Task synchronization for accelerated deep learning
AssigneeCerebras Systems Inc.
InventorsSean Lie, Michael Morrison, Srikanth Arekapudi, Michael Edwin James, Gary R. Lauterbach
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AssigneeCerebras Systems Inc.
InventorsSean Lie, Michael Morrison, Srikanth Arekapudi, Michael Edwin James, Gary R. Lauterbach
Estimating the term…
Techniques in advanced deep learning provide improvements in one or more of accuracy, performance, and energy efficiency. An array of processing elements performs flow-based computations on wavelets of data. Each processing element has a compute element and a routing element. Each compute element has memory. Each router enables communication via wavelets with at least nearest neighbors in a 2D mesh. Routing is controlled by respective virtual channel specifiers in each wavelet and routing configuration information in each router. A compute element conditionally selects for task initiation a previously received wavelet specifying a particular one of the virtual channels. The conditional selecting excludes the previously received wavelet for selection until at least block/unblock state maintained for the particular virtual channel is in an unblock state. The compute element executes block/unblock instructions to modify the block/unblock state.
A method comprising:
An apparatus comprising:
A method comprising:
Dependencies are inferred from the claim text.