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aa24601f98
There are HIP applications e.g. Tensorflow 1.3 using amdgpu kernel attributes, however currently they are only allowed on OpenCL kernel functions. This patch will allow amdgpu kernel attributes to be applied to CUDA/HIP __global__ functions. Differential Revision: https://reviews.llvm.org/D47958 llvm-svn: 334561
81 lines
3.4 KiB
Plaintext
81 lines
3.4 KiB
Plaintext
// RUN: %clang_cc1 -fsyntax-only -verify %s
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#include "Inputs/cuda.h"
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__attribute__((amdgpu_flat_work_group_size(32, 64)))
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__global__ void flat_work_group_size_32_64() {}
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__attribute__((amdgpu_waves_per_eu(2)))
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__global__ void waves_per_eu_2() {}
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__attribute__((amdgpu_waves_per_eu(2, 4)))
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__global__ void waves_per_eu_2_4() {}
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__attribute__((amdgpu_num_sgpr(32)))
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__global__ void num_sgpr_32() {}
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__attribute__((amdgpu_num_vgpr(64)))
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__global__ void num_vgpr_64() {}
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__attribute__((amdgpu_flat_work_group_size(32, 64), amdgpu_waves_per_eu(2)))
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__global__ void flat_work_group_size_32_64_waves_per_eu_2() {}
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__attribute__((amdgpu_flat_work_group_size(32, 64), amdgpu_waves_per_eu(2, 4)))
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__global__ void flat_work_group_size_32_64_waves_per_eu_2_4() {}
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__attribute__((amdgpu_flat_work_group_size(32, 64), amdgpu_num_sgpr(32)))
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__global__ void flat_work_group_size_32_64_num_sgpr_32() {}
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__attribute__((amdgpu_flat_work_group_size(32, 64), amdgpu_num_vgpr(64)))
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__global__ void flat_work_group_size_32_64_num_vgpr_64() {}
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__attribute__((amdgpu_waves_per_eu(2), amdgpu_num_sgpr(32)))
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__global__ void waves_per_eu_2_num_sgpr_32() {}
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__attribute__((amdgpu_waves_per_eu(2), amdgpu_num_vgpr(64)))
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__global__ void waves_per_eu_2_num_vgpr_64() {}
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__attribute__((amdgpu_waves_per_eu(2, 4), amdgpu_num_sgpr(32)))
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__global__ void waves_per_eu_2_4_num_sgpr_32() {}
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__attribute__((amdgpu_waves_per_eu(2, 4), amdgpu_num_vgpr(64)))
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__global__ void waves_per_eu_2_4_num_vgpr_64() {}
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__attribute__((amdgpu_num_sgpr(32), amdgpu_num_vgpr(64)))
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__global__ void num_sgpr_32_num_vgpr_64() {}
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__attribute__((amdgpu_flat_work_group_size(32, 64), amdgpu_waves_per_eu(2), amdgpu_num_sgpr(32)))
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__global__ void flat_work_group_size_32_64_waves_per_eu_2_num_sgpr_32() {}
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__attribute__((amdgpu_flat_work_group_size(32, 64), amdgpu_waves_per_eu(2), amdgpu_num_vgpr(64)))
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__global__ void flat_work_group_size_32_64_waves_per_eu_2_num_vgpr_64() {}
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__attribute__((amdgpu_flat_work_group_size(32, 64), amdgpu_waves_per_eu(2, 4), amdgpu_num_sgpr(32)))
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__global__ void flat_work_group_size_32_64_waves_per_eu_2_4_num_sgpr_32() {}
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__attribute__((amdgpu_flat_work_group_size(32, 64), amdgpu_waves_per_eu(2, 4), amdgpu_num_vgpr(64)))
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__global__ void flat_work_group_size_32_64_waves_per_eu_2_4_num_vgpr_64() {}
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__attribute__((amdgpu_flat_work_group_size(32, 64), amdgpu_waves_per_eu(2), amdgpu_num_sgpr(32), amdgpu_num_vgpr(64)))
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__global__ void flat_work_group_size_32_64_waves_per_eu_2_num_sgpr_32_num_vgpr_64() {}
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__attribute__((amdgpu_flat_work_group_size(32, 64), amdgpu_waves_per_eu(2, 4), amdgpu_num_sgpr(32), amdgpu_num_vgpr(64)))
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__global__ void flat_work_group_size_32_64_waves_per_eu_2_4_num_sgpr_32_num_vgpr_64() {}
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// expected-error@+2{{attribute 'reqd_work_group_size' can only be applied to an OpenCL kernel function}}
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__attribute__((reqd_work_group_size(32, 64, 64)))
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__global__ void reqd_work_group_size_32_64_64() {}
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// expected-error@+2{{attribute 'work_group_size_hint' can only be applied to an OpenCL kernel function}}
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__attribute__((work_group_size_hint(2, 2, 2)))
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__global__ void work_group_size_hint_2_2_2() {}
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// expected-error@+2{{attribute 'vec_type_hint' can only be applied to an OpenCL kernel function}}
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__attribute__((vec_type_hint(int)))
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__global__ void vec_type_hint_int() {}
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// expected-error@+2{{attribute 'intel_reqd_sub_group_size' can only be applied to an OpenCL kernel function}}
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__attribute__((intel_reqd_sub_group_size(64)))
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__global__ void intel_reqd_sub_group_size_64() {}
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