---
id: onemkl-sycl-lapack
version: "2026.1.0"
license: Intel Simplified Software License
license_treatment: unclear
maintenance: active
---

# onemkl-sycl-lapack — Intel® oneAPI Math Kernel Library

License: unclear · Maintenance: active · Downloads: 171.2K/mo

## What it is and what it does

onemkl-sycl-lapack is Intel's oneAPI Math Kernel Library packaged for Python, exposing C and Data Parallel C++ (DPC++) interfaces to highly optimized linear algebra and mathematical routines. It targets applications requiring maximum performance on Intel hardware, supporting both current and future generations of Intel CPUs and GPUs through DPC++ parallelism.

The package is a thin wrapper around Intel's native libraries and requires manual environment configuration (MKLROOT) after installation. It is platform-specific, available only for Linux x86_64 and Windows x86_64, and depends on four runtime packages including mkl and onemkl-sycl-blas. Intended for developers, researchers, and system administrators building high-performance numerical applications.

Use it for:

- Accelerate linear algebra operations (BLAS, LAPACK) in scientific computing workflows on Intel hardware.
- Build DPC++ applications that dispatch compute to Intel GPUs while maintaining C/C++ compatibility.
- Optimize numerical simulations and data-parallel workloads on Intel CPUs with threaded MKL routines.
- Integrate Intel's math libraries into C/C++ applications via Python bindings for performance-critical sections.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Provides optimized C and Data Parallel C++ interfaces to Intel's oneAPI Math Kernel Library for high-performance linear algebra and mathematical computing on Intel CPUs and GPUs.

Yes, if you are developing on Intel hardware (Linux x86_64 or Windows x86_64) and need high-performance linear algebra or DPC++ GPU compute. The medium install friction and manual MKLROOT setup are acceptable trade-offs for Intel-optimized math routines. No known vulnerabilities. License is proprietary and unclear—verify Intel's terms for your use case before committing.

## Install

pip install onemkl-sycl-lapack
uv add onemkl-sycl-lapack
poetry add onemkl-sycl-lapack

## Installing onemkl-sycl-lapack

Before you install: Medium install friction due to four runtime dependencies (dpcpp-cpp-rt, intel-opencl-rt, mkl, onemkl-sycl-blas) and platform-specific wheels (Linux x86_64 and Windows only). Active maintenance with recent release.

License in practice: Licensed under Intel Simplified Software License (proprietary, not SPDX-identified). License treatment is unclear—review Intel's terms before use in commercial or redistributed contexts.

Quickstart:

pip install onemkl-sycl-lapack
# Then import and call C/DPC++ interfaces via ctypes or language bindings
# Requires setting MKLROOT environment variable manually per Intel documentation

MKLROOT environment variable must be configured manually after installation; Linux x86_64 or Windows x86_64 required; Intel runtime libraries (dpcpp-cpp-rt, intel-opencl-rt) must be present.

Verify before relying:

- Exact Python version compatibility (requires_python not specified in metadata)
- Whether MKLROOT setup is documented in the package or only in external Intel docs
- Performance benchmarks or typical use-case guidance for CPU vs. GPU dispatch

## Package facts

- License: Intel Simplified Software License (unclear)
- Python support: unspecified
- Install friction: medium
- Maintenance: active
- Downloads: 171.2K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

intel mkl lapack bindings, oneapi math kernel library, dpc++ linear algebra, optimized blas lapack, intel gpu compute library, intel-optimized, gpu-compute, numerical-computing

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