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Physical Sciences and Mathematics Commons™
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Full-Text Articles in Physical Sciences and Mathematics
Hardware Acceleration Of Inference Computing: The Numenta Htm Algorithm, Dan Hammerstrom
Hardware Acceleration Of Inference Computing: The Numenta Htm Algorithm, Dan Hammerstrom
Systems Science Friday Noon Seminar Series
In this presentation I will describe the latest version of the Numenta HTM Cortical Learning Algorithm and why it is interesting for doing research into radical new computer architectures. Then I will discuss the hardware acceleration research we are doing, and briefly look at some preliminary applications development.
Scalable Correct Memory Ordering Via Relativistic Programming, Josh Triplett, Philip William Howard, Paul E. Mckenney, Jonathan Walpole
Scalable Correct Memory Ordering Via Relativistic Programming, Josh Triplett, Philip William Howard, Paul E. Mckenney, Jonathan Walpole
Computer Science Faculty Publications and Presentations
We propose and document a new concurrent programming model, relativistic programming. This model allows readers to run concurrently with writers, without blocking or using expensive synchronization. Relativistic programming builds on existing synchronization primitives that allow writers to wait for current readers to finish with minimal reader overhead. Our methodology models data structures as graphs, and reader algorithms as traversals of these graphs; from this foundation we show how writers can implement arbitrarily strong ordering guarantees for the visibility of their writes, up to and including total ordering.