[Feb 7 Webinar] Programming Python Beyond the CPU

Achieve high-performance gains on data parallel devices like GPUs.

[Time zone converter] [Available On-Demand on Thursday, February 8] Learn how to offload Python data and workloads to GPUs and other accelerators with minimal code effort using Data Parallel Extensions for Python, which extend numerical Python capabilities beyond CPUs. You'll learn how to: Use the Extensions for open-source heterogeneous computing and compilation Easily write SYCL kernels in Python Use JIT compilation in Python on any SYCL device for near-native performance Achieve data interoperability and scale via powerful drop-in replacements for NumPy and Numba Includes demonstrations showcasing the Extensions in action, including the speedups. Skill level: Intermediate Register now Featured software Download Data Parallel Extensions for Python [GitHub] Session demos will be done in the Intel® Developer Cloud. If you don't have an account, get an introductory one for free here Featured software Pairwise Distance: Open-Source XPU Programming with Data Parallel Extensions for Python See all code samples View in browser.

                                                           

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