With the emergence of GPUs, xPUs (DPU, IPU, FAC, NAPU, etc) and computational storage devices for host offload and accelerated processing, a panoramic wild west of frameworks are emerging, consolidating and vying for the preferred programming software stack that best integrates the application layer with these underlying processing units.
This webcast will provide an overview of programming frameworks that support (1) GPUs (CUDA, SYCL, OpenCL, oneAPI), (2) xPUs (DASH, DOCA, OPI, IPDK), and (3) Computational Storage (SNIA computational storage API, NVMe TP4091 and FPGA programming shells).
We will discuss strengths and challenges and market adoption across these programming frameworks as we untangle the alphabet soup of new frameworks that include:
• AI/ML: OpenCL, CUDA, SYCL, oneAPI
• xPU: DOCA, OPI, DASH, IPDK
• Core data path frameworks: SPDK, DPDK
• Computational Storage: SNIA Standard 0.8 (in public review), TP4091
Presented by John Kim, NVIDIA; James Reinders, Intel; Joseph White, Dell; Benjamin Walker, Intel; David McIntyre, Samsung; Alex McDonald, Independent Consultant
After watching, check out the Q&A blog at https://bit.ly/FrameworksQABlog
Learn More:
SNIA Website: https://snia.org/
SNIA Educational Library: https://snia.org/library
Twitter: https://twitter.com/SNIA
LinkedIn: https://linkedin.com/company/snia/
