| 42 | |
| 43 | @dataclass |
| 44 | class KernelHardwareInfo: |
| 45 | device_id: int = 0 |
| 46 | sm_count: int = 0 |
| 47 | |
| 48 | @staticmethod |
| 49 | def query_device_multiprocessor_count(device_id: int = 0, arch: str = "90a"): |
| 50 | cuda_header_code = f""" |
| 51 | #include <cuda_runtime.h> |
| 52 | #include <iostream> |
| 53 | static constexpr int device_id = {device_id}; |
| 54 | """ |
| 55 | cuda_code = """ |
| 56 | int main() { |
| 57 | cudaError_t result = cudaSetDevice(device_id); |
| 58 | if (result != cudaSuccess) { |
| 59 | std::cerr << "cudaSetDevice() returned error " |
| 60 | << cudaGetErrorString(result) << std::endl; |
| 61 | return 1; |
| 62 | } |
| 63 | int multiprocessor_count; |
| 64 | result = cudaDeviceGetAttribute(&multiprocessor_count, |
| 65 | cudaDevAttrMultiProcessorCount, device_id); |
| 66 | if (result != cudaSuccess) { |
| 67 | std::cerr << "cudaDeviceGetAttribute() returned error " |
| 68 | << cudaGetErrorString(result) << std::endl; |
| 69 | return 1; |
| 70 | } |
| 71 | std::cout << multiprocessor_count << std::endl; |
| 72 | return 0; |
| 73 | } |
| 74 | """ |
| 75 | # Combine the header and main CUDA code |
| 76 | full_cuda_code = cuda_header_code + cuda_code |
| 77 | |
| 78 | # Write the CUDA code to a temporary file |
| 79 | with open("temp_query_device.cu", "w") as file: |
| 80 | file.write(full_cuda_code) |
| 81 | |
| 82 | # Compile the CUDA code using nvcc |
| 83 | compile_command = ( |
| 84 | f"nvcc -arch=sm_{arch} temp_query_device.cu -o temp_query_device" |
| 85 | ) |
| 86 | try: |
| 87 | subprocess.run( |
| 88 | compile_command, |
| 89 | check=True, |
| 90 | shell=True, |
| 91 | text=True, |
| 92 | stderr=subprocess.PIPE, |
| 93 | ) |
| 94 | except subprocess.CalledProcessError as e: |
| 95 | print(f"Compilation failed: {e.stderr}") |
| 96 | return -1 |
| 97 | |
| 98 | # Run the compiled binary and capture the output |
| 99 | try: |
| 100 | result = subprocess.run( |
| 101 | "./temp_query_device", capture_output=True, text=True, check=True |