Existing math kernel libraries have lacked portability across heterogeneous platforms—until now. A unifying programming model—and availability of standard library interfaces—enables development of performance-portable libraries among diverse hardware architectures. In this episode, Julia Sukharina, Senior Engineering Manager at Intel, and Mehdi Goli, Principal Software Engineer at Codeplay Software, talk about a collaborative project to make this portability possible, and Mehdi dives into his work to enable the first math library implementation for #oneAPI on Nvidia GPUs. Have a favorite library you want to enable, or want to contribute a proposal for a new math interface to drive standardization across multiple hardware?

To get started, visit:
github.com/oneAPI-SRC/oneMKL

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Tags: BLAS, C++, Codeplay Software, compute-intensive, CuBLAS, CUDA, Data Parallel C++, data-intensive, developers, DPC++, GPU, heterogeneous, Intel Math Kernel Library, Julia Sukharina, libraries, linear algebra, math, math libraries, Mehdi Goli, MKL, NVIDIA, oneMKL, OpenCL, SYCL
 
Posted in: Audio Podcast, Code Together, Intel