# plaidml/plaidml

PlaidML is a framework for making deep learning work everywhere.

Repository: https://github.com/plaidml/plaidml
Canonical: https://ross.abutalabs.com/products/plaidml
Homepage: https://ai.intel.com/plaidml
Language: C++
License: Apache-2.0
License Family: permissive
Archived: true
Last push: 2023-07-23T20:16:29+00:00

## Health v2 (maintenance only)
Score: 10/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 3306, "days_push": 1137, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: archived
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 4566, forks 398 (observed 2026-08-28T04:08:53.517616+00:00)

## What it is
PlaidML is a portable tensor compiler that enables deep learning on hardware (especially GPUs and embedded devices) not well supported by mainstream stacks. It sits underneath frameworks like Keras, ONNX, and nGraph, compiling tensor operations via an MLIR-based compiler stack.

## Use cases
- run deep learning training on AMD GPUs without CUDA
- train Keras models on unsupported hardware
- compile tensor operations for embedded devices
- use deep learning on laptops without vendor-specific ML libraries
- avoid restrictive licensing in GPU ML software stacks

## When to choose
- your GPU or device lacks support from TensorFlow or PyTorch
- you need a portable backend for Keras or ONNX models
- you want an open, permissively licensed tensor compiler

## When to avoid
- you need cutting-edge performance on NVIDIA hardware with CUDA available
- you require actively maintained software - the master branch is frozen and v1 is a research project
- you need support for the latest hardware targets or production stability

## Facets
- artifact type: library
- maturity: maintenance
- function: deep-learning, compiler, machine-learning, gpu-computing
- domain: deep-learning, machine-learning, compilers, gpu-computing
- platform: cross-platform, windows, python, cpp
- tags: tensor-compiler, keras-backend, onnx, mlir, opencl, portable-deep-learning, linux, macos

## Member repositories
- plaidml/plaidml (main) score 10

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:53.517616+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T18:19:58.871986+00:00, confidence not recorded.
  - readme: https://github.com/plaidml/plaidml (fetched 2026-08-28T04:08:53.517616+00:00, sha 1cff7df5886d)
- Data as of 2026-08-30T08:39:29.467469+00:00.