公开(公告)号：US10997492B2

公开(公告)日：2021-05-04

申请号：US15838273

申请日：2017-12-11

Applicant: NVIDIA Corporation

Inventor： Szymon Migacz ,  Hao Wu ,  Dilip Sequeira ,  Ujval Kapasi ,  Maxim Milakov ,  Slawomir Kierat ,  Zacky Zhou ,  Yilin Zhang ,  Alex Fit-Florea

IPC: G06N3/04 ,  G06N3/08 ,  G06N3/063 ,  G06N3/02 ,  G06N3/10 ,  G06N7/00 ,  G06T9/00

Abstract: Aspects of the present invention are directed to computer-implemented techniques for performing data compression and conversion between data formats of varying degrees of precision, and more particularly for improving the inferencing (application) of artificial neural networks using a reduced precision (e.g., INT8) data format. Embodiments of the present invention generate candidate conversions of data output, then employ a relative measure of quality to identify the candidate conversion with the greatest accuracy (i.e., least divergence from the original higher precision values). The representation can be then be used during inference to perform computations on the resulting output data.

公开(公告)号：US20210256348A1

公开(公告)日：2021-08-19

申请号：US17306171

申请日：2021-05-03

Applicant: NVIDIA Corporation

Inventor： Szymon Migacz ,  Hao Wu ,  Dilip Sequeira ,  Ujval Kapasi ,  Maxim Milakov ,  Slawomir Kierat ,  Zacky Zhou ,  Yilin Zhang ,  Alex Fit-Florea

IPC: G06N3/04 ,  G06N3/08

Abstract: Aspects of the present invention are directed to computer-implemented techniques for performing data compression and conversion between data formats of varying degrees of precision, and more particularly for improving the inferencing (application) of artificial neural networks using a reduced precision (e.g., INT8) data format. Embodiments of the present invention generate candidate conversions of data output, then employ a relative measure of quality to identify the candidate conversion with the greatest accuracy (i.e., least divergence from the original higher precision values). The representation can be then be used during inference to perform computations on the resulting output data.

公开(公告)号：US20220188608A1

公开(公告)日：2022-06-16

申请号：US17122598

申请日：2020-12-15

Applicant: NVIDIA Corporation

Inventor： Gregory Heinrich ,  Maxim Milakov ,  Xin Tong ,  Yue Wu

IPC: G06N3/063 ,  G06N5/04 ,  G06F12/0893

Abstract: Apparatuses, systems, and techniques to cache and reuse data for a neural network. In at least one embodiment, data generated by one or more layers of a neural network is cached and reused by the neural network.

公开(公告)号：US20180211152A1

公开(公告)日：2018-07-26

申请号：US15838273

申请日：2017-12-11

Applicant: NVIDIA Corporation

Inventor： Szymon Migacz ,  Hao Wu ,  Dilip Sequeira ,  Ujval Kapasi ,  Maxim Milakov ,  Slawomir Kierat ,  Zacky Zhou ,  Yilin Zhang ,  Alex Fit-Florea

IPC: G06N3/04 ,  G06N3/08

CPC classification number: G06N3/04 ,  G06N3/0454 ,  G06N3/08 ,  G06N7/00

Abstract: Aspects of the present invention are directed to computer-implemented techniques for performing data compression and conversion between data formats of varying degrees of precision, and more particularly for improving the inferencing (application) of artificial neural networks using a reduced precision (e.g., INT8) data format. Embodiments of the present invention generate candidate conversions of data output, then employ a relative measure of quality to identify the candidate conversion with the greatest accuracy (i.e., least divergence from the original higher precision values). The representation can be then be used during inference to perform computations on the resulting output data.