#include #include #include #include #include #include int profile_gemm(int, char*[]); int profile_batched_gemm(int, char*[]); int profile_gemm_bias_2d(int, char*[]); int profile_gemm_bias_relu(int, char*[]); int profile_gemm_bias_relu_add(int, char*[]); int profile_conv_fwd(int, char*[]); int profile_conv_fwd_bias_relu(int, char*[]); int profile_conv_fwd_bias_relu_add(int, char*[]); int profile_conv_fwd_bias_relu_atomic_add(int, char*[]); int main(int argc, char* argv[]) { if(strcmp(argv[1], "gemm") == 0) { return profile_gemm(argc, argv); } else if(strcmp(argv[1], "gemm_bias_2d") == 0) { return profile_gemm_bias_2d(argc, argv); } else if(strcmp(argv[1], "gemm_bias_relu") == 0) { return profile_gemm_bias_relu(argc, argv); } else if(strcmp(argv[1], "gemm_bias_relu_add") == 0) { return profile_gemm_bias_relu_add(argc, argv); } else if(strcmp(argv[1], "batched_gemm") == 0) { return profile_batched_gemm(argc, argv); } else if(strcmp(argv[1], "conv_fwd") == 0) { return profile_conv_fwd(argc, argv); } else if(strcmp(argv[1], "conv_fwd_bias_relu") == 0) { return profile_conv_fwd_bias_relu(argc, argv); } else if(strcmp(argv[1], "conv_fwd_bias_relu_add") == 0) { return profile_conv_fwd_bias_relu_add(argc, argv); } else if(strcmp(argv[1], "conv_fwd_bias_relu_atomic_add") == 0) { return profile_conv_fwd_bias_relu_atomic_add(argc, argv); } else { // clang-format off printf("arg1: tensor operation (gemm: GEMM\n" " gemm_bias_2d: GEMM+Bias(2D)\n" " gemm_bias_relu: GEMM+Bias+ReLU\n" " gemm_bias_relu_add: GEMM+Bias+ReLU+Add\n" " conv_fwd: ForwardConvolution\n" " conv_fwd_bias_relu: ForwardConvolution+Bias+ReLU\n" " conv_fwd_bias_relu_add: ForwardConvolution+Bias+ReLU+Add\n" " conv_fwd_bias_relu_atomic_add: ForwardConvolution+Bias+ReLU+AtomicAdd\n"); // clang-format on return 0; } }