Abstract
This study presents a selective data-compression interconnection network to boost its performance. Data compression virtually increases the effective network bandwidth. One drawback of data compression is a long latency to perform (de-)compression operation at a compute node. In terms of the communication latency, we explore the trade-off between the compression latency overhead and the reduced injection latency by shortening the packet length by compression algorithms. As a result, we present to selectively apply a compression technique to a packet. We perform a compression operation to long packets and it is also taken when network congestion is detected at a source compute node. Through a cycle-accurate network simulation, the selective compression method using the above compression algorithms improves by up to 39% the network throughput with a moderate increase in the communication latency of short packets.
Original language | English |
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Pages (from-to) | 2057-2065 |
Number of pages | 9 |
Journal | IEICE Transactions on Information and Systems |
Volume | E105D |
Issue number | 12 |
DOIs | |
Publication status | Published - 2022 Dec |
Keywords
- communication latency
- data compression
- interconnection networks
- parallel processing
ASJC Scopus subject areas
- Software
- Hardware and Architecture
- Computer Vision and Pattern Recognition
- Electrical and Electronic Engineering
- Artificial Intelligence