Jaffery Watson Mendonsa & Hamilton LLP
Compute optimizations for low precision machine learning operations
One embodiment provides an accelerator module comprising a memory stack including multiple memory dies; a graphics processing unit (GPU) coupled with the memory stack via one or more memory controllers, the GPU including a plurality of multiprocessors having a single instruction, multiple thread (SIMT) architecture, the multiprocessors to execute at least one single instruction. The at least one single instruction is to cause at least a portion of the GPU to perform a floating point operation on input having differing precisions. The floating point operation is a two-dimensional matrix multiply and accumulate operation.
Intel Corporation
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Sara S. Linda L. Anbang Xiaoming John C. Kevin Elmoustapha Michael S. Mike B. Dukhwan Barath Liwei Altug Abhishek R. Joydeep Ben J. Ping T.
Baghsorkhi Hurd Yao Chen Weast Nealis Ould-Ahmed-Vall Strickland Macpherson Kim Lakshmanan Ma Koker Appu Ray Ashbaugh Tang