iree-org/iree
A retargetable MLIR-based machine learning compiler and runtime toolkit.
What it solves
IREE simplifies the deployment of machine learning models across a wide variety of hardware. It addresses the challenge of scaling ML models to work efficiently on everything from massive data centers to resource-constrained mobile and edge devices.
How it works
IREE is an end-to-end compiler and runtime based on MLIR (Multi-Level Intermediate Representation). It works by lowering ML models into a unified intermediate representation (IR) that can then be optimized and executed on diverse hardware targets.
Who it’s for
It is designed for developers and engineers who need to deploy ML models to diverse hardware environments, including data centers, mobile devices, and edge deployments.
Highlights
- MLIR-based compiler and runtime architecture.
- Unified IR for cross-platform deployment.
- Supports scaling from data center scale to mobile and edge constraints.
- Part of the LF AI & Data Foundation.
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