Joseph Huber d5d836635c [Libomptarget] Add test config for compiling in LTO-mode
We are planning on making LTO the default compilation mode for
offloading. In order to make sure it works we should run these tests on
the test suite. AMDGPU already uses the LTO compilation path for its
linking, but in LTO mode it also links the static library late.

Performing LTO requires the static library to be built, if we make the
change this will be a hard requirement and the old bitcode library will
go away. This means users will need to use either a two-step build or a
runtimes build for libomptarget.

Reviewed By: JonChesterfield

Differential Revision: https://reviews.llvm.org/D127512
2022-06-14 10:16:03 -04:00

151 lines
4.4 KiB
C++

// RUN: %libomptarget-compilexx-run-and-check-generic
// Currently hangs on amdgpu
// UNSUPPORTED: amdgcn-amd-amdhsa
// UNSUPPORTED: amdgcn-amd-amdhsa-oldDriver
// UNSUPPORTED: amdgcn-amd-amdhsa-LTO
// UNSUPPORTED: x86_64-pc-linux-gnu
// UNSUPPORTED: x86_64-pc-linux-gnu-oldDriver
// UNSUPPORTED: x86_64-pc-linux-gnu-LTO
#include <cassert>
#include <cmath>
#include <iostream>
#include <limits>
#include <memory>
#include <vector>
class BlockMatrix {
private:
const int rowsPerBlock;
const int colsPerBlock;
const long nRows;
const long nCols;
const int nBlocksPerRow;
const int nBlocksPerCol;
std::vector<std::vector<std::unique_ptr<float[]>>> Blocks;
public:
BlockMatrix(const int _rowsPerBlock, const int _colsPerBlock,
const long _nRows, const long _nCols)
: rowsPerBlock(_rowsPerBlock), colsPerBlock(_colsPerBlock), nRows(_nRows),
nCols(_nCols), nBlocksPerRow(_nRows / _rowsPerBlock),
nBlocksPerCol(_nCols / _colsPerBlock), Blocks(nBlocksPerCol) {
for (int i = 0; i < nBlocksPerCol; i++) {
for (int j = 0; j < nBlocksPerRow; j++) {
Blocks[i].emplace_back(new float[_rowsPerBlock * _colsPerBlock]);
}
}
};
// Initialize the BlockMatrix from 2D arrays
void Initialize(const std::vector<float> &matrix) {
for (int i = 0; i < nBlocksPerCol; i++)
for (int j = 0; j < nBlocksPerRow; j++) {
float *CurrBlock = GetBlock(i, j);
for (int ii = 0; ii < colsPerBlock; ++ii)
for (int jj = 0; jj < rowsPerBlock; ++jj) {
int curri = i * colsPerBlock + ii;
int currj = j * rowsPerBlock + jj;
CurrBlock[ii + jj * colsPerBlock] = matrix[curri + currj * nCols];
}
}
}
void Compare(const std::vector<float> &matrix) const {
for (int i = 0; i < nBlocksPerCol; i++)
for (int j = 0; j < nBlocksPerRow; j++) {
float *CurrBlock = GetBlock(i, j);
for (int ii = 0; ii < colsPerBlock; ++ii)
for (int jj = 0; jj < rowsPerBlock; ++jj) {
int curri = i * colsPerBlock + ii;
int currj = j * rowsPerBlock + jj;
float m_value = matrix[curri + currj * nCols];
float bm_value = CurrBlock[ii + jj * colsPerBlock];
assert(std::fabs(bm_value - m_value) <
std::numeric_limits<float>::epsilon());
}
}
}
float *GetBlock(int i, int j) const {
assert(i < nBlocksPerCol && j < nBlocksPerRow && "Accessing outside block");
return Blocks[i][j].get();
}
};
constexpr const int BS = 16;
constexpr const int N = 256;
int BlockMatMul_TargetNowait(BlockMatrix &A, BlockMatrix &B, BlockMatrix &C) {
#pragma omp parallel
#pragma omp master
for (int i = 0; i < N / BS; ++i)
for (int j = 0; j < N / BS; ++j) {
float *BlockC = C.GetBlock(i, j);
for (int k = 0; k < N / BS; ++k) {
float *BlockA = A.GetBlock(i, k);
float *BlockB = B.GetBlock(k, j);
// clang-format off
#pragma omp target depend(in: BlockA[0], BlockB[0]) depend(inout: BlockC[0]) \
map(to: BlockA[:BS * BS], BlockB[:BS * BS]) \
map(tofrom: BlockC[:BS * BS]) nowait
// clang-format on
#pragma omp parallel for
for (int ii = 0; ii < BS; ii++)
for (int jj = 0; jj < BS; jj++) {
for (int kk = 0; kk < BS; ++kk)
BlockC[ii + jj * BS] +=
BlockA[ii + kk * BS] * BlockB[kk + jj * BS];
}
}
}
return 0;
}
void Matmul(const std::vector<float> &a, const std::vector<float> &b,
std::vector<float> &c) {
for (int i = 0; i < N; ++i) {
for (int j = 0; j < N; ++j) {
float sum = 0.0;
for (int k = 0; k < N; ++k) {
sum = sum + a[i * N + k] * b[k * N + j];
}
c[i * N + j] = sum;
}
}
}
int main(int argc, char *argv[]) {
std::vector<float> a(N * N);
std::vector<float> b(N * N);
std::vector<float> c(N * N, 0.0);
for (int i = 0; i < N; ++i) {
for (int j = 0; j < N; ++j) {
a[i * N + j] = b[i * N + j] = i + j % 100;
}
}
auto BlockedA = BlockMatrix(BS, BS, N, N);
auto BlockedB = BlockMatrix(BS, BS, N, N);
auto BlockedC = BlockMatrix(BS, BS, N, N);
BlockedA.Initialize(a);
BlockedB.Initialize(b);
BlockedC.Initialize(c);
BlockedA.Compare(a);
BlockedB.Compare(b);
BlockedC.Compare(c);
Matmul(a, b, c);
BlockMatMul_TargetNowait(BlockedA, BlockedB, BlockedC);
BlockedC.Compare(c);
std::cout << "PASS\n";
return 0;
}
// CHECK: PASS