Heterogenous Parallel Programming Using oneAPI: A Virtual Workshop
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Overview
Heterogeneous computing is no longer the next wave of innovation. It's the “now” wave—the go-to computing foundation to solve science, industry, and societal challenges. Applications that fulfill these needs not only must be parallelized, they must be optimized for a diversity of hardware—CPUs, GPUs, FPGAs, and other accelerators.
So, how is it accomplished?
A lot rests on the use of software development tools—products purpose-built to help developers program compute-intense applications that take advantage of the hardware they are deployed on.
That is the focus of this on-demand workshop. Recently held as a live virtual event, it's now available to view at your convenience in its full two-hour format.
Watch Dr. Ellick Chan talk about heterogeneity in the context of Intel's oneAPI initiative. Here are the highlights of what he covers:
- The rise of parallelism and need for heterogeneous computing [11:05]
- An overview of oneAPI—the programming challenges it addresses, the toolkits, and Data Parallel C++ (DPC++) language, compiler, and compatibility tool [20:45]
- Unified shared memory for porting with minimal changes, including DPC++ demonstrations of buffers, accessors, and vector-add [43:30]
- Performance analysis and tuning tools, including Intel® VTune™ Profiler and Intel® Advisor, and a demonstration of Offload Advisor [1:00:25]
- A list of key resources and Intel opportunities, including oneAPI tools, code samples, and programs tailored to educators and students [1:10:45]
At time stamp 1:11:50, you can test your knowledge by playing oneAPI Jeopardy. Will you win money, fame, and glory? Nope. But you can prove (even to yourself) that you are the smartest developer in the room.
Finally, timestamp 1:27:50 marks the Q&A period with Dr. Chan and Intel senior principal engineer, Henry Gabb as they answer attendee questions.
Watch.
Get the Software
- Download the Intel® oneAPI Base Toolkit—the essential set of 15 software development tools and libraries including DPC++ language, compiler, and compatibility tool, Intel VTune Profiler, and Intel Advisor.
- Develop in the Cloud—Sign up for an Intel® Developer Cloud account, a free development sandbox with access to the latest Intel hardware and oneAPI software.
Dr. Ellick Chan
Head of university relations and research, Intel® AI Academy, Intel Corporation
Dr. Ellick Chan is passionate about bringing advanced computing technology to students. An instructor of deep learning at Northwestern University, Ellick brought his commitment to AI and heterogeneous programming education to Intel in 2018, leading university relations and research worldwide for the Intel AI Academy. His expertise spans operating systems, parallel, distributed, and GPU programming, and security. Additionally, he directs and advises on strategic technical engagements with university spinouts and key emerging AI independent software vendors (ISVs). Ellick holds three computer science degrees and an MBA from the University of Illinois.
Henry Gabb, PhD
Senior principal engineer, Intel Corporation
Henry is part of the Intel Software and Services Group, Developer Products Division, and is the editor of The Parallel Universe, Intel’s quarterly magazine for software innovation. He first joined Intel in 2000 to help drive parallel computing inside and outside the company. He transferred to Intel Labs in 2010 to become the program manager for various research programs in academia, including the Universal Parallel Computing Research Centers at the University of California at Berkeley and the University of Illinois at Urbana-Champaign. Prior to joining Intel, Henry was director of scientific computing at the US Army Engineer Research and Development Center MSRC, a Department of Defense high-performance computing facility. Henry holds a BS in biochemistry from Louisiana State University, an MS in medical informatics from the Northwestern Feinberg School of Medicine, and a PhD in molecular genetics from the University of Alabama at Birmingham School of Medicine. He has published extensively in computational life science and high-performance computing. Henry recently rejoined Intel after spending four years working on a second PhD in information science at the University of Illinois at Urbana-Champaign, where he established an expertise in applied informatics and machine learning for problems in healthcare and chemical exposure.
Develop high-performance, data-centric applications for CPUs, GPUs, and FPGAs with this core set of tools, libraries, and frameworks including LLVM*-based compilers.
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