Performance#

Welcome to Performance, the foundational module detailing how MolSysMT handles Big Data trajectories, high-throughput numerical calculations, and hardware scaling. Structural biology simulations often involve millions of atoms and thousands of trajectory frames, expanding file sizes into tens or hundreds of gigabytes. MolSysMT is built from the ground up to process these massive datasets efficiently without overwhelming workstation memory or sacrificing execution speed.

This module introduces MolSysMT’s performance architecture: deferred evaluation via lazy loading, bounded memory streaming with the chunked execution engine, compiled Rust C-API acceleration, CPU multi-threading, validated execution boundaries, SMonitor diagnostics, caching layers, empirical benchmark metrics, and the GPU acceleration roadmap.

Contents#

  • Lazy Loading
    Metadata-first initialization, deferred evaluation, and streaming I/O for processing large datasets without eager memory allocation.

  • Chunked Execution
    Managing the memory wall problem, the ChunkedExecutor engine, eager vs. heavy execution paths, and memory pressure monitoring.

  • The Rust Core
    High-performance compiled C/Rust native kernels for heavy distance calculations, minimum image conventions, SASA, and RMSD.

  • Parallel Execution
    Multi-core CPU parallelization with Rayon, threadpool concurrency, and SIMD compiler vectorization.

  • Internal Optimizations
    Low-overhead internal optimizations: puw.fast_track unit bypass, controlled digestion bypass, kernel-input preparation, and zero-copy array views.

  • Diagnostics & Profiling with SMonitor
    Execution timeline profiling, RAM memory pressure warnings (MemoryPressureWarning), and telemetry events managed through SMonitor.

  • Caching & Memoization
    Selection query AST memoization, index caching, and dynamic form registry caching for zero-overhead iterative calls.

  • Benchmarks
    Empirical throughput metrics, memory scaling benchmarks, Python vs. Rust performance comparisons, and Showcase links.

  • GPU Acceleration
    Strategic roadmap for Post-1.0 CUDA and WGPU kernel acceleration for massive trajectory spatial analysis.

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