/*************************************************************************************************** * Copyright (c) 2023 - 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved. * SPDX-License-Identifier: BSD-3-Clause * * Redistribution and use in source and binary forms, with or without * modification, are permitted provided that the following conditions are met: * * 1. Redistributions of source code must retain the above copyright notice, this * list of conditions and the following disclaimer. * * 2. Redistributions in binary form must reproduce the above copyright notice, * this list of conditions and the following disclaimer in the documentation * and/or other materials provided with the distribution. * * 3. Neither the name of the copyright holder nor the names of its * contributors may be used to endorse or promote products derived from * this software without specific prior written permission. * * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" * AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE * DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE * FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL * DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR * SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER * CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, * OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE * OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. * **************************************************************************************************/ #pragma once #include "cutlass/device_kernel.h" #if !defined(__CUDACC_RTC__) #include "cuda_runtime.h" #include "cutlass/cluster_launch.hpp" #include "cutlass/trace.h" #endif #include namespace cutlass { struct KernelHardwareInfo { // // Data members // // Hardware properties int device_id = 0; int sm_count = 0; // Kernel properties int max_active_clusters = 0; // Maximum number of clusters that could co-exist on the target device. dim3 cluster_shape = {0,0,0}; dim3 cluster_shape_fallback = {0,0,0}; // // Methods // #if !defined(__CUDACC_RTC__) static inline int query_device_multiprocessor_count(int device_id = 0) { cudaError_t result = cudaGetDevice(&device_id); if (result != cudaSuccess) { CUTLASS_TRACE_HOST( " cudaGetDevice() returned error " << cudaGetErrorString(result)); return 0; } int multiprocessor_count; result = cudaDeviceGetAttribute(&multiprocessor_count, cudaDevAttrMultiProcessorCount, device_id); if (result != cudaSuccess) { CUTLASS_TRACE_HOST( " cudaDeviceGetAttribute() returned error " << cudaGetErrorString(result)); return 0; } return multiprocessor_count; } // Query maximum number of active clusters that could co-exist on the target device // based on kernel properties such as cluster dims and threadblock dims static inline int query_device_max_active_clusters( dim3 cluster_dims, uint32_t threads_per_block, void const* kernel_ptr) { int max_active_clusters = 0; #if defined(CUTLASS_SM90_CLUSTER_LAUNCH_ENABLED) ClusterLauncher::LaunchConfig cluster_launch_config = ClusterLauncher::make_cluster_launch_config( cluster_dims /* minumum grid dim */, cluster_dims, {threads_per_block, 1, 1}); // Given the kernel function and launch configuration, return the maximum number of clusters that could co-exist on the target device. cudaError_t result = cudaOccupancyMaxActiveClusters(&max_active_clusters, kernel_ptr, &cluster_launch_config.launch_config); if (result != cudaSuccess) { CUTLASS_TRACE_HOST( " cudaGetDevice() returned error " << cudaGetErrorString(result)); return 0; } CUTLASS_TRACE_HOST("cudaOccupancyMaxActiveClusters: maximum number of clusters that could co-exist on the target device = " << max_active_clusters << "\n"); return max_active_clusters; #else CUTLASS_TRACE_HOST("ClusterLauncher: CUTLASS_SM90_CLUSTER_LAUNCH_ENABLED not defined! Aborting cluster occupancy query."); return max_active_clusters; #endif } // Simpler version of the above query function that fetches relevant information from the Kernel template static inline int query_device_max_active_clusters() { dim3 cluster_dims(cute::size<0>(typename Kernel::ClusterShape{}), cute::size<1>(typename Kernel::ClusterShape{}), cute::size<2>(typename Kernel::ClusterShape{})); uint32_t threads_per_block = Kernel::MaxThreadsPerBlock; void const* kernel_ptr = (void*)(device_kernel); return query_device_max_active_clusters(cluster_dims, threads_per_block, kernel_ptr); } template static inline KernelHardwareInfo make_kernel_hardware_info(int const device_id = 0, int sm_count = 0, int max_active_clusters = 0) { if (sm_count == 0) { sm_count = query_device_multiprocessor_count(device_id); } if (max_active_clusters == 0) { max_active_clusters = query_device_max_active_clusters(); } return {device_id, sm_count, max_active_clusters}; } #endif }; } // namespace cutlass