47166968db
Recently OpenMP has transitioned to using the "new" driver which primarily merges the device and host linking phases into a single wrapper that handles both at the same time. This replaced a few tools that were only used for OpenMP offloading, such as the `clang-offload-wrapper` and `clang-nvlink-wrapper`. The new driver carries some marked benefits compared to the old driver that is now being deprecated. Things like device-side LTO, static library support, and more compatible tooling. As such, we should be able to completely deprecate the old driver, at least for OpenMP. The old driver support will still exist for CUDA and HIP, although both of these can currently be compiled on Linux with `--offload-new-driver` to use the new method. Note that this does not deprecate the `clang-offload-bundler`, although it is unused by OpenMP now, it is still used by the HIP toolchain both as their device binary format and object format. When I proposed deprecating this code I heard some vendors voice concernes about needing to update their code in their fork. They should be able to just revert this commit if it lands. Reviewed By: jdoerfert, MaskRay, ye-luo Differential Revision: https://reviews.llvm.org/D130020
58 lines
2.0 KiB
C
58 lines
2.0 KiB
C
// Use the generic state machine. On some architectures, other threads in the
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// main thread's warp must avoid barrier instructions.
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//
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// RUN: %libomptarget-compile-run-and-check-generic
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// SPMDize. There is no main thread, so there's no issue.
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//
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// RUN: %libomptarget-compile-generic -O1 -Rpass=openmp-opt > %t.spmd 2>&1
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// RUN: %fcheck-nvptx64-nvidia-cuda -check-prefix=SPMD -input-file=%t.spmd
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// RUN: %fcheck-amdgcn-amd-amdhsa -check-prefix=SPMD -input-file=%t.spmd
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// RUN: %libomptarget-run-generic 2>&1 | %fcheck-generic
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//
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// SPMD: Transformed generic-mode kernel to SPMD-mode.
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// Use the custom state machine, which must avoid the same barrier problem as
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// the generic state machine.
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//
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// RUN: %libomptarget-compile-generic -O1 -Rpass=openmp-opt \
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// RUN: -mllvm -openmp-opt-disable-spmdization > %t.custom 2>&1
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// RUN: %fcheck-nvptx64-nvidia-cuda -check-prefix=CUSTOM -input-file=%t.custom
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// RUN: %fcheck-amdgcn-amd-amdhsa -check-prefix=CUSTOM -input-file=%t.custom
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// RUN: %libomptarget-run-generic 2>&1 | %fcheck-generic
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//
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// Repeat with reduction clause, which has managed to break the custom state
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// machine in the past.
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//
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// RUN: %libomptarget-compile-generic -O1 -Rpass=openmp-opt -DADD_REDUCTION \
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// RUN: -mllvm -openmp-opt-disable-spmdization > %t.custom 2>&1
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// RUN: %fcheck-nvptx64-nvidia-cuda -check-prefix=CUSTOM -input-file=%t.custom
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// RUN: %fcheck-amdgcn-amd-amdhsa -check-prefix=CUSTOM -input-file=%t.custom
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// RUN: %libomptarget-run-generic 2>&1 | %fcheck-generic
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//
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// CUSTOM: Rewriting generic-mode kernel with a customized state machine.
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// Hangs
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// UNSUPPORTED: amdgcn-amd-amdhsa
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// UNSUPPORTED: amdgcn-amd-amdhsa-LTO
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#if ADD_REDUCTION
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# define REDUCTION(...) reduction(__VA_ARGS__)
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#else
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# define REDUCTION(...)
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#endif
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#include <stdio.h>
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int main() {
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int x = 0, y = 1;
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#pragma omp target teams num_teams(1) map(tofrom:x, y) REDUCTION(+:x)
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{
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x += 5;
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#pragma omp parallel
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y = 6;
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}
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// CHECK: 5, 6
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printf("%d, %d\n", x, y);
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return 0;
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}
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