mirror of
https://github.com/ROCm/composable_kernel.git
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186 lines
6.0 KiB
C++
186 lines
6.0 KiB
C++
#include "ck/host/device_gemm_multiple_d/problem.hpp"
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#include "ck/host/device_gemm_multiple_d/operation.hpp"
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#include "ck/host/headers.hpp"
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#include "ck/host/stringutils.hpp"
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#include "ck/host/utils.hpp"
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#include <algorithm>
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#include <cmath>
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#include <iterator>
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#include <random>
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#include <test.hpp>
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#include <rtc/compile_kernel.hpp>
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#include <rtc/hip.hpp>
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using half = _Float16;
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// using half = __fp16;
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std::vector<rtc::src_file> get_headers_for_test()
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{
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std::vector<rtc::src_file> result;
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auto hs = ck::host::GetHeaders();
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std::transform(
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hs.begin(), hs.end(), std::back_inserter(result), [&](const auto& p) -> rtc::src_file {
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return {p.first, p.second};
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});
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return result;
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}
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template <class T>
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rtc::buffer<T> generate_buffer(std::size_t n, std::size_t seed = 0)
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{
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rtc::buffer<T> result(n);
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std::mt19937 gen(seed);
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std::uniform_real_distribution<double> dis(-1.0);
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std::generate(result.begin(), result.end(), [&] { return dis(gen); });
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return result;
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}
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template <class T, class U>
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bool allclose(const T& a, const U& b, double atol = 0.01, double rtol = 0.01)
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{
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return std::equal(a.begin(), a.end(), b.begin(), b.end(), [&](double x, double y) {
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return fabs(x - y) < atol + rtol * fabs(y);
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});
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}
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std::string classify(double x)
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{
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switch(std::fpclassify(x))
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{
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case FP_INFINITE: return "inf";
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case FP_NAN: return "nan";
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case FP_NORMAL: return "normal";
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case FP_SUBNORMAL: return "subnormal";
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case FP_ZERO: return "zero";
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default: return "unknown";
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}
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}
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template <class Buffer>
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void print_classification(const Buffer& x)
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{
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std::unordered_set<std::string> result;
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for(const auto& i : x)
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result.insert(classify(i));
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for(const auto& c : result)
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std::cout << c << ", ";
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std::cout << std::endl;
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}
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template <class Buffer>
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void print_statistics(const Buffer& x)
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{
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std::cout << "Min value: " << *std::min_element(x.begin(), x.end()) << ", ";
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std::cout << "Max value: " << *std::max_element(x.begin(), x.end()) << ", ";
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double num_elements = x.size();
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auto mean =
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std::accumulate(x.begin(), x.end(), double{0.0}, std::plus<double>{}) / num_elements;
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auto stddev = std::sqrt(
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std::accumulate(x.begin(),
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x.end(),
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double{0.0},
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[&](double r, double v) { return r + std::pow((v - mean), 2.0); }) /
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num_elements);
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std::cout << "Mean: " << mean << ", ";
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std::cout << "StdDev: " << stddev << "\n";
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}
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template <class Buffer>
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void print_preview(const Buffer& x)
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{
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if(x.size() <= 10)
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{
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std::for_each(x.begin(), x.end(), [&](double i) { std::cout << i << ", "; });
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}
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else
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{
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std::for_each(x.begin(), x.begin() + 5, [&](double i) { std::cout << i << ", "; });
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std::cout << "..., ";
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std::for_each(x.end() - 5, x.end(), [&](double i) { std::cout << i << ", "; });
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}
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std::cout << std::endl;
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}
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template <class T>
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struct check_all
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{
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rtc::buffer<T> data{};
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bool operator()(const rtc::buffer<T>& x)
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{
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if(data.empty())
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{
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data = x;
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return true;
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}
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if(std::any_of(x.begin(), x.end(), [](double y) { return std::isnan(y); }))
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return false;
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return allclose(data, x);
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}
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};
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template <class Solution>
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auto report(const Solution& solution, bool pass)
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{
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return test::make_predicate(solution.ToTemplateString(), [=] { return pass; });
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}
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const std::string gemm_compile_check = R"__ck__(
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#include <${include}>
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extern "C" __global__ void f(const ck::half_t* a, const ck::half_t* b, ck::half_t* c) {
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using G = ${template};
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constexpr auto desc = ${template}::make_descriptor(ck::make_naive_tensor_descriptor_packed(ck::make_tuple(${m}, ${k})),
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ck::make_naive_tensor_descriptor(ck::make_tuple(${n}, ${k}), ck::make_tuple(1, ${n})),
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ck::make_tuple(),
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ck::make_naive_tensor_descriptor_packed(ck::make_tuple(${m}, ${n})));
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static_assert(desc.IsValid(), "Invalid ck gemm.");
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if constexpr(desc.IsValid())
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{
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${template}::Run(desc,
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a,
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b,
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ck::make_tuple(),
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c);
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}
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}
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)__ck__";
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TEST_CASE(test_problem_kernel)
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{
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ck::host::device_gemm_multiple_d::Problem prob;
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prob.M = 1024;
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prob.N = 1024;
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prob.K = 1024;
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check_all<half> check;
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auto a = to_gpu(generate_buffer<half>(1024 * 1024, 0));
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auto b = to_gpu(generate_buffer<half>(1024 * 1024, 1));
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auto c = to_gpu(generate_buffer<half>(1024 * 1024, 2));
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for(auto solution : prob.GetSolutions("gfx90a"))
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{
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auto src = ck::host::InterpolateString(gemm_compile_check,
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{{"include", prob.GetIncludeHeader()},
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{"template", solution.ToTemplateString()},
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{"m", std::to_string(prob.M)},
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{"n", std::to_string(prob.N)},
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{"k", std::to_string(prob.K)}});
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auto srcs = get_headers_for_test();
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srcs.push_back({"main.cpp", src});
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rtc::compile_options options;
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options.kernel_name = "f";
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auto k = rtc::compile_kernel(srcs, options);
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auto block_size = solution.GetTemplateParameter<std::size_t>("BlockSize");
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auto m_per_block = solution.GetTemplateParameter<std::size_t>("MPerBlock");
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auto n_per_block = solution.GetTemplateParameter<std::size_t>("NPerBlock");
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auto grid_size = ck::host::integer_divide_ceil(prob.M, m_per_block) *
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ck::host::integer_divide_ceil(prob.N, n_per_block);
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k.launch(nullptr, grid_size * block_size, block_size)(a.data(), b.data(), c.data());
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CHECK(report(solution, check(rtc::from_gpu(c))));
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}
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}
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int main(int argc, const char* argv[]) { test::run(argc, argv); }
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