TY - GEN
T1 - Performance analysis of hardware-based numerical data compression on various data formats
AU - Ueno, Tomohiro
AU - Sano, Kentaro
AU - Furusawa, Takashi
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/7/19
Y1 - 2018/7/19
N2 - The amount of data processed in high-performance computing has been growing rapidly. Accordingly, the cost of data movement in a large-scale computing system further increases, which has a huge effect on computing performance. To reduce the data movement cost, we have proposed hardware-based data compression for numerical data streams that can greatly reduce overhead has been proposed. Although our proposed hardware compressor works well for scientific computation in previous studies, the compression performance heavily depends on a type of target data. For practical use, we need to know the characteristics of the data compression and the relationship between data types and compression performance. In this paper, we clarify difference in compression performance among different data types by investigating hardware-based compression performance for data types of double, single, and half-precision floating-point and ffixed-point with results of numerical simulation. We also propose an area-saving hardware design for double-precision floating-point data.
AB - The amount of data processed in high-performance computing has been growing rapidly. Accordingly, the cost of data movement in a large-scale computing system further increases, which has a huge effect on computing performance. To reduce the data movement cost, we have proposed hardware-based data compression for numerical data streams that can greatly reduce overhead has been proposed. Although our proposed hardware compressor works well for scientific computation in previous studies, the compression performance heavily depends on a type of target data. For practical use, we need to know the characteristics of the data compression and the relationship between data types and compression performance. In this paper, we clarify difference in compression performance among different data types by investigating hardware-based compression performance for data types of double, single, and half-precision floating-point and ffixed-point with results of numerical simulation. We also propose an area-saving hardware design for double-precision floating-point data.
KW - FPGA
KW - Floating Point
KW - Hardware
KW - Numerical Simulation
UR - http://www.scopus.com/inward/record.url?scp=85050996845&partnerID=8YFLogxK
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U2 - 10.1109/DCC.2018.00043
DO - 10.1109/DCC.2018.00043
M3 - Conference contribution
AN - SCOPUS:85050996845
T3 - Data Compression Conference Proceedings
SP - 345
EP - 354
BT - Proceedings - DCC 2018
A2 - Bilgin, Ali
A2 - Storer, James A.
A2 - Serra-Sagrista, Joan
A2 - Marcellin, Michael W.
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 Data Compression Conference, DCC 2018
Y2 - 27 March 2018 through 30 March 2018
ER -