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Julia: Full-Stack GPU computing for AI

Setup Time:
30 minutes
Tuesday, March 27, 2018 at 6:00pm
Tuesday, March 27, 2018 at 9:00pm
Teardown Time:
15 minutes
Estimated size:

Learn how the Julia programming language can be used for GPU programming, both for (1) low-level kernel programming, and (2) high-level array and AI libraries. This full-stack support drastically simplifies code bases, and GPU programmers can take advantage of all of Julia's most powerful features: generic programming, n-dimensional kernels, higher order functions and custom numeric types. We'll give overview the compiler's implementation and performance characteristics via the Rodinia benchmark suite. We'll show how these techniques enable highly flexible AI libraries with state-of-the-art performance, and allow a major government user to run highly computational threat modelling on terabytes of data in real time.


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