DYNAMIC ROUTING FOR ACCELERATED DEEP LEARNING
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United States of America
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Issued Date -
Mar 6, 2025
app pub date -
Nov 12, 2024
filing date -
Nov 12, 2024
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Abstract
Techniques in dynamic routing for advanced deep learning provide improvements in one or more of accuracy, performance, and energy efficiency. An array of processing elements comprising a portion of a neural network accelerator performs flow-based computations on wavelets of data. Each processing element comprises a compute element enabled to execute programmed instructions using the data and a router enabled to route the wavelets via static routing, dynamic routing, or both. The routing is in accordance with a respective virtual channel specifier of each of the wavelets and controlled by routing configuration information of the router. The static techniques enable statically specifiable neuron connections. The dynamic techniques enable information from the wavelets to alter the routing configuration information during neural network processing.
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