From c0f2aa2b64bdc0d18432dbc98ce80d20a70207aa Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Constantin=20F=C3=BCrst?= Date: Tue, 12 Dec 2023 16:22:11 +0100 Subject: [PATCH] re-plot the benchmarks with the new data --- .../plot-perf-peakthroughput.py | 10 +++++----- .../plot-perf-allnodethroughput.png | Bin 0 -> 100543 bytes .../plot-perf-peakthroughput.png | Bin 109674 -> 0 bytes .../plot-perf-smartthroughput.png | Bin 0 -> 118921 bytes 4 files changed, 5 insertions(+), 5 deletions(-) create mode 100644 benchmarks/benchmark-results/plot-perf-allnodethroughput.png delete mode 100644 benchmarks/benchmark-results/plot-perf-peakthroughput.png create mode 100644 benchmarks/benchmark-results/plot-perf-smartthroughput.png diff --git a/benchmarks/benchmark-plotters/plot-perf-peakthroughput.py b/benchmarks/benchmark-plotters/plot-perf-peakthroughput.py index 6867cce..29957fd 100644 --- a/benchmarks/benchmark-plotters/plot-perf-peakthroughput.py +++ b/benchmarks/benchmark-plotters/plot-perf-peakthroughput.py @@ -11,7 +11,7 @@ runid = "Run ID" x_label = "Destination Node" y_label = "Source Node" v_label = "Throughput" -title = "Copy Throughput for 1GiB Elements running on SRC Node" +title = "Copy Throughput in GiB/s tested for 1GiB Elements using all 8 DSA Chiplets" index = [ runid, x_label, y_label] data = [] @@ -34,11 +34,11 @@ def load_time_mesurements(file_path): with open(file_path, 'r') as file: data = json.load(file) count = data["count"] - batch_size = 8 + batch_size = data["list"][0]["task"]["batching"]["batch_size"] if data["list"][0]["task"]["batching"]["batch_size"] > 0 else 1 iterations = data["list"][0]["task"]["iterations"] return { - "total": sum([x / (iterations * batch_size * count) for x in list(chain([data["list"][i]["report"]["time"]["total"] for i in range(count)]))]), + "total": sum([x / (iterations * batch_size * count * count) for x in list(chain([data["list"][i]["report"]["time"]["total"] for i in range(count)]))]), "combined": [ x / (count * batch_size) for x in list(chain(*[data["list"][i]["report"]["time"]["combined"] for i in range(count)]))], "submission": [ x / (count * batch_size) for x in list(chain(*[data["list"][i]["report"]["time"]["submission"] for i in range(count)]))], "completion": [ x / (count * batch_size) for x in list(chain(*[data["list"][i]["report"]["time"]["completion"] for i in range(count)]))] @@ -63,7 +63,7 @@ def main(): for src_node in range(16): for dst_node in range(16): - file = os.path .join(folder_path, f"copy-n{src_node}ton{dst_node}-1gib-4e.json") + file = os.path.join(folder_path, f"copy-n{src_node}ton{dst_node}-1gib-allnodes-1e.json") process_file_to_dataset(file, src_node, dst_node) df = pd.DataFrame(data) @@ -73,7 +73,7 @@ def main(): sns.heatmap(data_pivot, annot=True, cmap="YlGn", fmt=".0f") plt.title(title) - plt.savefig(os.path.join(folder_path, "plot-perf-peakthroughput.png"), bbox_inches='tight') + plt.savefig(os.path.join(folder_path, 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