| //===-- nvptxintrin.h - NVPTX intrinsic functions -------------------------===// |
| // |
| // Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions. |
| // See https://llvm.org/LICENSE.txt for license information. |
| // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception |
| // |
| //===----------------------------------------------------------------------===// |
| |
| #ifndef __NVPTXINTRIN_H |
| #define __NVPTXINTRIN_H |
| |
| #ifndef __NVPTX__ |
| #error "This file is intended for NVPTX targets or offloading to NVPTX" |
| #endif |
| |
| #ifndef __GPUINTRIN_H |
| #error "Never use <nvptxintrin.h> directly; include <gpuintrin.h> instead" |
| #endif |
| |
| #ifndef __CUDA_ARCH__ |
| #define __CUDA_ARCH__ 0 |
| #endif |
| |
| _Pragma("omp begin declare target device_type(nohost)"); |
| _Pragma("omp begin declare variant match(device = {arch(nvptx64)})"); |
| |
| // Type aliases to the address spaces used by the NVPTX backend. |
| #define __gpu_private __attribute__((address_space(5))) |
| #define __gpu_constant __attribute__((address_space(4))) |
| #define __gpu_local __attribute__((address_space(3))) |
| #define __gpu_global __attribute__((address_space(1))) |
| #define __gpu_generic __attribute__((address_space(0))) |
| |
| // Attribute to declare a function as a kernel. |
| #define __gpu_kernel __attribute__((nvptx_kernel, visibility("protected"))) |
| |
| // Returns the number of CUDA blocks in the 'x' dimension. |
| _DEFAULT_FN_ATTRS static __inline__ uint32_t __gpu_num_blocks_x(void) { |
| return __nvvm_read_ptx_sreg_nctaid_x(); |
| } |
| |
| // Returns the number of CUDA blocks in the 'y' dimension. |
| _DEFAULT_FN_ATTRS static __inline__ uint32_t __gpu_num_blocks_y(void) { |
| return __nvvm_read_ptx_sreg_nctaid_y(); |
| } |
| |
| // Returns the number of CUDA blocks in the 'z' dimension. |
| _DEFAULT_FN_ATTRS static __inline__ uint32_t __gpu_num_blocks_z(void) { |
| return __nvvm_read_ptx_sreg_nctaid_z(); |
| } |
| |
| // Returns the 'x' dimension of the current CUDA block's id. |
| _DEFAULT_FN_ATTRS static __inline__ uint32_t __gpu_block_id_x(void) { |
| return __nvvm_read_ptx_sreg_ctaid_x(); |
| } |
| |
| // Returns the 'y' dimension of the current CUDA block's id. |
| _DEFAULT_FN_ATTRS static __inline__ uint32_t __gpu_block_id_y(void) { |
| return __nvvm_read_ptx_sreg_ctaid_y(); |
| } |
| |
| // Returns the 'z' dimension of the current CUDA block's id. |
| _DEFAULT_FN_ATTRS static __inline__ uint32_t __gpu_block_id_z(void) { |
| return __nvvm_read_ptx_sreg_ctaid_z(); |
| } |
| |
| // Returns the number of CUDA threads in the 'x' dimension. |
| _DEFAULT_FN_ATTRS static __inline__ uint32_t __gpu_num_threads_x(void) { |
| return __nvvm_read_ptx_sreg_ntid_x(); |
| } |
| |
| // Returns the number of CUDA threads in the 'y' dimension. |
| _DEFAULT_FN_ATTRS static __inline__ uint32_t __gpu_num_threads_y(void) { |
| return __nvvm_read_ptx_sreg_ntid_y(); |
| } |
| |
| // Returns the number of CUDA threads in the 'z' dimension. |
| _DEFAULT_FN_ATTRS static __inline__ uint32_t __gpu_num_threads_z(void) { |
| return __nvvm_read_ptx_sreg_ntid_z(); |
| } |
| |
| // Returns the 'x' dimension id of the thread in the current CUDA block. |
| _DEFAULT_FN_ATTRS static __inline__ uint32_t __gpu_thread_id_x(void) { |
| return __nvvm_read_ptx_sreg_tid_x(); |
| } |
| |
| // Returns the 'y' dimension id of the thread in the current CUDA block. |
| _DEFAULT_FN_ATTRS static __inline__ uint32_t __gpu_thread_id_y(void) { |
| return __nvvm_read_ptx_sreg_tid_y(); |
| } |
| |
| // Returns the 'z' dimension id of the thread in the current CUDA block. |
| _DEFAULT_FN_ATTRS static __inline__ uint32_t __gpu_thread_id_z(void) { |
| return __nvvm_read_ptx_sreg_tid_z(); |
| } |
| |
| // Returns the size of a CUDA warp, always 32 on NVIDIA hardware. |
| _DEFAULT_FN_ATTRS static __inline__ uint32_t __gpu_num_lanes(void) { |
| return __nvvm_read_ptx_sreg_warpsize(); |
| } |
| |
| // Returns the id of the thread inside of a CUDA warp executing together. |
| _DEFAULT_FN_ATTRS static __inline__ uint32_t __gpu_lane_id(void) { |
| return __nvvm_read_ptx_sreg_laneid(); |
| } |
| |
| // Returns the bit-mask of active threads in the current warp. |
| _DEFAULT_FN_ATTRS static __inline__ uint64_t __gpu_lane_mask(void) { |
