Title
Advancing DSP into HPC, AI, and beyond: challenges, mechanisms, and future directions
Abstract
Digital Signal Processors (DSPs) have been widely used in embedded domains, delivering high performance with ultra-low power consumption. Such promises make it attractive for more domains that DSP was not an option before. To show how DSP lives up to these promises, we review two milestone DSPs: FT-Matrix and FT-Matrix2, which are designed by National University of Defense Technology with the purpose of advancing DSPs into the era of higher performance computing, AI, and even beyond. We demonstrate that the key challenges lie in the orchestration of huge computation resources and efficient data supply sub-system design. We show the key mechanisms in both FT-Matrix and FT-Matrix2 targeting these challenges, and also come up with possible future directions for enabling DSPs for a wider scope of applications.
Year
DOI
Venue
2021
10.1007/s42514-020-00057-2
CCF TRANSACTIONS ON HIGH PERFORMANCE COMPUTING
Keywords
DocType
Volume
SIMD, DSP, VLIW, AI, HPC
Journal
3
Issue
ISSN
Citations 
1
2524-4922
1
PageRank 
References 
Authors
0.36
0
8
Name
Order
Citations
PageRank
Yaohua Wang14414.23
Chen Li2112.58
Chang Liu310.36
Sheng Liu474.06
Yuanwu Lei510714.28
Jian Zhang610.36
Yang Zhang711.03
Yang Guo86732.72