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View all- Chen JLiu LChen RPeng WHuang X(2021)SecRec: A Privacy-Preserving Method for the Context-Aware Recommendation SystemIEEE Transactions on Dependable and Secure Computing10.1109/TDSC.2021.3085562(1-1)Online publication date: 2021
Data Flow Transformation for Energy-Efficient Implementation of Givens Rotation--Based QRD
Authors: 
Namita Sharma, Preeti Ranjan Panda, Francky Catthoor, Min Li, Prashant AgrawalAuthors Info & Claims
Namita Sharma, Preeti Ranjan Panda, Francky Catthoor, Min Li, Prashant AgrawalAuthors Info & ClaimsArticle No.: 18, Pages 1 - 23
Abstract
QR decomposition (QRD), a matrix decomposition algorithm widely used in embedded application domain, can be realized in a large number of valid processing sequences that differ significantly in the number of memory accesses and computations, and hence the overall implementation energy. With modern low-power embedded processors evolving toward register files with wide memory interfaces and vector functional units (FUs), data flow in these algorithms needs to be carefully devised to efficiently utilize the costly wide memory accesses and the vector FUs. In this article, we present an energy-efficient data flow transformation strategy for the Givens rotation--based QRD.
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- Data Flow Transformation for Energy-Efficient Implementation of Givens Rotation--Based QRD
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Publication History
Published: 13 January 2016
Accepted: 01 October 2015
Revised: 01 July 2015
Received: 01 January 2015
Published in TECS Volume 15, Issue 1
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View all- Chen JLiu LChen RPeng WHuang X(2021)SecRec: A Privacy-Preserving Method for the Context-Aware Recommendation SystemIEEE Transactions on Dependable and Secure Computing10.1109/TDSC.2021.3085562(1-1)Online publication date: 2021
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