{"id":20433759,"url":"https://github.com/intelpython/numba-dpex","last_synced_at":"2025-12-11T21:03:36.116Z","repository":{"id":38440633,"uuid":"309665284","full_name":"IntelPython/numba-dpex","owner":"IntelPython","description":"Data Parallel Extension for Numba","archived":false,"fork":false,"pushed_at":"2024-11-18T06:37:52.000Z","size":40558,"stargazers_count":79,"open_issues_count":103,"forks_count":32,"subscribers_count":12,"default_branch":"main","last_synced_at":"2025-03-28T16:11:48.814Z","etag":null,"topics":["intel-xpu","numba","python","sycl"],"latest_commit_sha":null,"homepage":"https://intelpython.github.io/numba-dpex/","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/IntelPython.png","metadata":{"files":{"readme":"README.md","changelog":"CHANGELOG.md","contributing":"CONTRIBUTING.md","funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":".github/CODEOWNERS","security":"SECURITY.md","support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2020-11-03T11:30:02.000Z","updated_at":"2025-03-05T02:15:41.000Z","dependencies_parsed_at":"2024-02-08T23:38:54.258Z","dependency_job_id":"d054cdcb-24c9-442b-b7d1-1dcc21c16c13","html_url":"https://github.com/IntelPython/numba-dpex","commit_stats":null,"previous_names":[],"tags_count":91,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/IntelPython%2Fnumba-dpex","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/IntelPython%2Fnumba-dpex/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/IntelPython%2Fnumba-dpex/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/IntelPython%2Fnumba-dpex/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/IntelPython","download_url":"https://codeload.github.com/IntelPython/numba-dpex/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247217184,"owners_count":20903009,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["intel-xpu","numba","python","sycl"],"created_at":"2024-11-15T08:20:57.874Z","updated_at":"2025-12-11T21:03:36.051Z","avatar_url":"https://github.com/IntelPython.png","language":"Python","readme":"[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)\n[![Coverage Status](https://coveralls.io/repos/github/IntelPython/numba-dpex/badge.svg?branch=main)](https://coveralls.io/github/IntelPython/numba-dpex?branch=main)\n[![pre-commit](https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit\u0026logoColor=white)](https://github.com/pre-commit/pre-commit)\n[![Join the chat at https://matrix.to/#/#Data-Parallel-Python_community:gitter.im](https://badges.gitter.im/Join%20Chat.svg)](https://app.gitter.im/#/room/#Data-Parallel-Python_community:gitter.im)\n[![Coverity Scan Build Status](https://scan.coverity.com/projects/29068/badge.svg)](https://scan.coverity.com/projects/intelpython-numba-dpex)\n[![OpenSSF Scorecard](https://api.securityscorecards.dev/projects/github.com/IntelPython/numba-dpex/badge)](https://securityscorecards.dev/viewer/?uri=github.com/IntelPython/numba-dpex)\n\u003cimg align=\"left\" src=\"https://spec.oneapi.io/oneapi-logo-white-scaled.jpg\" alt=\"oneAPI logo\" width=\"75\"/\u003e\n\u003cbr/\u003e\n\u003cbr/\u003e\n\u003cbr/\u003e\n\u003cbr/\u003e\n\n\n\nData Parallel Extension for Numba* (numba-dpex) is an open-source standalone\nextension for the [Numba](http://numba.pydata.org) Python JIT compiler.\nNumba-dpex provides a [SYCL*](https://sycl.tech/)-like API for kernel\nprogramming Python. SYCL* is an open standard developed by the [Unified\nAcceleration Foundation](https://uxlfoundation.org/) as a vendor-agnostic way of\nprogramming different types of data-parallel hardware such as multi-core CPUs,\nGPUs, and FPGAs. Numba-dpex's kernel-programming API brings the same programming\nmodel and a similar API to Python. The API allows expressing portable\ndata-parallel kernels  in Python and then JIT compiling them for different\nhardware targets. JIT compilation is supported for hardware that use the\n[SPIR-V](https://www.khronos.org/spir/) intermediate representation format that\nincludes [OpenCL](https://www.khronos.org/opencl/) CPU (Intel, AMD) devices,\nOpenCL GPU (Intel integrated and discrete GPUs) devices, and [oneAPI Level\nZero](https://spec.oneapi.io/level-zero/latest/index.html) GPU (Intel integrated\nand discrete GPUs) devices.\n\nThe kernel programming API does not yet support every SYCL* feature. Refer to\nthe [SYCL* and numba-dpex feature comparison](https://intelpython.github.io/numba-dpex/latest/supported_sycl_features.html)\npage to get a summary of supported features.\nNumba-dpex only implements SYCL*'s kernel programming API, all SYCL runtime\nPython bindings are provided by the [dpctl](https://github.com/IntelPython/dpctl)\npackage.\n\nAlong with the kernel programming API, numba-dpex extends Numba's\nauto-parallelizer to bring device offload capabilities to `prange` loops and\nNumPy-like vector expressions. The offload functionality is supported via the\nNumPy drop-in replacement library: [dpnp](https://github.com/IntelPython/dpnp).\nNote that `dpnp` and NumPy-based expressions can be used together in the same\nfunction, with `dpnp` expressions getting offloaded by `numba-dpex` and NumPy\nexpressions getting parallelized by Numba.\n\nRefer the [documentation](https://intelpython.github.io/numba-dpex) and examples\nto learn more.\n\n# Getting Started\n\nNumba-dpex is part of the Intel\u0026reg; Distribution of Python (IDP) and Intel\u0026reg;\noneAPI AIKit, and can be installed along with oneAPI. Additionally, we support\ninstalling it from Anaconda cloud. Please refer the instructions\non our [documentation page](https://intelpython.github.io/numba-dpex/latest/getting_started.html)\nfor more details.\n\nOnce the package is installed, a good starting point is to run the examples in\nthe `numba_dpex/examples` directory. The test suite may also be invoked as\nfollows:\n\n```bash\npython -m pytest --pyargs numba_dpex.tests\n```\n\n## Conda\n\nTo install `numba_dpex` from the Intel(R) channel on Anaconda\ncloud, use the following command:\n\n```bash\nconda install numba-dpex -c conda-forge\n```\n\n## Pip\n\nThe `numba_dpex` can be installed using `pip` obtaining wheel packages either from PyPi.\n\n```bash\npython -m pip install numba-dpex\n```\n\n# Contributing\n\nPlease create an issue for feature requests and bug reports. You can also use\nthe GitHub Discussions feature for general questions.\n\nIf you want to chat with the developers, join the\n[#Data-Parallel-Python_community](https://app.gitter.im/#/room/#Data-Parallel-Python_community:gitter.im) room on Gitter.im.\n\nAlso refer our [CONTRIBUTING](https://github.com/IntelPython/numba-dpex/blob/main/CONTRIBUTING.md) page.\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fintelpython%2Fnumba-dpex","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fintelpython%2Fnumba-dpex","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fintelpython%2Fnumba-dpex/lists"}