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Merged
ajpotts merged 3 commits into from
Feb 10, 2026
Merged

Improve flatten benchmark #5360

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8067701
Improve flatten benchmark
ajpotts Jan 28, 2026
482e06d
Merge branch 'main' into flatten_benchmark_improvements
ajpotts Feb 9, 2026
b209877
Merge branch 'main' into flatten_benchmark_improvements
ajpotts Feb 10, 2026
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3 changes: 1 addition & 2 deletions benchmark.ini
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Original file line number Diff line number Diff line change
Expand Up @@ -14,8 +14,7 @@ testpaths =
benchmark_v2/coargsort_benchmark.py
benchmark_v2/split_benchmark.py
benchmark_v2/encoding_benchmark.py
benchmark_v2/reduce_benchmark.py
benchmark_v2/flatten_benchmark.py
benchmark_v2/reduce_benchmark.py
benchmark_v2/gather_benchmark.py
benchmark_v2/scatter_benchmark.py
benchmark_v2/setops_benchmark.py
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16 changes: 8 additions & 8 deletions benchmark_v2/optional/flatten_benchmark.py
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Expand Up @@ -19,24 +19,24 @@ def bench_ak_flatten_2d(benchmark, dtype, shape_type):

if shape_type == "square":
# Ensure N has an integer square root:
N = int(np.round(np.sqrt(N)) ** 2)
trimmed_N = int(np.round(np.sqrt(N)) ** 2)
sqrt_N = int(np.sqrt(N))
shape = (sqrt_N, sqrt_N)
elif shape_type == "tall":
# Ensure N is divisible by 2:
N = int(N // 2 * 2)
trimmed_N = int(N // 2 * 2)
shape = (N // 2, 2)
else:
# Ensure N is divisible by 2:
N = int(N // 2 * 2)
trimmed_N = int(N // 2 * 2)
shape = (2, N // 2)

if dtype == "int64":
data = ak.randint(0, 2**32, N, dtype=ak.int64, seed=pytest.seed)
data = ak.randint(0, 2**32, trimmed_N, dtype=ak.int64, seed=pytest.seed)
elif dtype == "float64":
data = ak.randint(0, 1, N, dtype=ak.float64, seed=pytest.seed)
data = ak.randint(0, 1, trimmed_N, dtype=ak.float64, seed=pytest.seed)
elif dtype == "bool":
data = ak.randint(0, 2, N, dtype=ak.bool_, seed=pytest.seed)
data = ak.randint(0, 2, trimmed_N, dtype=ak.bool_, seed=pytest.seed)

arr2d = data.reshape(shape)

Expand All @@ -46,8 +46,8 @@ def flatten_op():
benchmark.pedantic(flatten_op, rounds=pytest.trials)
num_bytes = calc_num_bytes(data)

benchmark.extra_info["description"] = f"Measures ak.flatten (np-style) on dtype={dtype}"
benchmark.extra_info["problem_size"] = N
benchmark.extra_info["description"] = f"Measures ak.flatten on 2D {shape_type} array, dtype={dtype}"
benchmark.extra_info["problem_size"] = trimmed_N
benchmark.extra_info["backend"] = "Arkouda"
benchmark.extra_info["num_bytes"] = num_bytes
# units are GiB/sec:
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