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How to Rev Up Parallel Algorithms and Many-Core Architectures?

Discover the evolution of parallel processing and many-core architectures since 2005. Explore successes, failures, and the quest for killer applications. Uncover the challenges and possibilities with off-the-shelf or research-stage architectures. Join the discussion on potential killer apps.

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How to Rev Up Parallel Algorithms and Many-Core Architectures?

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  1. How to Rev Up Parallel Algorithms and Many-Core Architectures? Uzi Vishkin

  2. State of the Art - Since ~2005 parallel processing is the only way for improving performance of an application. "We are dedicating all of our future product development to multicore designs“-- Paul Otellini, CEO, Intel, 2005. - In 2005: Intel expected coupling 1000 cores on-chip by 2015. - But, where are we in 2019? General success stories • iGPUs (Intel’s integrated GPU) • Dedicated GPUs (NVIDIA) Deprecated after major investment since 2005 • Many-Integrated-Core, known as MIC or Xeon Phi (Intel) So revving up is important and timely

  3. Possible Explanation What went right? • Computer graphics is a much needed application in the general-purpose CPU space. Hence: iGPU • Deep learning has become a “killer app” for dedicated GPUs What went wrong • MIC failed to grow killer apps • Possibly because the architecture made it too challenging to develop apps for it; i.e., it was too difficult to program effectively the architecture

  4. Conclusion • Research question: develop a killer-app for a many-core architecture • The architecture can be • An off-the-shelf one, or • A research-stage one such as the UMD XMT architecture that my team developed. See http://users.umiacs.umd.edu/~vishkin/XMT/index.shtml • This is much more challenging than meets the eye • I can discuss with you candidate killer apps, but will also be glad to hear your suggestions

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