#!/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, "axpybatched": settings.AXPYBATCHED, "gemv": settings.GEMV, "gemm": settings.GEMM, "gemm_small": settings.GEMM_SMALL, "gemmbatched": settings.GEMMBATCHED, "gemmstridedbatched": settings.GEMMSTRIDEDBATCHED, "symm": settings.SYMM, "syrk": settings.SYRK, "summary": settings.SUMMARY, } COMPARISONS = ["clBLAS", "CPU-BLAS", "cuBLAS"] COMPARISON_ARGS = ["-clblas", "-cblas", "-cublas"] COMPARISON_IDS = [2, 3, 4] def run_benchmark(name, arguments_list, precision, num_runs, platform, device, comparisons): 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"] common_arguments = ["-precision %d" % precision, "-runs %d" % num_runs] opencl_arguments = ["-platform %d" % platform, "-device %d" % device] comparison_arguments = [] for name, arg in zip(COMPARISONS, COMPARISON_ARGS): if name in comparisons: comparison_arguments.append(arg + " 1") else: comparison_arguments.append(arg + " 0") all_arguments = opencl_arguments + common_arguments + constant_arguments + comparison_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(min(len(result), len(result_extra))): result[index]["GBs_1_FP32"] = result_extra[index]["GBs_1"] result[index]["GFLOPS_1_FP32"] = result_extra[index]["GFLOPS_1"] for id in COMPARISON_IDS: if "GBs_%d" % id in result_extra[index].keys(): result[index]["GBs_%d" % id] = result_extra[index]["GBs_%d" % id] result[index]["GFLOPS_%d" % id] = result_extra[index]["GFLOPS_%d" % id] results.extend(result) return results def parse_arguments(argv): parser = argparse.ArgumentParser(description="Runs a full benchmark for a specific routine on a specific device") parser.add_argument("-b", "--benchmark", required=True, help="The benchmark to perform (choose from %s)" % sorted(EXPERIMENTS.keys())) parser.add_argument("-c", "--comparisons", default=[], nargs='+', help="The library(s) to compare against (choose from %s)" % COMPARISONS) 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=None, help="Overrides the default 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="Loading existing results from JSON file and replot") parser.add_argument("-t", "--plot_title", default="", 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("-o", "--output_folder", default=os.getcwd(), help="Sets the folder for output plots (defaults to current folder)") parser.add_argument("-v", "--verbose", action="store_true", help="Increase verbosity of the script") cl_args = parser.parse_args(argv) return vars(cl_args) def benchmark_single(benchmark, comparisons, platform, device, num_runs, precision, load_from_disk, plot_title, tight_plot, output_folder, verbose): # Sanity check if not os.path.isdir(output_folder): print("[benchmark] Error: folder '%s' doesn't exist" % output_folder) return # The benchmark name and plot title benchmark_name = utils.precision_to_letter(precision) + benchmark.upper() if benchmark.upper() != "SUMMARY": plot_title = benchmark_name if plot_title == "" else benchmark_name + ": " + plot_title # Retrieves the comparison settings library_ids = [1] for comparison in comparisons: if comparison not in COMPARISONS: print("[benchmark] Invalid comparison library '%s', choose from %s" % (comparison, COMPARISONS)) return library_ids.append(COMPARISON_IDS[COMPARISONS.index(comparison)]) # Retrieves the benchmark settings if benchmark not in EXPERIMENTS.keys(): print("[benchmark] Invalid benchmark '%s', choose from %s" % (benchmark, EXPERIMENTS.keys())) return experiment = EXPERIMENTS[benchmark] benchmarks = experiment["benchmarks"] # Either run the benchmarks for this experiment or load old results from disk json_file_name = os.path.join(output_folder, benchmark_name.lower() + "_benchmarks.json") if 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" % (platform, device)) print("[benchmark] Running %d benchmarks for settings '%s'" % (len(benchmarks), benchmark)) results = {"label_names": ["CLBlast"] + comparisons, "num_rows": experiment["num_rows"], "num_cols": experiment["num_cols"], "benchmarks": []} for bench in benchmarks: num_runs_benchmark = bench["num_runs"] if num_runs is None else num_runs print("[benchmark] Running benchmark '%s:%s'" % (bench["name"], bench["title"])) result = run_benchmark(bench["name"], bench["arguments"], precision, num_runs_benchmark, platform, device, comparisons) results["benchmarks"].append(result) # Stores the results to disk print("[benchmark] Saving benchmark results to '" + json_file_name + "'") with open(json_file_name, "w") as f: json.dump(results, f, sort_keys=True, indent=4) # Retrieves the data from the benchmark settings file_name_suffix = "_tight" if tight_plot else "" pdf_file_name = os.path.join(output_folder, benchmark_name.lower() + "_plot" + file_name_suffix + ".pdf") titles = [b["title"] if "BATCHED" in b["name"].upper() else utils.precision_to_letter(precision) + b["name"].upper() + " " + b["title"] for b in benchmarks] x_keys = [b["x_keys"] for b in benchmarks] y_keys = [["%s_%d" % (b["y_key"], i) for i in library_ids] 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 precision == 16: label_names[0] += " FP16" for index in range(1, len(label_names)): label_names[index] += " FP32" label_names.append("CLBlast FP32") y_keys = [y_key + [y_key[0] + "_FP32"] for y_key in y_keys] # For batched routines: comparison is non-batched if benchmark in ["axpybatched", "gemmbatched", "gemmstridedbatched"]: for index in range(1, len(label_names)): label_names[index] += " (non-batched)" # 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, plot_title, tight_plot, verbose) print("[benchmark] All done") if __name__ == '__main__': parsed_arguments = parse_arguments(sys.argv[1:]) benchmark_single(**parsed_arguments)