Previously an opt-in flag `-fopenmp-new-driver` was used to enable the new offloading driver. After passing tests for a few months it should be sufficiently mature to flip the switch and make it the default. The new offloading driver is now enabled if there is OpenMP and OpenMP offloading present and the new `-fno-openmp-new-driver` is not present. The new offloading driver has three main benefits over the old method: - Static library support - Device-side LTO - Unified clang driver stages Depends on D122683 Differential Revision: https://reviews.llvm.org/D122831
149 lines
4.4 KiB
C++
149 lines
4.4 KiB
C++
// RUN: %libomptarget-compilexx-run-and-check-generic
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// Currently hangs on amdgpu
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// UNSUPPORTED: amdgcn-amd-amdhsa
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// UNSUPPORTED: amdgcn-amd-amdhsa-oldDriver
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// UNSUPPORTED: x86_64-pc-linux-gnu
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// UNSUPPORTED: x86_64-pc-linux-gnu-oldDriver
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#include <cassert>
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#include <cmath>
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#include <iostream>
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#include <limits>
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#include <memory>
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#include <vector>
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class BlockMatrix {
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private:
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const int rowsPerBlock;
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const int colsPerBlock;
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const long nRows;
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const long nCols;
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const int nBlocksPerRow;
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const int nBlocksPerCol;
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std::vector<std::vector<std::unique_ptr<float[]>>> Blocks;
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public:
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BlockMatrix(const int _rowsPerBlock, const int _colsPerBlock,
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const long _nRows, const long _nCols)
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: rowsPerBlock(_rowsPerBlock), colsPerBlock(_colsPerBlock), nRows(_nRows),
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nCols(_nCols), nBlocksPerRow(_nRows / _rowsPerBlock),
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nBlocksPerCol(_nCols / _colsPerBlock), Blocks(nBlocksPerCol) {
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for (int i = 0; i < nBlocksPerCol; i++) {
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for (int j = 0; j < nBlocksPerRow; j++) {
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Blocks[i].emplace_back(new float[_rowsPerBlock * _colsPerBlock]);
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}
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}
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};
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// Initialize the BlockMatrix from 2D arrays
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void Initialize(const std::vector<float> &matrix) {
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for (int i = 0; i < nBlocksPerCol; i++)
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for (int j = 0; j < nBlocksPerRow; j++) {
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float *CurrBlock = GetBlock(i, j);
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for (int ii = 0; ii < colsPerBlock; ++ii)
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for (int jj = 0; jj < rowsPerBlock; ++jj) {
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int curri = i * colsPerBlock + ii;
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int currj = j * rowsPerBlock + jj;
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CurrBlock[ii + jj * colsPerBlock] = matrix[curri + currj * nCols];
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}
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}
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}
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void Compare(const std::vector<float> &matrix) const {
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for (int i = 0; i < nBlocksPerCol; i++)
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for (int j = 0; j < nBlocksPerRow; j++) {
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float *CurrBlock = GetBlock(i, j);
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for (int ii = 0; ii < colsPerBlock; ++ii)
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for (int jj = 0; jj < rowsPerBlock; ++jj) {
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int curri = i * colsPerBlock + ii;
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int currj = j * rowsPerBlock + jj;
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float m_value = matrix[curri + currj * nCols];
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float bm_value = CurrBlock[ii + jj * colsPerBlock];
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assert(std::fabs(bm_value - m_value) <
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std::numeric_limits<float>::epsilon());
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}
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}
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}
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float *GetBlock(int i, int j) const {
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assert(i < nBlocksPerCol && j < nBlocksPerRow && "Accessing outside block");
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return Blocks[i][j].get();
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}
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};
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constexpr const int BS = 16;
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constexpr const int N = 256;
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int BlockMatMul_TargetNowait(BlockMatrix &A, BlockMatrix &B, BlockMatrix &C) {
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#pragma omp parallel
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#pragma omp master
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for (int i = 0; i < N / BS; ++i)
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for (int j = 0; j < N / BS; ++j) {
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float *BlockC = C.GetBlock(i, j);
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for (int k = 0; k < N / BS; ++k) {
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float *BlockA = A.GetBlock(i, k);
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float *BlockB = B.GetBlock(k, j);
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// clang-format off
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#pragma omp target depend(in: BlockA[0], BlockB[0]) depend(inout: BlockC[0]) \
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map(to: BlockA[:BS * BS], BlockB[:BS * BS]) \
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map(tofrom: BlockC[:BS * BS]) nowait
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// clang-format on
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#pragma omp parallel for
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for (int ii = 0; ii < BS; ii++)
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for (int jj = 0; jj < BS; jj++) {
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for (int kk = 0; kk < BS; ++kk)
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BlockC[ii + jj * BS] +=
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BlockA[ii + kk * BS] * BlockB[kk + jj * BS];
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}
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}
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}
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return 0;
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}
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void Matmul(const std::vector<float> &a, const std::vector<float> &b,
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std::vector<float> &c) {
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for (int i = 0; i < N; ++i) {
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for (int j = 0; j < N; ++j) {
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float sum = 0.0;
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for (int k = 0; k < N; ++k) {
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sum = sum + a[i * N + k] * b[k * N + j];
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}
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c[i * N + j] = sum;
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}
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}
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}
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int main(int argc, char *argv[]) {
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std::vector<float> a(N * N);
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std::vector<float> b(N * N);
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std::vector<float> c(N * N, 0.0);
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for (int i = 0; i < N; ++i) {
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for (int j = 0; j < N; ++j) {
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a[i * N + j] = b[i * N + j] = i + j % 100;
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}
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}
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auto BlockedA = BlockMatrix(BS, BS, N, N);
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auto BlockedB = BlockMatrix(BS, BS, N, N);
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auto BlockedC = BlockMatrix(BS, BS, N, N);
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BlockedA.Initialize(a);
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BlockedB.Initialize(b);
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BlockedC.Initialize(c);
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BlockedA.Compare(a);
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BlockedB.Compare(b);
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BlockedC.Compare(c);
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Matmul(a, b, c);
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BlockMatMul_TargetNowait(BlockedA, BlockedB, BlockedC);
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BlockedC.Compare(c);
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std::cout << "PASS\n";
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return 0;
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}
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// CHECK: PASS
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