Initial import of code.

Author: ndryden

.gitmodules

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+[submodule "dace"]
+	path = dace
+	url = https://github.com/spcl/dace.git

config_selection/load_data.py

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+import os
+import os.path
+import functools
+import numpy as np
+import pandas as pd
+
+
+_int_kernel_cols = ['h', 'b', 'j', 'k', 'u', 'n', 'p']
+
+
+@functools.lru_cache(maxsize=None)
+def load_kernel(filename, cache=True):
+    if cache:
+        cache_filename = filename + '.pkl'
+        if os.path.exists(cache_filename):
+            return pd.read_pickle(cache_filename)
+    with open(filename, 'r') as f:
+        lines = f.readlines()
+    # Determine columns.
+    parts = lines[0].split(' ')
+    # -1 to skip the final 's'.
+    columns = [parts[i].lower() for i in range(0, len(parts) - 1, 3)]
+    data = {c: [] for c in columns}
+    for line in lines:
+        parts = line.split(' ')
+        for i in range(0, len(parts) - 1, 3):
+            data[parts[i].lower()].append(parts[i+2].lower())
+    data['time'] = [float(t) for t in data['time']]
+    # Try to convert to ints.
+    for col in _int_kernel_cols:
+        if col in data:
+            data[col] = [int(x) for x in data[col]]
+    df = pd.DataFrame(data=data)
+    def translate_layouts(x):
+        if isinstance(x, str):
+            x = x.translate({ord('n'): 'i'})
+        return x
+    df = df.applymap(translate_layouts)
+    if cache:
+        df.to_pickle(cache_filename)
+    return df
+
+
+@functools.lru_cache(maxsize=None)
+def load_tc(filename, cache=True):
+    if cache:
+        cache_filename = filename + '.pkl'
+        if os.path.exists(cache_filename):
+            return pd.read_pickle(cache_filename)
+    df = pd.read_csv(filename)
+    df.rename(columns={'Time': 'time'}, inplace=True)
+    if cache:
+        df.to_pickle(cache_filename)
+    return df

config_selection/merge_benchmarks.py

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+import argparse
+import glob
+import os.path
+import os
+from collections import Counter
+
+parser = argparse.ArgumentParser(
+    description='Concatenate all benchmark results into a single file')
+parser.add_argument(
+    'bmdir', type=str,
+    help='Directory containing benchmark results')
+parser.add_argument(
+    'outdir', type=str,
+    help='Directory to output results')
+parser.add_argument(
+    '--basename', type=str,
+    help='Basename of benchmark results to merge')
+
+if __name__ == '__main__':
+    args = parser.parse_args()
+    if not os.path.exists(args.bmdir):
+        raise ValueError(f'Benchmark directory {args.bmdir} not found')
+    if not os.path.exists(args.outdir):
+        os.makedirs(args.outdir)
+
+    if args.basename:
+        pattern = args.basename + '-bm*.csv'
+    else:
+        pattern = '*-bm*.csv'
+    bm_files = glob.glob(os.path.join(args.bmdir, pattern))
+    benchmark_results = Counter()
+    for f in bm_files:
+        name = os.path.splitext(os.path.basename(f))[0]
+        name = name.split('-')
+        name = '-'.join(name[:-1])
+        benchmark_results[name] += 1
+
+    for bm, num in benchmark_results.items():
+        print(f'Merging {num} results from {bm}')
+        with open(os.path.join(args.outdir, bm + '-combined.csv'), 'w') as out_f:
+            for i in range(num):
+                with open(os.path.join(args.bmdir, f'{bm}-bm{i}.csv'), 'r') as in_f:
+                    out_f.write(in_f.read())
+