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Changelog

All notable changes to this project will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

1.0.0 - 2025-04-16

🎉 First Stable Release

This is the first stable release of GPU SpMV, featuring complete CSR and ELL format support, four optimized CUDA kernels with automatic selection, and production-ready engineering quality.

✨ Added

Core Features

  • CSR (Compressed Sparse Row) sparse matrix format with full operations
  • ELL (ELLPACK) sparse matrix format with column-major GPU-optimized storage
  • Four CUDA Kernels: Scalar CSR, Vector CSR, Merge Path, ELL Kernel
  • Automatic kernel selection based on matrix statistics (avg_nnz, skewness)
  • Texture cache support with SpMVExecutionContext for object reuse
  • RAII resource management: CudaBuffer<T>, CudaTimer, ScopedTexture
  • Semantic error codes: SpMVError enum with descriptive error messages

Performance & Benchmarking

  • Bandwidth metrics calculation with GPU peak bandwidth detection
  • Comprehensive benchmarking framework with warmup runs and statistical analysis
  • GPU vs CPU performance comparison with speedup metrics
  • JSON export for benchmark results

Applications

  • PageRank algorithm with GPU-accelerated iterative computation
  • Configurable damping factor and convergence tolerance
  • Top-K node ranking extraction

Engineering Quality

  • CMake Presets for easy Debug/Release builds
  • CPU-only configuration option for development environments
  • Cross-platform support (Windows/Linux)
  • Complete Google Test test suite with property-based testing
  • GitHub Actions CI/CD with format checking
  • Doxygen-compatible documentation

Documentation

  • Full documentation site at https://lessup.github.io/gpu-spmv/
  • Bilingual README (English and Chinese)
  • API reference, performance guide, and code examples
  • Architecture documentation and design decision records

🔒 Security

  • Integer overflow protection in size calculations
  • Memory bounds checking in matrix operations

🚀 Performance

  • ELL Column-major storage for fully coalesced memory access
  • Warp-level shuffle reduction avoiding shared memory bank conflicts
  • Merge Path algorithm for perfect load balancing on irregular matrices
  • Automatic texture cache for large input vectors (>10000 elements)

0.1.0 - 2025-03-01

🚀 Initial Release

  • Basic project structure
  • Initial CSR matrix implementation
  • Simple SpMV GPU kernel
  • CMake build configuration

Version History

Version Date Status Highlights
1.0.0 2025-04-16 Stable First stable release with complete feature set
0.1.0 2025-03-01 Archived Initial prototype

Migration Guide

Upgrading to 1.0.0

No breaking changes from pre-release versions. The API is now stable.

Recommended Updates

  1. Use named constants instead of magic numbers:

    // Before
config.block_size = 256;
config.use_texture = (cols > 10000);

// After (recommended)
config.block_size = spmv::DEFAULT_BLOCK_SIZE;
config.use_texture = (cols > spmv::TEXTURE_CACHE_THRESHOLD_COLS);

  2. Use SpMVExecutionContext for texture object reuse:

    // Before: Texture created/destroyed each call
for (int i = 0; i < iterations; i++) {
    spmv_csr(csr, d_x, d_y, &config, cols);
}

// After: Reuse texture across calls
SpMVExecutionContext context;
for (int i = 0; i < iterations; i++) {
    spmv_csr(csr, d_x, d_y, &config, cols, &context);
}

  3. Check error codes consistently:

    SpMVResult result = spmv_csr(csr, d_x, d_y, &config, cols);
if (result.error_code != static_cast<int>(SpMVError::SUCCESS)) {
    std::cerr << "Error: " << spmv_error_string(
        static_cast<SpMVError>(result.error_code)) << std::endl;
}

Future Roadmap

Planned for 1.1.0

  • COO (Coordinate) format support
  • Hybrid CSR/ELL format
  • Multi-GPU support
  • Batched SpMV operations
  • Double precision support

Under Consideration

  • BFloat16 precision support
  • Automatic format selection tuning
  • Integration with cuSPARSE for comparison
  • Python bindings