|
| 1 | +import json |
| 2 | + |
| 3 | +import matplotlib.pyplot as plt |
| 4 | +import numpy as np |
| 5 | +import pandas as pd |
| 6 | + |
| 7 | +BENCHMARKS_JSON = "results.json" |
| 8 | + |
| 9 | +# Hardware details shown in title |
| 10 | +HARDWARE = "AMD Ryzen 9 9900X 12-Core Processor 63032 MB (fp64 fp16)\noneAPI 2025.1.3 Intel(R) OpenCL Graphics: Intel(R) Arc(TM) B580 Graphics, 11873 MB (fp64 fp16)" |
| 11 | + |
| 12 | +# Show speedup in graph |
| 13 | +SHOW_NUMBERS = True |
| 14 | + |
| 15 | +# Round to digits after decimal |
| 16 | +ROUND_NUMBERS = 1 |
| 17 | + |
| 18 | +# package list in graph order; arrayfire packages are added later |
| 19 | +PKG_NAMES = ["numpy", "dpnp", "cupy"] |
| 20 | + |
| 21 | +# color used in graphs |
| 22 | +PKG_COLOR = { |
| 23 | + "numpy": "tab:blue", |
| 24 | + "cupy": "tab:green", |
| 25 | + "dpnp": "tab:red", |
| 26 | + "afcpu": "tab:orange", |
| 27 | + "afopencl": "tab:orange", |
| 28 | + "afcuda": "tab:orange", |
| 29 | + "afoneapi": "tab:orange", |
| 30 | +} |
| 31 | + |
| 32 | +# labels displayed in the graph |
| 33 | +PKG_LABELS = { |
| 34 | + "numpy": "numpy[cpu]", |
| 35 | + "dpnp": "dpnp[level_zero:gpu]", |
| 36 | + "cupy": "cupy", |
| 37 | + "afcpu": "afcpu", |
| 38 | + "afcuda": "afcuda", |
| 39 | + "afopencl": "afopencl[opencl:gpu]", |
| 40 | + "afoneapi": "afoneapi[opencl:gpu]", |
| 41 | +} |
| 42 | + |
| 43 | +AFBACKENDS = ["afcpu", "afcuda", "afopencl", "afoneapi"] |
| 44 | + |
| 45 | +# Tests to be shown in graphs |
| 46 | +TESTS = [ |
| 47 | + "qr", |
| 48 | + "neural_network", |
| 49 | + "gemm", |
| 50 | + "mandelbrot", |
| 51 | + "nbody", |
| 52 | + "pi", |
| 53 | + "black_scholes", |
| 54 | + "fft", |
| 55 | + "normal", |
| 56 | + "group_elementwise", |
| 57 | + # Other tests |
| 58 | + # 'svd |
| 59 | + # 'cholesky', |
| 60 | + # 'det', |
| 61 | + # 'norm', |
| 62 | + # 'uniform', |
| 63 | + # 'inv' |
| 64 | +] |
| 65 | + |
| 66 | + |
| 67 | +def get_benchmark_data(): |
| 68 | + results = {} |
| 69 | + descriptions = {} |
| 70 | + with open(BENCHMARKS_JSON) as f: |
| 71 | + js = json.load(f) |
| 72 | + for bench in js["benchmarks"]: |
| 73 | + test_name = bench["name"] |
| 74 | + test_name = test_name[test_name.find("_") + 1 : test_name.find("[")] |
| 75 | + |
| 76 | + key = bench["param"] |
| 77 | + val = bench["stats"]["ops"] |
| 78 | + |
| 79 | + if len(bench["extra_info"]) != 0 and (not test_name in descriptions): |
| 80 | + descriptions[test_name] = bench["extra_info"]["description"] |
| 81 | + |
| 82 | + if test_name not in results: |
| 83 | + results[test_name] = {key: val} |
| 84 | + else: |
| 85 | + results[test_name][key] = val |
| 86 | + |
| 87 | + return results, descriptions |
| 88 | + |
| 89 | + |
| 90 | +def create_graph(test_name, test_results): |
| 91 | + names = [] |
| 92 | + values = [] |
| 93 | + for name in test_results: |
| 94 | + names.append(name) |
| 95 | + values.append(test_results[name]) |
| 96 | + |
| 97 | + bar = plt.bar(names, values) |
| 98 | + plt.title(test_name) |
| 99 | + |
| 100 | + plt.savefig("img/" + test_name + ".png") |
| 101 | + plt.close() |
| 102 | + |
| 103 | + |
| 104 | +def generate_individual_graphs(): |
| 105 | + results, descriptions = get_benchmark_data() |
| 106 | + |
| 107 | + for test in results: |
| 108 | + create_graph(test, results[test]) |
| 109 | + |
| 110 | + |
| 111 | +# Stores the timing results in a csv file |
| 112 | +def store_csv(): |
| 113 | + data_dict = {} |
| 114 | + data_dict["Test(seconds)"] = [] |
| 115 | + results = {} |
| 116 | + for pkg in PKG_LABELS.keys(): |
| 117 | + data_dict[pkg] = [] |
