7481b465ae
If the user did not provide any static clause to override the grid size, we assume the default grid size as upper bound and use it to improve code generation through vendor specific attributes. Fixes: https://github.com/llvm/llvm-project/issues/64816 Differential Revision: https://reviews.llvm.org/D158382
104 lines
3.2 KiB
C
104 lines
3.2 KiB
C
// clang-format off
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// RUN: %libomptarget-compile-generic
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// RUN: env LIBOMPTARGET_INFO=16 \
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// RUN: %libomptarget-run-generic 2>&1 | %fcheck-generic --check-prefix=DEFAULT
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// UNSUPPORTED: nvptx64-nvidia-cuda
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// UNSUPPORTED: nvptx64-nvidia-cuda-LTO
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// UNSUPPORTED: aarch64-unknown-linux-gnu
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// UNSUPPORTED: aarch64-unknown-linux-gnu-LTO
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// UNSUPPORTED: x86_64-pc-linux-gnu
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// UNSUPPORTED: x86_64-pc-linux-gnu-LTO
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__attribute__((optnone)) int optnone() { return 1; }
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int main() {
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int N = optnone() * 4098 * 32;
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// DEFAULT: [[NT:(128|256)]] (MaxFlatWorkGroupSize: [[NT]]
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#pragma omp target teams distribute parallel for simd
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for (int i = 0; i < N; ++i) {
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optnone();
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}
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// DEFAULT: [[NT:(128|256)]] (MaxFlatWorkGroupSize: [[NT]]
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#pragma omp target teams distribute parallel for simd
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for (int i = 0; i < N; ++i) {
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optnone();
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}
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// DEFAULT: [[NT:(128|256)]] (MaxFlatWorkGroupSize: [[NT]]
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#pragma omp target teams distribute parallel for simd
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for (int i = 0; i < N; ++i) {
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optnone();
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}
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// DEFAULT: [[NT:(128|256)]] (MaxFlatWorkGroupSize: [[NT]]
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#pragma omp target
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#pragma omp teams distribute parallel for
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for (int i = 0; i < N; ++i) {
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optnone();
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}
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// DEFAULT: 42 (MaxFlatWorkGroupSize: 1024
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#pragma omp target thread_limit(optnone() * 42)
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#pragma omp teams distribute parallel for
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for (int i = 0; i < N; ++i) {
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optnone();
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}
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// DEFAULT: 42 (MaxFlatWorkGroupSize: 42
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#pragma omp target thread_limit(optnone() * 42) ompx_attribute(__attribute__((amdgpu_flat_work_group_size(42, 42))))
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#pragma omp teams distribute parallel for
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for (int i = 0; i < N; ++i) {
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optnone();
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}
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// FIXME: Use the attribute value to imply a thread_limit
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// DEFAULT: {{(128|256)}} (MaxFlatWorkGroupSize: 42
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#pragma omp target ompx_attribute(__attribute__((amdgpu_flat_work_group_size(42, 42))))
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#pragma omp teams distribute parallel for
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for (int i = 0; i < N; ++i) {
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optnone();
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}
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// DEFAULT: MaxFlatWorkGroupSize: 1024
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#pragma omp target
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#pragma omp teams distribute parallel for num_threads(optnone() * 42)
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for (int i = 0; i < N; ++i) {
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optnone();
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}
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// DEFAULT: MaxFlatWorkGroupSize: 1024
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#pragma omp target teams distribute parallel for thread_limit(optnone() * 42)
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for (int i = 0; i < N; ++i) {
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optnone();
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}
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// DEFAULT: MaxFlatWorkGroupSize: 1024
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#pragma omp target teams distribute parallel for num_threads(optnone() * 42)
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for (int i = 0; i < N; ++i) {
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optnone();
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}
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// DEFAULT: 9 (MaxFlatWorkGroupSize: 9
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#pragma omp target
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#pragma omp teams distribute parallel for num_threads(9)
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for (int i = 0; i < N; ++i) {
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optnone();
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}
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// DEFAULT: 4 (MaxFlatWorkGroupSize: 4
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#pragma omp target thread_limit(4)
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#pragma omp teams distribute parallel for
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for (int i = 0; i < N; ++i) {
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optnone();
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}
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// DEFAULT: 4 (MaxFlatWorkGroupSize: 4
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#pragma omp target
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#pragma omp teams distribute parallel for thread_limit(4)
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for (int i = 0; i < N; ++i) {
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optnone();
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}
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// DEFAULT: 9 (MaxFlatWorkGroupSize: 9
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#pragma omp target teams distribute parallel for num_threads(9)
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for (int i = 0; i < N; ++i) {
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optnone();
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}
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// DEFAULT: 4 (MaxFlatWorkGroupSize: 4
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#pragma omp target teams distribute parallel for simd thread_limit(4)
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for (int i = 0; i < N; ++i) {
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optnone();
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}
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}
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