onemkl-sycl-dft
Intel® oneAPI Math Kernel Library
Decision gist · record as of 2026-08-14
Yes, if you are developing performance-critical numerical code targeting Intel hardware and are comfortable with proprietary licensing and manual environment setup. The package is actively maintained, carries no known vulnerabilities, and is in the top PyPI packages by download volume. However, verify Python version compatibility first (unspecified in metadata) and review Intel's license terms, particularly if redistribution is planned.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- MKLROOT environment variable must be configured manually after installation; three Intel runtime libraries (dpcpp-cpp-rt, intel-opencl-rt, mkl) are required dependencies.
- Medium install friction due to three runtime dependencies (dpcpp-cpp-rt, intel-opencl-rt, mkl).
- Package is actively maintained with recent release.
License · maintenance · safety
(unclear) — Licensed under Intel Simplified Software License (proprietary, non-SPDX). License treatment is unclear, meaning you should review Intel's terms directly before integrating into your project, particularly if redistribution or commercial use is planned.
last release 2026-07-01 (44 days)
0 known vulnerabilities (OSV.dev, 2026-08-14) · 171,126 downloads/mo, #10,381 on PyPI
Alternatives
Verify before relying
pip install onemkl-sycl-dft
import onemkl_sycl_dft
# Requires MKLROOT environment variable to be set manually- Exact Python version compatibility (requires_python is unspecified in metadata)
- Whether MKLROOT setup is documented in the Intel developer documentation referenced
- Supported Intel GPU architectures and CPU generations beyond 'current and future'
What it is and what it does
onemkl-sycl-dft is Intel's oneAPI Math Kernel Library packaged for Python, exposing highly optimized mathematical routines through C and Data Parallel C++ interfaces. It targets developers building performance-critical numerical applications that need to leverage Intel CPUs and GPUs. The package bundles three runtime dependencies (dpcpp-cpp-rt, intel-opencl-rt, mkl) and requires manual configuration of the MKLROOT environment variable after installation—a setup step not handled automatically by PyPI.
The library is positioned for scientific computing, machine learning, and data analysis workloads where maximum performance on Intel hardware is a priority. It is actively maintained and carries a proprietary Intel license. Because the license treatment is unclear in the metadata, you should consult Intel's terms directly before committing to production use, especially if your project involves redistribution or commercial deployment.
Use it for
- Accelerate numerical simulations and scientific computations on Intel CPUs and GPUs
- Optimize linear algebra and Fourier transform operations in machine learning pipelines
- Build high-performance data analysis applications leveraging Intel's threaded math routines
- Develop heterogeneous compute applications using Data Parallel C++ on Intel hardware
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are developing performance-critical numerical code targeting Intel hardware and are comfortable with proprietary licensing and manual environment setup.
The package is actively maintained, carries no known vulnerabilities, and is in the top PyPI packages by download volume. However, verify Python version compatibility first (unspecified in metadata) and review Intel's license terms, particularly if redistribution is planned.
Install
onemkl-sycl-dft on PyPI
Before you install
Medium install friction due to three runtime dependencies (dpcpp-cpp-rt, intel-opencl-rt, mkl). Package is actively maintained with recent release. Note that MKLROOT environment variable requires manual setup post-installation and is not configured automatically by PyPI.
MKLROOT environment variable must be configured manually after installation; three Intel runtime libraries (dpcpp-cpp-rt, intel-opencl-rt, mkl) are required dependencies.
License in practice
Licensed under Intel Simplified Software License (proprietary, non-SPDX). License treatment is unclear, meaning you should review Intel's terms directly before integrating into your project, particularly if redistribution or commercial use is planned.
Quickstart
pip install onemkl-sycl-dft
import onemkl_sycl_dft
# Requires MKLROOT environment variable to be set manuallyVerify before relying
- Exact Python version compatibility (requires_python is unspecified in metadata)
- Whether MKLROOT setup is documented in the Intel developer documentation referenced
- Supported Intel GPU architectures and CPU generations beyond 'current and future'
Package facts
| License | Not declared unclear |
| Python support | Not specified |
| Install friction | Medium. Platform-specific wheel |
| Runtime dependencies | 3 packagesdpcpp-cpp-rtintel-opencl-rtmkl |
| Maintenance | Actively maintained 44 days since the last release |
| First released | |
| Downloads | 171,126 / month, #10,381 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableIntended Audience :: DevelopersIntended Audience :: EducationIntended Audience :: Other AudienceIntended Audience :: Science/ResearchIntended Audience :: System AdministratorsLicense :: Other/Proprietary LicenseOperating System :: POSIX :: LinuxTopic :: Software Development :: Libraries |
Evidence: onemkl_sycl_dft-2026.1.0-py2.py3-none-manylinux_2_28_x86_64.whl; onemkl_sycl_dft-2026.1.0-py2.py3-none-win_amd64.whl
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See also onemkl-sycl-rng · onemkl-license · onemkl-sycl-lapack · onemkl-sycl-blas · mkl-include · mkl-static · onemkl-sycl-sparse · daal · oneccl-devel · intel-sycl-rt