Monte Carlo Benchmarking Engine
High-performance SIMD Monte Carlo engine (AVX2/NEON) with custom memory allocators and perf logging.
 
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[detail level 12]
  pipeline
 combine_batch_parquets.pyCombines multiple per-method parquet log files into a single file
 gen_perf_parquet_logs.pyGenerates perf benchmarking parquet from command-line arguments
 insert_to_clickhouse.pyInserts filtered benchmarking logs into a ClickHouse database
 parse_perf_metrics.pyCLI flag generator from perf CSV output (perf stat -x,)
 schema.pyDefines the canonical schema used across ETL, validation, and ClickHouse ingestion
 schema_to_clickhouse.pyConverts Polars schema to ClickHouse-compatible SQL
 utils.pyShared utilities for safe casting, schema enforcement, and arithmetic fallback logic
  scripts
 config.pyLoads environment-based configuration for pipeline and services
 run_perf.shDockerized perf benchmarker for Monte Carlo simulation engine
 setup.pyCLI utility to initialize ClickHouse + Grafana for benchmark pipeline
 benchmark.hppWall-clock + cycle-accurate benchmarking for performance profiling
 main.cppCLI runner for benchmarking Monte Carlo simulation methods
 montecarlo.hppHigh-performance Monte Carlo π Estimation Engine — SIMD-accelerated, memory-optimized
 pool.hppFixed-size aligned pool allocator for high-performance simulations