TY - GEN
T1 - Low-Latency High-Bandwidth Interconnection Networks by Selective Packet Compression
AU - Niwa, Naoya
AU - Amano, Hideharu
AU - Koibuchi, Michihiro
N1 - Funding Information:
ACKNOWLEDGEMENTS This work was supported by JSPS KAKENHI 19H01106 and JST SPRING, Grant Number JPMJSP2123.
Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - Interconnection network ideally transfers the maximum amount of communication dataset within the least amount of time to fully exploit the parallelism of target applications on parallel computer systems. To this goal, we propose a selective data-compression interconnection network. Data compression virtually increases the effective network bandwidth, while each compute node introduces additional latency overhead to perform (de-)compression operation to end-To-end communication latency. To minimize the effect of the compression latency overhead on the end-To-end communication latency, we selectively apply a compression technique to a packet. The compression operation is taken for long packets and is also taken when network congestion is detected at a network interface. Evaluation results show that simple lossless and lossy compression algorithms have up to 3.0 and 1.8 compression ratios for integer and floating-point communication data in some parallel applications, respectively, while the lossy compression algorithm successfully satisfies the required quality of results. Through a cycle-network simulation, the selective compression method using the above compression algorithms improves by up to 46% the network throughput with the moderate increase of the communication latency of short packets.
AB - Interconnection network ideally transfers the maximum amount of communication dataset within the least amount of time to fully exploit the parallelism of target applications on parallel computer systems. To this goal, we propose a selective data-compression interconnection network. Data compression virtually increases the effective network bandwidth, while each compute node introduces additional latency overhead to perform (de-)compression operation to end-To-end communication latency. To minimize the effect of the compression latency overhead on the end-To-end communication latency, we selectively apply a compression technique to a packet. The compression operation is taken for long packets and is also taken when network congestion is detected at a network interface. Evaluation results show that simple lossless and lossy compression algorithms have up to 3.0 and 1.8 compression ratios for integer and floating-point communication data in some parallel applications, respectively, while the lossy compression algorithm successfully satisfies the required quality of results. Through a cycle-network simulation, the selective compression method using the above compression algorithms improves by up to 46% the network throughput with the moderate increase of the communication latency of short packets.
KW - Congestion control
KW - Interconnection network
KW - Lossy data compression
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U2 - 10.1109/CANDAR53791.2021.00015
DO - 10.1109/CANDAR53791.2021.00015
M3 - Conference contribution
AN - SCOPUS:85124165797
T3 - Proceedings - 2021 9th International Symposium on Computing and Networking, CANDAR 2021
SP - 56
EP - 64
BT - Proceedings - 2021 9th International Symposium on Computing and Networking, CANDAR 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 9th International Symposium on Computing and Networking, CANDAR 2021
Y2 - 23 November 2021 through 26 November 2021
ER -