TY - GEN
T1 - High performance and energy efficient wireless NoC-enabled multicore architectures for graph analytics
AU - Duraisamy, Karthi
AU - Lu, Hao
AU - Pande, Partha Pratim
AU - Kalyanaraman, Ananth
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/11/10
Y1 - 2015/11/10
N2 - With its applicability spanning numerous data-driven fields, the implementation of graph analytics on multicore platforms is gaining momentum. The most important component of a multicore chip is its communication backbone. Due to the inherent irregularities in data movements manifested by graph based applications, it is essential to design an efficient on-chip interconnect for multicore chips performing graph analytics. In this paper we present a detailed analysis of the traffic patterns generated by graph-based applications when mapped to multicore chips. Based on this analysis, we present the design of wireless Network-on-Chip (WiNoC)-enabled multicore platforms for efficient implementation of graph analytics. When compared to traditional wireline mesh architecture, WiNoC enables a faster data exchange among the computing cores, leading to reduced execution times and lower energy dissipation. We demonstrate that depending on the particular graph application, the WiNoC reduces the execution time up to 35% and lowers the energy dissipation up to 40% when compared to traditional wireline mesh.
AB - With its applicability spanning numerous data-driven fields, the implementation of graph analytics on multicore platforms is gaining momentum. The most important component of a multicore chip is its communication backbone. Due to the inherent irregularities in data movements manifested by graph based applications, it is essential to design an efficient on-chip interconnect for multicore chips performing graph analytics. In this paper we present a detailed analysis of the traffic patterns generated by graph-based applications when mapped to multicore chips. Based on this analysis, we present the design of wireless Network-on-Chip (WiNoC)-enabled multicore platforms for efficient implementation of graph analytics. When compared to traditional wireline mesh architecture, WiNoC enables a faster data exchange among the computing cores, leading to reduced execution times and lower energy dissipation. We demonstrate that depending on the particular graph application, the WiNoC reduces the execution time up to 35% and lowers the energy dissipation up to 40% when compared to traditional wireline mesh.
KW - Community detection
KW - Graph Analytics
KW - Graph coloring
KW - Network-on-Chip architectures
KW - Wireless NoCs
UR - http://www.scopus.com/inward/record.url?scp=84962268189&partnerID=8YFLogxK
U2 - 10.1109/CASES.2015.7324555
DO - 10.1109/CASES.2015.7324555
M3 - Conference contribution
AN - SCOPUS:84962268189
T3 - 2015 International Conference on Compilers, Architecture and Synthesis for Embedded Systems, CASES 2015
SP - 147
EP - 156
BT - 2015 International Conference on Compilers, Architecture and Synthesis for Embedded Systems, CASES 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - International Conference on Compilers, Architecture and Synthesis for Embedded Systems, CASES 2015
Y2 - 4 October 2015 through 9 October 2015
ER -