Vision

FASTSolver aims to revolutionize scientific computing by providing a seamless, high-performance framework that bridges the gap between ease of use and computational efficiency. Our roadmap outlines the strategic development path toward achieving this vision.

Current State (2025 Q1)

Core Features

• Hybrid Python/C++ architecture

  • Python frontend with NumPy-compatible API:
    • Full compatibility with NumPy’s ndarray operations
    • Support for broadcasting and advanced indexing
    • Array operations with minimal overhead (<5% compared to native NumPy)
    • Transparent data type conversion and memory management
    • Just-in-time compilation for critical code paths
  • C++ computational backend:
    • Optimized computational core using modern C++20 features
    • SIMD vectorization with AVX-512 instruction set
    • Cache-friendly data structures with aligned memory access
    • Template metaprogramming for compile-time optimizations
    • Performance >80% of pure C++ implementations
  • Automated type conversion and memory management:
    • Zero-copy data transfer between Python and C++ layers using Pybind11
    • Intelligent memory pooling for frequent allocations
    • Custom allocator with thread-local caching
    • Reference counting with cycle detection
    • Automatic memory defragmentation

• Advanced numerical solvers