BENCHMARK(BENCHMARK_##name##_novec_##ty##_)->Unit(benchmark::kNanosecond); | ||
|
|
||
| // Unconditional increment benchmark. | ||
| #define BENCHMARK_UNCOND_CASE(ty) \ | ||
| void BENCHMARK_uncond_inc_autovec_##ty##_(benchmark::State &state) { \ | ||
| benchmark_cfv_autovec<ty>(state, run_uncond_inc_autovec, \ | ||
| run_uncond_inc_novec); \ | ||
| } \ | ||
| BENCHMARK(BENCHMARK_uncond_inc_autovec_##ty##_) \ | ||
| ->Unit(benchmark::kNanosecond); \ | ||
| \ | ||
| void BENCHMARK_uncond_inc_novec_##ty##_(benchmark::State &state) { \ | ||
| benchmark_cfv_novec<ty>(state, run_uncond_inc_novec); \ | ||
| } \ | ||
| BENCHMARK(BENCHMARK_uncond_inc_novec_##ty##_)->Unit(benchmark::kNanosecond); | ||
|
|
||
| // Add benchmarks for all variants. | ||
| #define ADD_CFV_BENCHMARKS(ty) \ | ||
| BENCHMARK_UNCOND_CASE(ty) \ | ||
| BENCHMARK_CFV_CASE(cond_inc_stride_16, ty) \ | ||
| BENCHMARK_CFV_CASE(cond_inc_stride_32, ty) \ | ||
| BENCHMARK_CFV_CASE(cond_inc_stride_64, ty) \ | ||
| BENCHMARK_CFV_CASE(cond_inc_stride_128, ty) \ | ||
| BENCHMARK_CFV_CASE(cond_inc_by_value, ty) | ||
|
|
||
| ADD_CFV_BENCHMARKS(int64_t) | ||
| ADD_CFV_BENCHMARKS(int32_t) | ||
| ADD_CFV_BENCHMARKS(int16_t) | ||
|
|
||
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
might be good to use a more descriptive name or add a comment
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Update to
ControlFlowLoopFunc. Thanks!