METHOD AND ARCHITECTURE FOR ACCELERATING DETERMINISTIC STOCHASTIC COMPUTING USING RESIDUE NUMBER SYSTEM
Patent №
US 12,307,352
Granted
2025-05-20
Filed 2021
Owner
University of Louisiana at Lafayette
Lab
—
AI components
0
Assignment
None on record
Dataset
AIPD
Application
17166378
Inaccuracy of computations is an important challenge with the Stochastic Computing (SC) paradigm. Recently, deterministic approaches to SC are proposed to produce completely accurate results with SC circuits. Instead of random bit-streams, the computations are performed on structured deterministic bit-streams. However, current deterministic methods take a large number of clock cycles to produce correct result. This long processing time directly translates to very high energy consumption. This invention proposes a design methodology based on the Residue Number Systems (RNS) to mitigate the long processing time of the deterministic methods. Compared to the state-of-the-art deterministic methods of SC, the proposed approach delivers improvements in terms of processing time and energy consumption.
Ownership
University of Louisiana at Lafayette