Changelog#

This project adheres to Keep a Changelog and Semantic Versioning.

v0.2.0#

  • Added

    • CSC/COO Python classes and bindings parity with CSR (Csc64, Coo64).

    • Format conversions exposed via Python: CSR<->CSC, CSR<->COO, CSC<->COO.

    • ND COO baseline:

      • Kernels in lacuna-kernels: sum_coond_f64, permute_axes_coond_f64_i64, reduce_sum_axes_coond_f64_i64, spmv_coond_f64_i64, spmm_coond_f64_i64.

      • ND→2D conversions: coond_mode_to_{csr,csc}_f64_i64, coond_axes_to_{csr,csc}_f64_i64.

    • PyO3 exports for ND wrappers in lacuna-py (coond_*_from_parts).

    • High-level Python COOND class in lacuna.sparse; added python/tests/test_nd.py.

    • ND COO new ops:

      • Mean: mean_coond_f64; Axis-wise mean: reduce_mean_axes_coond_f64_i64.

      • Reshape: reshape_coond_f64_i64.

      • Broadcasted Hadamard product: hadamard_broadcast_coond_f64_i64.

    • PyO3 exports for new ND ops:

      • coond_mean_from_parts, coond_reduce_mean_axes_from_parts, coond_reshape_from_parts, coond_hadamard_broadcast_from_parts.

    • Python COOND methods: mean, reduce_mean_axes, reshape, hadamard_broadcast.

    • Python tests: added coverage for the above ND ops in python/tests/test_nd.py.

  • Changed

    • Split monolithic lacuna-py/src/lib.rs into modules: csr.rs, csc.rs, coo.rs, functions.rs.

      • No Python API changes; lib.rs now only aggregates and registers symbols.

    • Centralized kernel utilities in lacuna-kernels/src/util.rs (constants, helpers, UsizeF64Map).

    • Benchmarks now import lacuna only from the installed environment (removed local sys.path injection).

  • Performance

    • Replaced HashMap-based sparse accumulators with a custom linear-probing UsizeF64Map in reduce.rs and spmv.rs.

    • Parallelized small-dimension reduction paths; SIMD-accelerated stripe merge in column-sum kernels.

    • Parallel linearization in coond_axes_to_coo_f64_i64 using slice access + unchecked indexing to reduce overhead.

    • Parallel index normalization/accumulation in ND broadcasted Hadamard and parallel linearize/delinearize in ND reshape.

  • Fixed

    • Balanced unmatched braces in reduce.rs causing “unclosed delimiter” compile errors; added missing closers.

    • Fixed Rayon Sync error in convert.rs by avoiding capturing raw pointers in parallel closures (use slice + get_unchecked).

    • Fixed i64_to_usize missing brace in arith.rs.

    • Resolved E0596 borrow errors in parallel closures in arith.rs and transform.rs by using raw pointer writes for disjoint parallel writes.

    • Removed stray closing brace in arith.rs.

    • Corrected product_checked to return the accumulator and moved mean_coond_f64/reduce_mean_axes_coond_f64_i64 to top-level scope in reduce.rs.

v0.1.0#

  • Added

    • Core CSR sparse matrix type with f64 values and i64 indices.

    • Python bindings via PyO3; development builds via maturin develop.

    • Core operations (CSR basics):

      • Shape/nnz/meta, transpose, dtype/index casting.

      • Reductions: global sum, row/column sums.

      • Element access (A[i, j] read) and row/column slicing.

      • Arithmetic: A @ x (SpMV), A @ B_dense (SpMM), A + B, A - B, Hadamard A.multiply(B), scalar ops.

      • Cleanup utilities: eliminate_zeros, prune(eps).

    • High-performance kernels (rayon parallelism + std::simd) for f64/i64 in lacuna-kernels.

    • Repository structure with lacuna-core, lacuna-kernels, lacuna-io, lacuna-py, and Python package lacun.

    • Tests: Rust unit tests and Python pytest suite; basic benchmark scripts.

  • Packaging

    • Build and install with maturin; Python 3.10–3.13.

    • Windows, Linux (manylinux), and macOS targets in plan; wheel scripts provided.

  • Documentation

    • Initial developer guide and project overview.

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