trueno 0.11.0

Multi-Target High-Performance Compute Library

trueno (Spanish: "thunder") provides unified compute primitives across CPU SIMD, GPU, and WebAssembly.

Features

• CPU SIMD: x86 (SSE2/AVX/AVX2/AVX-512), ARM (NEON), WASM (SIMD128)
• GPU: Vulkan/Metal/DX12/WebGPU via wgpu (matrix multiply only)
• Auto-dispatch: Runtime selection of optimal backend
• Zero unsafe in public API: Safety via type system

Installation

[dependencies]
trueno = "0.8"

# Optional: GPU support for large matrices
trueno = { version = "0.8", features = ["gpu"] }

Quick Start

use trueno::{Vector, Matrix, SymmetricEigen};

// Vector operations - auto-selects best SIMD backend
let a = Vector::from_slice(&[1.0, 2.0, 3.0, 4.0]);
let b = Vector::from_slice(&[5.0, 6.0, 7.0, 8.0]);

let sum = a.add(&b).unwrap();           // [6.0, 8.0, 10.0, 12.0]
let dot = a.dot(&b).unwrap();           // 70.0
let activated = a.relu().unwrap();      // ReLU activation

// Matrix operations
let m = Matrix::from_vec(2, 2, vec![1.0, 2.0, 3.0, 4.0]).unwrap();
let product = m.matmul(&m).unwrap();    // Matrix multiplication
let transposed = m.transpose();          // Transpose

// Batched matmul for transformers (Q @ K^T pattern)
let batch = 2; let heads = 4; let seq = 8; let dim = 64;
let q: Vec<f32> = vec![0.1; batch * heads * seq * dim];
let kt: Vec<f32> = vec![0.1; batch * heads * dim * seq];
let attn = Matrix::batched_matmul_4d(&q, &kt, batch, heads, seq, dim, seq).unwrap();

// Eigendecomposition (PCA, spectral analysis)
let cov = Matrix::from_vec(2, 2, vec![3.0, 1.0, 1.0, 3.0]).unwrap();
let eigen = SymmetricEigen::new(&cov).unwrap();
let eigenvalues = eigen.eigenvalues();  // [4.0, 2.0]

Performance

GPU Note: GPU acceleration benefits matrix multiply only. Element-wise operations use CPU SIMD (GPU transfer overhead exceeds compute time).

Operations

Vector: add, sub, mul, div, dot, sum, min, max, argmin, argmax, norm_l1, norm_l2, normalize

Activations: relu, leaky_relu, elu, sigmoid, tanh, gelu, swish, softmax, log_softmax

Matrix: matmul, batched_matmul, batched_matmul_4d, transpose, matvec, convolve2d

Statistics: mean, variance, stddev, covariance, correlation, zscore

Eigen: symmetric eigendecomposition (Jacobi algorithm)

Development

cargo test                  # Run tests
cargo bench                 # Run benchmarks
make coverage              # Coverage report (requires cargo-llvm-cov)

Ecosystem

Part of the Pragmatic AI Labs stack:

• trueno-gpu - Pure Rust PTX generation
• trueno-db - GPU-first analytics database
• trueno-graph - Graph algorithms
• trueno-rag - RAG pipeline

License

MIT - see LICENSE