Adjoint computation and Backpropagation
Abstract
In this talk Dr Pallez will discuss the impact of memory in the computation of automatic differentiation or for the backpropagation step of machine learning algorithms. He will show different strategies based on the amount of memory available. In particular he will discuss optimal strategies when one can reuse memory slots, and when considering a hierarchical memory platform
Origin | Files produced by the author(s) |
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