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32 lines
1.1 KiB
Python
32 lines
1.1 KiB
Python
# Minimal probe for nsys: train pedestal, run one batched pass, print summary.
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# Usage: nsys_kernel_probe.py [n_streams] [n_frames]
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import sys
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sys.path.append('/home/ferjao_k/aare/build')
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from pathlib import Path
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import time
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from aare import File, ClusterFinderCUDA
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n_streams = int(sys.argv[1]) if len(sys.argv) > 1 else 8
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N = int(sys.argv[2]) if len(sys.argv) > 2 else 2000
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base = Path('/mnt/sls_det_storage/moench_data/2603_MaxIVBeamtime/2026032408/process/xrf/')
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f = File(base / 'Cu_factor_10_data_master_0.json')
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pd = File(base / 'Cu_factor_10_pedestal_master_0.json')
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cf = ClusterFinderCUDA((f.rows, f.cols), (3, 3), n_sigma=5,
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max_clusters_per_frame=3000, n_streams=n_streams)
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for _ in range(1000):
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cf.push_pedestal_frame(pd.read_frame().copy())
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data = f.read_n(N)
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cf.register_input_buffer(data)
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t0 = time.perf_counter()
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res = cf.find_clusters_batched(data, first_frame=0)
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t = time.perf_counter() - t0
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cf.unregister_input_buffer()
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n = sum(cv.size for cv in res)
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print(f'n_streams={n_streams} N={N} wall={t:.3f}s ({N/t:.0f} FPS) '
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f'clusters/frame={n/N:.2f} event kernel_ms={cf.avg_kernel_time_ms():.3f}') |