Tensor Algebra in Rust

Note: This is a personal project collaboration between @showmyth and @IrregularPersona

A foundational library for performing basic algebraic operations on N-dimensional numerical data structures (Arrays, Matrices, and Tensors) in Rust.

Overview

Tensor Algebra provides efficient implementations for working with:

• Vectors (1D arrays)
• Matrices (2D arrays)
• Tensors (N-dimensional arrays)

All operations are aimed to be fast and safe whilst using Rust's powerful type system.

Features

Current

• Generic Numeric Types: Full support for i32/64, u32/64, f32/64
• Type Safety
• Zero-Copy Operations: Efficient memory usage through references and views
• Seamless integration with Rust's Iterator ecosystem

Upcoming

• Basic Arithmetic: Element-wise addition, subtraction, multiplication, and division
• Scalar Operations: Broadcasting scalar values across tensors
• Linear Algebra: Matrix multiplication, transpose, determinant, and inverse operations
• Advanced Operations: Dot products, cross products, and norm calculations

Quick Start

Installation

Add this to your Cargo.toml:

[dependencies]
tensor-algebra = "0.1.0"

Performance

This library is designed with performance in mind:

• Zero-cost abstractions
• Minimal allocations
• Cache-friendly memory layouts

Development Status

This project is in active development. Current focus areas:

• Core tensor data structures
• Basic arithmetic operations
• Linear algebra foundations
• Comprehensive test suite
• Documentation and examples

Contributing

Status: Pull requests are currently closed while we establish the core architecture.

We welcome contributions! Once we open contributions, please:

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Make your changes with tests
4. Ensure all tests pass (cargo test)
5. Update documentation as needed
6. Submit a pull request

Development Setup

# Clone the repository
git clone https://github.com/showmyth/Tensor-Algebra-in-Rust.git
cd Tensor-Algebra-in-Rust

# Run tests
cargo test

# Run benchmarks
cargo bench

# Generate documentation
cargo doc --open

Architecture

The library is structured around three core abstractions:

• Tensor<T, const N: usize>: N-dimensional arrays with compile-time dimension checking
• Matrix<T>: Specialized 2D operations with linear algebra support
• Vector<T>: 1D operations with vector space operations

Examples

Check out the examples/ directory for comprehensive usage examples:

• arrays_basics.rs
• matmul_basics.rs
• matrices_basics.rs

Documentation

Coming soon!

Roadmap

Version 0.0.0 (Current)

• Basic data structures
• Memory layout optimization
• Type system foundation

Version 0.1.0

• Arithmetic operations
• Basic linear algebra
• Comprehensive benchmarks

License(s)

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

• Inspired by NumPy and similar tensor libraries
• Built using Rust's powerful type system
• Thanks to the Rust community for excellent documentation and tools

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Stay tuned for upcoming announcements! 👀

For questions or suggestions, feel free to open an issue or reach out to the maintainers.