Introducing Additional oneAPI Open Source Math Library Interfaces
Drive Math-based Application Optimization with oneMKL
Today, as part of the oneAPI industry initiative, we released a third in a family of open source math interfaces. The goal of open-sourcing the oneAPI Math Kernel Library (oneMKL) interface is to address the lack of an industry-standard interface and provide a single, cross-architecture API for CPUs and accelerators. The oneMKL open source interface lets developers use a single DPC++-based API across multiple CPU and accelerator architectures. Until recently, developers have used multiple libraries, which increased the complexity of their code base and lengthened their development cycle.
oneMKL Solves Key Customer Challenges with a Variety of Domains
The oneMKL APIs can be combined with math libraries that target a range of CPU hardware and other accelerator architectures. For example, the oneMKL open source interface provides a path to run AMD and NVIDIA libraries on Intel CPUs, GPUs and other accelerators. In other words, oneMKL APIs have a common front-end with a hardware-specific backend.
oneMKL is an important part of the oneAPI specification, and offers essential math library interfaces for:
- Dense linear algebra
- Sparse linear algebra
- Random number generators
- Discrete Fourier transforms
- Vector math
- Summary statistics
oneMKL LAPACK (Linear Algebra PACKage) includes functionality for solving systems of linear equations and linear least squares, eigenvalue problems, and singular value decomposition. Developers use oneMKL LAPACK in high-performance computing, numerical simulations, artificial intelligence, machine learning, and many other scientific computing applications. The oneMKL LAPACK open source interface greatly expands the coverage of common math functions.
The oneMKL open source interfaces currently support the dense linear algebra BLAS and LAPACK domains, as well as the RNG domain.. LAPACK open source interfaces, with support for the Intel® oneAPI Math Kernel Library on Intel CPU and Intel GPU backends, are now available for download. We encourage oneAPI partners to utilize the new interfaces to support additional cross-architecture hardware devices. In future development, additional open source interfaces may be added for other domains. The oneAPI specification supports cross-architecture programming, extending developer programming models to enable a diverse set of hardware through language, a set of library APIs, and a low-level hardware interface. To promote compatibility and enable developer productivity and innovation, the oneAPI specification builds on industry standards and provides an open, cross-platform developer stack.
Address the data deluge and get number-crunching today with oneMKL for heterogeneous hardware. Join us to enable new hardware and extend math interfaces to other math domains:
- Download the oneMKL open source interface supports the BLAS, RNG & LAPACK domains
- Watch oneMKL webinar #1 about Developing in a heterogeneous environment
- Watch oneMKL webinar #2 about GPU support for Linear Algebra, Sparse Matrices and RNGs
- Read how Lawrence Berkley National Labs implemented the RNG interface for Nvidia GPUs
- Learn more
oneAPI is a cross-industry, open, standards-based, unified programming model that delivers a common developer experience across accelerator architectures—for faster application performance, more productivity, and greater innovation. The oneAPI industry initiative encourages collaboration on the oneAPI specification and compatible oneAPI implementations across the ecosystem.