[OpenMP] Remove 'minncta' attributes from NVPTX kernels (#88398)
Summary: Currently we treat this attribute as a minimum number for the amount of blocks scheduled on the kernel. However, the doucmentation states that this applies to CTA's mapped onto a *single* SM. Currently we just set it to the total number of blocks, which will almost always result in a warning that the value is out of range and will be ignored. We don't have a good way to automatically know how many CTAs can be put on a single SM nor if we should do this, so we should probably leave this up to users manually adding it. https://docs.nvidia.com/cuda/parallel-thread-execution/index.html#performance-tuning-directives-minnctapersm
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@ -36,6 +36,5 @@ void func() {
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// NVIDIA: "omp_target_thread_limit"="45"
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// NVIDIA: "omp_target_thread_limit"="17"
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// NVIDIA: !{ptr @__omp_offloading[[HASH1:.*]]_l16, !"maxntidx", i32 20}
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// NVIDIA: !{ptr @__omp_offloading[[HASH2:.*]]_l18, !"minctasm", i32 90}
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// NVIDIA: !{ptr @__omp_offloading[[HASH2]]_l18, !"maxntidx", i32 45}
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// NVIDIA: !{ptr @__omp_offloading[[HASH2:.*]]_l18, !"maxntidx", i32 45}
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// NVIDIA: !{ptr @__omp_offloading[[HASH3:.*]]_l20, !"maxntidx", i32 17}
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@ -4786,11 +4786,9 @@ OpenMPIRBuilder::readTeamBoundsForKernel(const Triple &, Function &Kernel) {
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void OpenMPIRBuilder::writeTeamsForKernel(const Triple &T, Function &Kernel,
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int32_t LB, int32_t UB) {
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if (T.isNVPTX()) {
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if (T.isNVPTX())
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if (UB > 0)
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updateNVPTXMetadata(Kernel, "maxclusterrank", UB, true);
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updateNVPTXMetadata(Kernel, "minctasm", LB, false);
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}
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if (T.isAMDGPU())
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Kernel.addFnAttr("amdgpu-max-num-workgroups", llvm::utostr(LB) + ",1,1");
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