feat: parallelise Monte Carlo, add histogram sorting - #3
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Parallel Monte Carlo: - Fan-out/fan-in across runtime.NumCPU() goroutines with per-worker ChaCha8 PRNGs seeded from crypto/rand - Workers accumulate in local frequency maps, send batches of 10,000 - Wall-clock: 100M trials in 220ms vs 17.5s sequential (80x, M3 Pro) Histogram sorting: - --sort flag: original, count[-desc|-asc], name[-asc|-desc] - --rank shorthand for --sort=count (most frequent first) - Sort applies to both terminal histogram and TSV output Google Go Style Guide fixes: - Extract whitespace regexp to package-level var - Return errors from Histogram.Render and WriteTSV - Fix MonteCarlo doc comment grammar README: - Define all first-use acronyms (GCSE, ODE, POSIX, CSPRNG, PRNG, TSV) - New section 2.8 on concurrent trial generation with benchmarks - Worked examples for sort/rank flags - Updated flags reference
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Parallel Monte Carlo: - Fan-out/fan-in across runtime.NumCPU() goroutines with per-worker ChaCha8 PRNGs seeded from crypto/rand - Workers accumulate in local frequency maps, send batches of 10,000 - Wall-clock: 100M trials in 220ms vs 17.5s sequential (80x, M3 Pro) Histogram sorting: - --sort flag: original, count[-desc|-asc], name[-asc|-desc] - --rank shorthand for --sort=count (most frequent first) - Sort applies to both terminal histogram and TSV output Google Go Style Guide fixes: - Extract whitespace regexp to package-level var - Return errors from Histogram.Render and WriteTSV - Fix MonteCarlo doc comment grammar README: - Define all first-use acronyms (GCSE, ODE, POSIX, CSPRNG, PRNG, TSV) - New section 2.8 on concurrent trial generation with benchmarks - Worked examples for sort/rank flags - Updated flags reference
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See commit message for full details. 80x wall-clock speedup at 100M trials, histogram sort/rank flags, style guide fixes, acronym definitions.