| 118 | + results[pkg] = {} |
| 119 | + |
| 120 | + with open(BENCHMARKS_JSON) as f: |
| 121 | + js = json.load(f) |
| 122 | + for bench in js["benchmarks"]: |
| 123 | + test_name = bench["name"] |
| 124 | + test_name = test_name[test_name.find("_") + 1 : test_name.find("[")] |
| 125 | + |
| 126 | + pkg = bench["param"] |
| 127 | + time = bench["stats"]["mean"] |
| 128 | + |
| 129 | + if not test_name in data_dict["Test(seconds)"]: |
| 130 | + data_dict["Test(seconds)"].append(test_name) |
| 131 | + |
| 132 | + results[pkg][test_name] = time |
| 133 | + |
| 134 | + for test in data_dict["Test(seconds)"]: |
| 135 | + for pkg in PKG_LABELS.keys(): |
| 136 | + if test in results[pkg]: |
| 137 | + data_dict[pkg].append(results[pkg][test]) |
| 138 | + else: |
| 139 | + data_dict[pkg].append(np.nan) |
| 140 | + |
| 141 | + df = pd.DataFrame(data_dict) |
| 142 | + df.to_csv("summary.csv") |
| 143 | + |
| 144 | + |
| 145 | +def generate_group_graph(test_list=None, show_numbers=False, filename="comparison"): |
| 146 | + results, descriptions = get_benchmark_data() |
| 147 | + |
| 148 | + width = 1 / (1 + len(PKG_NAMES)) |
| 149 | + multiplier = 0 |
| 150 | + |
| 151 | + tests = None |
| 152 | + if test_list: |
| 153 | + tests = test_list |
| 154 | + else: |
| 155 | + tests = results.keys() |
| 156 | + |
| 157 | + tests_values = {} |
| 158 | + x = np.arange(len(tests)) |
| 159 | + |
| 160 | + for name in PKG_NAMES: |
| 161 | + tests_values[name] = [] |
| 162 | + |
| 163 | + max_val = 1 |
| 164 | + for test in tests: |
| 165 | + for name in PKG_NAMES: |
| 166 | + base_value = results[test]["numpy"] |
| 167 | + if name in results[test]: |
| 168 | + val = results[test][name] / base_value |
| 169 | + |
| 170 | + if ROUND_NUMBERS: |
| 171 | + val = round(val, ROUND_NUMBERS) |
| 172 | + |
| 173 | + if max_val < val: |
| 174 | + max_val = val |
| 175 | + |
| 176 | + tests_values[name].append(val) |
| 177 | + else: |
| 178 | + tests_values[name].append(np.nan) |
| 179 | + |
| 180 | + fig, ax = plt.subplots(layout="constrained") |
| 181 | + |
| 182 | + for name in PKG_NAMES: |
| 183 | + offset = width * multiplier |
| 184 | + rects = ax.barh(x + offset, tests_values[name], width, label=PKG_LABELS[name], color=PKG_COLOR[name]) |
| 185 | + |
| 186 | + if show_numbers: |
| 187 | + ax.bar_label(rects, padding=3, rotation=0) |
| 188 | + multiplier += 1 |
| 189 | + |
| 190 | + xlabels = [] |
| 191 | + for test in tests: |
| 192 | + xlabels.append(test + "\n" + descriptions[test]) |
| 193 | + |
| 194 | + ax.set_xlabel("Speedup") |
| 195 | + ax.set_xscale("log") |
| 196 | + ax.set_title(f"Runtime Comparison\n{HARDWARE}") |
| 197 | + ax.set_yticks(x + width, xlabels, rotation=0) |
| 198 | + xmin, xmax = ax.get_xlim() |
| 199 | + ax.set_xlim(xmin, xmax * 2) |
| 200 | + |
| 201 | + ax.legend(loc="lower right", ncols=len(PKG_NAMES)) |
| 202 | + fig.set_figheight(8) |
| 203 | + fig.set_figwidth(13) |
| 204 | + fig.savefig(f"img/{filename}.png") |
| 205 | + plt.show() |
| 206 | + |
| 207 | + |
| 208 | +def main(): |
| 209 | + store_csv() |
| 210 | + for backend in AFBACKENDS: |
| 211 | + try: |
| 212 | + filename = f"comparison_{backend}" |
| 213 | + if not backend in PKG_NAMES: |
| 214 | + PKG_NAMES.insert(1, backend) |
| 215 | + generate_group_graph(TESTS, SHOW_NUMBERS, filename) |
| 216 | + PKG_NAMES.remove(backend) |
| 217 | + except Exception as e: |
| 218 | + print(e) |
| 219 | + print("No data for", backend) |
| 220 | + |
| 221 | + |
| 222 | +if __name__ == "__main__": |
| 223 | + main() |
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