| return __nvvm_activemask(); |
| } |
| |
| // Copies the value from the first active thread in the warp to the rest. |
| _DEFAULT_FN_ATTRS static __inline__ uint32_t |
| __gpu_read_first_lane_u32(uint64_t __lane_mask, uint32_t __x) { |
| uint32_t __mask = (uint32_t)__lane_mask; |
| uint32_t __id = __builtin_ffs(__mask) - 1; |
| return __nvvm_shfl_sync_idx_i32(__mask, __x, __id, __gpu_num_lanes() - 1); |
| } |
| |
| // Returns a bitmask of threads in the current lane for which \p x is true. |
| _DEFAULT_FN_ATTRS static __inline__ uint64_t __gpu_ballot(uint64_t __lane_mask, |
| bool __x) { |
| uint32_t __mask = (uint32_t)__lane_mask; |
| return __nvvm_vote_ballot_sync(__mask, __x); |
| } |
| |
| // Waits for all the threads in the block to converge and issues a fence. |
| _DEFAULT_FN_ATTRS static __inline__ void __gpu_sync_threads(void) { |
| __syncthreads(); |
| } |
| |
| // Waits for all threads in the warp to reconverge for independent scheduling. |
| _DEFAULT_FN_ATTRS static __inline__ void __gpu_sync_lane(uint64_t __lane_mask) { |
| __nvvm_bar_warp_sync((uint32_t)__lane_mask); |
| } |
| |
| // Shuffles the the lanes inside the warp according to the given index. |
| _DEFAULT_FN_ATTRS static __inline__ uint32_t |
| __gpu_shuffle_idx_u32(uint64_t __lane_mask, uint32_t __idx, uint32_t __x, |
| uint32_t __width) { |
| // Mask out inactive lanes to match AMDGPU behavior. |
| uint32_t __mask = (uint32_t)__lane_mask; |
| bool __bitmask = (1ull << __idx) & __lane_mask; |
| return -__bitmask & |
| __nvvm_shfl_sync_idx_i32(__mask, __x, __idx, |
| ((__gpu_num_lanes() - __width) << 8u) | 0x1f); |
| } |
| |
| // Returns a bitmask marking all lanes that have the same value of __x. |
| _DEFAULT_FN_ATTRS static __inline__ uint64_t |
| __gpu_match_any_u32(uint64_t __lane_mask, uint32_t __x) { |
| // Newer targets can use the dedicated CUDA support. |
| #if __CUDA_ARCH__ >= 700 |
| return __nvvm_match_any_sync_i32(__lane_mask, __x); |
| #else |
| return __gpu_match_any_u32_impl(__lane_mask, __x); |
| #endif |
| } |
| |
| // Returns a bitmask marking all lanes that have the same value of __x. |
| _DEFAULT_FN_ATTRS static __inline__ uint64_t |
| __gpu_match_any_u64(uint64_t __lane_mask, uint64_t __x) { |
| // Newer targets can use the dedicated CUDA support. |
| #if __CUDA_ARCH__ >= 700 |
| return __nvvm_match_any_sync_i64(__lane_mask, __x); |
| #else |
| return __gpu_match_any_u64_impl(__lane_mask, __x); |
| #endif |
| } |
| |
| // Returns the current lane mask if every lane contains __x. |
| _DEFAULT_FN_ATTRS static __inline__ uint64_t |
| __gpu_match_all_u32(uint64_t __lane_mask, uint32_t __x) { |
| // Newer targets can use the dedicated CUDA support. |
| #if __CUDA_ARCH__ >= 700 |
| int predicate; |
| return __nvvm_match_all_sync_i32p(__lane_mask, __x, &predicate); |
| #else |
| return __gpu_match_all_u32_impl(__lane_mask, __x); |
| #endif |
| } |
| |
| // Returns the current lane mask if every lane contains __x. |
| _DEFAULT_FN_ATTRS static __inline__ uint64_t |
| __gpu_match_all_u64(uint64_t __lane_mask, uint64_t __x) { |
| // Newer targets can use the dedicated CUDA support. |
| #if __CUDA_ARCH__ >= 700 |
| int predicate; |
| return __nvvm_match_all_sync_i64p(__lane_mask, __x, &predicate); |
| #else |
| return __gpu_match_all_u64_impl(__lane_mask, __x); |
| #endif |
| } |
| |
| // Returns true if the flat pointer points to CUDA 'shared' memory. |
| _DEFAULT_FN_ATTRS static __inline__ bool __gpu_is_ptr_local(void *ptr) { |
| return __nvvm_isspacep_shared(ptr); |
| } |
| |
| // Returns true if the flat pointer points to CUDA 'local' memory. |
| _DEFAULT_FN_ATTRS static __inline__ bool __gpu_is_ptr_private(void *ptr) { |
| return __nvvm_isspacep_local(ptr); |
| } |
| |
| // Terminates execution of the calling thread. |
| _DEFAULT_FN_ATTRS [[noreturn]] static __inline__ void __gpu_exit(void) { |
| __nvvm_exit(); |
| } |
| |
| // Suspend the thread briefly to assist the scheduler during busy loops. |
| _DEFAULT_FN_ATTRS static __inline__ void __gpu_thread_suspend(void) { |
| if (__nvvm_reflect("__CUDA_ARCH") >= 700) |
| asm("nanosleep.u32 64;" ::: "memory"); |
| } |
| |
| _Pragma("omp end declare variant"); |
| _Pragma("omp end declare target"); |
| |
| #endif // __NVPTXINTRIN_H |