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Burn CPU Backend

Burn CubeCL CPU backend

This crate provides a CPU backend for Burn using CubeCL's CPU runtime. It JIT-compiles shared CubeCL kernels to native CPU code through LLVM, with kernel fusion and autotuning enabled by default. LLVM is bundled automatically, no system installation is required.

burn-cpu vs burn-flex

Burn has two independent CPU backends. Neither one is built on top of the other.

	`burn-cpu`	`burn-flex`
Implementation	CubeCL kernels compiled through LLVM	Hand-written Rust kernels, `gemm`, SIMD
Execution	JIT-compiled, with fusion and autotune	Eager
Native deps	Bundled LLVM, no system install	None (pure Rust)
`no_std` / Wasm	No	Yes
`burn` feature	`cpu`	`flex`
Device constructor	`Device::cpu()`	`Device::flex()`

Use burn-cpu when you want the CubeCL stack (fusion, custom CubeCL kernels shared with the GPU backends) on the CPU. Use burn-flex for a lightweight, portable CPU backend that also runs on no_std and WebAssembly targets.

burn-ndarray is the deprecated predecessor of burn-flex; it is not related to burn-cpu.

Usage Example

burn = { version = "0.22", features = ["cpu"] }

use burn::tensor::{Device, Tensor};

let device = Device::cpu();
let tensor = Tensor::<2>::from_data([[1.0, 2.0], [3.0, 4.0]], &device);

Part of the Burn deep learning framework. See the Burn Book and the API documentation.

burn-cpu 0.22.0

Burn CPU Backend

burn-cpu vs burn-flex

Usage Example