Files
GR-raytracing/benchmarks/hip_psf_2026-09-07/prepare_inputs.py
T
wyj e1ec480669 HIP: accelerate PSF accumulation and restore parallel producers
Cooperate across 32 lanes per PSF and use two completion-protected staging slots with complete batch timing. Restore coarse OpenMP event production while serializing shared GPU submissions and direct fallback boundaries.

Add bounded benchmarks, streaming and renderer regressions, and preserve validation evidence and ownership documentation.
2026-09-06 21:38:53 -04:00

28 lines
1.3 KiB
Python

#!/usr/bin/env python3
"""Recreate the bounded 2MASS samples used in this investigation."""
import hashlib
from pathlib import Path
repo = Path(__file__).resolve().parents[2]
source = repo / "assets/2mass/processed/all_sky"
multi = Path("/tmp/gr-hip-catalog-multi")
single = Path("/tmp/gr-hip-catalog-subset")
multi.mkdir(exist_ok=True)
single.mkdir(exist_ok=True)
for name in ["tile_ra252_dec048.csv", "tile_ra262_dec060.csv", "tile_ra082_dec090.csv"]:
raw = (source / name).read_bytes()
rows = raw.decode().splitlines()
n = min(8192, len(rows) - 1)
sample = ("\n".join([rows[0]] + [rows[1 + i * (len(rows) - 1) // n]
for i in range(n)]) + "\n").encode()
(multi / name).write_bytes(sample)
if name == "tile_ra252_dec048.csv":
(single / name).write_bytes(sample)
(Path(__file__).parent / "catalog_8192.csv").write_bytes(sample)
small = "\n".join([rows[0]] + [rows[1 + i * (len(rows) - 1) // 256]
for i in range(256)]) + "\n"
(Path(__file__).parent / "catalog_256.csv").write_text(small)
print(name, "source_stars", len(rows) - 1, "sampled", n,
"source_sha256", hashlib.sha256(raw).hexdigest(),
"sample_sha256", hashlib.sha256(sample).hexdigest())