Implementierung von N:m-Sparsity in einem Beschleuniger der Digitalen Datenverarbeitung im Speicher

Details

Veröffentlichungs-Nr.

EP4745753

Anmeldetag

13. Oktober 2025

Veröffentlichung

20. Mai 2026

Rechtsraum

EP

IPC

G06F7/544(OVSIANNIKOV ILIA et al.)

Abstract

To support flexible N:M sparsity pattern in a DCiM macro, the DCiM macro is subdivided into multiple sub-macros according to a partitioning factor P. Each sub-macro can support 1:2 sparsity ratio. Leveraging the partitioned design, the sub-macros can be grouped together to support different N:M sparsity patterns. To determine optimal N:N sparsity pattern for each layer of a neural network, an algorithm can determine the value A of a sparsity ratio A/B is based on the number of outliers in a layer, and the value B of the sparsity ratio A/B is based on the locality measure of the outliers representing the spatial distribution of the outliers. Moreover, the optimal N:M sparsity pattern that is aligned with the determined sparsity ratio A/B can be selected based on whether to prioritize latency or accuracy, or to balance both latency and accuracy.

Anmelder

Firma

INTEL Corporation

Land

🇺🇸 USA