#!/usr/bin/env python # This file is part of the CLBlast project. The project is licensed under Apache Version 2.0. This file follows the # PEP8 Python style guide and uses a max-width of 120 characters per line. # # Author(s): # Cedric Nugteren import argparse import json import os import sys import settings import plot import utils EXPERIMENTS = { "axpy": settings.AXPY, "gemv": settings.GEMV, "gemm": settings.GEMM, "gemm_small": settings.GEMM_SMALL, "symm": settings.SYMM, "syrk": settings.SYRK, "summary": settings.SUMMARY, } def run_benchmark(name, arguments_list, precision, num_runs, platform, device): binary = "./clblast_client_x" + name # Loops over sub-benchmarks per benchmark results = [] for arguments in arguments_list: # Sets the arguments constant_arguments = ["-warm_up", "-q", "-no_abbrv", "-cblas 0"] common_arguments = ["-precision %d" % precision, "-runs %d" % num_runs] opencl_arguments = ["-platform %d" % platform, "-device %d" % device] all_arguments = opencl_arguments + common_arguments + constant_arguments for name, value in arguments.items(): all_arguments.append("-" + name + " " + str(value)) # Calls the binary and parses the results benchmark_output = utils.run_binary(binary, all_arguments) result = utils.parse_results(benchmark_output) # For half-precision: also runs single-precision for comparison if precision == 16: all_arguments = [arg if arg != "-precision 16" else "-precision 32" for arg in all_arguments] benchmark_output = utils.run_binary(binary, all_arguments) result_extra = utils.parse_results(benchmark_output) for index in range(len(min(result, result_extra))): result[index]["GBs_1_FP32"] = result_extra[index]["GBs_1"] result[index]["GBs_2"] = result_extra[index]["GBs_2"] result[index]["GFLOPS_1_FP32"] = result_extra[index]["GFLOPS_1"] result[index]["GFLOPS_2"] = result_extra[index]["GFLOPS_2"] results.extend(result) return results def main(argv): # Parses the command-line arguments parser = argparse.ArgumentParser() parser.add_argument("-b", "--benchmark", required=True, help="The benchmark to perform (choose from %s)" % EXPERIMENTS.keys()) parser.add_argument("-p", "--platform", required=True, type=int, help="The ID of the OpenCL platform to test on") parser.add_argument("-d", "--device", required=True, type=int, help="The ID of the OpenCL device to test on") parser.add_argument("-n", "--num_runs", type=int, default=10, help="The number of benchmark repeats for averaging") parser.add_argument("-x", "--precision", type=int, default=32, help="The precision to test for (choose from 16, 32, 64, 3232, 6464") parser.add_argument("-l", "--load_from_disk", action="store_true", help="Increase verbosity of the script") parser.add_argument("-t", "--plot_title", default=None, help="The title for the plots, defaults to benchmark name") parser.add_argument("-z", "--tight_plot", action="store_true", help="Enables tight plot layout for in paper or presentation") parser.add_argument("-v", "--verbose", action="store_true", help="Increase verbosity of the script") cl_args = parser.parse_args(argv) # The benchmark name and plot title benchmark_name = utils.precision_to_letter(cl_args.precision) + cl_args.benchmark.upper() if cl_args.plot_title is None: cl_args.plot_title = benchmark_name # Retrieves the benchmark settings if cl_args.benchmark not in EXPERIMENTS.keys(): print("[benchmark] Invalid benchmark '%s', choose from %s" % (cl_args.benchmark, EXPERIMENTS.keys())) return experiment = EXPERIMENTS[cl_args.benchmark] benchmarks = experiment["benchmarks"] # Either run the benchmarks for this experiment or load old results from disk json_file_name = benchmark_name.lower() + "_benchmarks.json" if cl_args.load_from_disk and os.path.isfile(json_file_name): print("[benchmark] Loading previous benchmark results from '" + json_file_name + "'") with open(json_file_name) as f: results = json.load(f) else: # Runs all the individual benchmarks print("[benchmark] Running on platform %d, device %d" % (cl_args.platform, cl_args.device)) print("[benchmark] Running %d benchmarks for settings '%s'" % (len(benchmarks), cl_args.benchmark)) results = {"label_names": experiment["label_names"], "num_rows": experiment["num_rows"], "num_cols": experiment["num_cols"], "benchmarks": []} for benchmark in benchmarks: print("[benchmark] Running benchmark '%s:%s'" % (benchmark["name"], benchmark["title"])) result = run_benchmark(benchmark["name"], benchmark["arguments"], cl_args.precision, cl_args.num_runs, cl_args.platform, cl_args.device) results["benchmarks"].append(result) # Stores the results to disk print("[benchmark] Saving benchmark results to '" + json_file_name + "'") with open(json_file_name, "wb") as f: json.dump(results, f, sort_keys=True, indent=4) # Retrieves the data from the benchmark settings pdf_file_name = benchmark_name.lower() + "_plot.pdf" titles = [utils.precision_to_letter(cl_args.precision) + b["name"].upper() + " " + b["title"] for b in benchmarks] x_keys = [b["x_keys"] for b in benchmarks] y_keys = [b["y_keys"] for b in benchmarks] x_labels = [b["x_label"] for b in benchmarks] y_labels = [b["y_label"] for b in benchmarks] label_names = results["label_names"] # For half-precision: also adds single-precision results for comparison if cl_args.precision == 16: label_names = ["CLBlast FP16", "clBLAS FP32", "CLBlast FP32"] y_keys = [y_key + [y_key[0] + "_FP32"] for y_key in y_keys] # Plots the graphs plot.plot_graphs(results["benchmarks"], pdf_file_name, results["num_rows"], results["num_cols"], x_keys, y_keys, titles, x_labels, y_labels, label_names, cl_args.plot_title, cl_args.tight_plot, cl_args.verbose) print("[benchmark] All done") if __name__ == '__main__': main(sys.argv[1:])