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#!/usr/bin/env python3
import os
import sys
import math
import cccl.bench
def elapsed_time_looks_good(x):
if isinstance(x, float):
if math.isfinite(x):
return True
return False
def get_largest_problem_size(rt_values):
# Small problem sizes do not utilize entire GPU.
# Benchmarking small problem sizes in environments where we do not control
# distributions comparison, e.g. CI, is not useful because of stability issues.
elements = []
for element in rt_values:
if element.isdigit():
elements.append(int(element))
return [str(max(elements))]
def filter_runtime_workloads_for_ci(rt_values):
for subbench in rt_values:
for axis in rt_values[subbench]:
if axis.startswith('Elements') and axis.endswith('[pow2]'):
rt_values[subbench][axis] = get_largest_problem_size(rt_values[subbench][axis])
return rt_values
class BaseRunner:
def __init__(self):
self.estimator = cccl.bench.MedianCenterEstimator()
def __call__(self, algname, ct_workload_space, rt_values):
failure_occured = False
rt_values = filter_runtime_workloads_for_ci(rt_values)
for ct_workload in ct_workload_space:
bench = cccl.bench.BaseBench(algname)
if bench.build(): # might throw
results = bench.run(ct_workload, rt_values, self.estimator, False)
for subbench in results:
for point in results[subbench]:
bench_name = "{}.{}-{}".format(bench.algorithm_name(), subbench, point)
bench_name = bench_name.replace(' ', '___')
bench_name = "".join(c if c.isalnum() else "_" for c in bench_name)
elapsed_time = results[subbench][point]
if elapsed_time_looks_good(elapsed_time):
print("&&&& PERF {} {} -sec".format(bench_name, elapsed_time))
else:
failure_occured = True
print("&&&& FAILED {}".format(algname))
if failure_occured:
sys.exit(1)
def main():
print("&&&& RUNNING bench")
os.environ["CUDA_MODULE_LOADING"] = "EAGER"
cccl.bench.search(BaseRunner())
print("&&&& PASSED bench")
if __name__ == "__main__":
main()
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