TY - GEN
T1 - Real chip evaluation of a low power CGRA with optimized application mapping
AU - Kojima, Takuya
AU - Ando, Naoki
AU - Matshushita, Yusuke
AU - Okuhara, Hayate
AU - Doan, Ng Anh Vu
AU - Amano, Hideharu
N1 - Publisher Copyright:
© Association for Computing Machinery. All rights reserved.
PY - 2018/6/20
Y1 - 2018/6/20
N2 - Even though many optimization methods for CGRAs (Coarse-Grained Reconfigurable Architectures) have been proposed, aggressive power optimization still remains a complex problem to be solved. Moreover, the developments of these methods have mainly been proven on the basis of simulations. Therefore, the questions remains whether they can be applied for a real chip. Here, we consider a real implemented low power CGRA called CCSOTB2, and explore the possibility of the power reduction for this design. This paper proposes to use a metaheuristic method to optimize the power while considering all configurable factors of the CGRA, especially the mapping of an application. This methodology can generate mappings with their related pipeline structure and body bias control automatically. Optimized configurations to use on the real chip are obtained with this methodology and allow to measure the power consumption. The experimental results show a power reduction of 14.2% in average, when compared to a previously-used mapping method which cannot consider body bias and pipeline structure. In addition, the proposed method enables users to select a mapping from various solutions depending on performance requirement and trade-off possibilities (e.g. throughput vs power consumption).
AB - Even though many optimization methods for CGRAs (Coarse-Grained Reconfigurable Architectures) have been proposed, aggressive power optimization still remains a complex problem to be solved. Moreover, the developments of these methods have mainly been proven on the basis of simulations. Therefore, the questions remains whether they can be applied for a real chip. Here, we consider a real implemented low power CGRA called CCSOTB2, and explore the possibility of the power reduction for this design. This paper proposes to use a metaheuristic method to optimize the power while considering all configurable factors of the CGRA, especially the mapping of an application. This methodology can generate mappings with their related pipeline structure and body bias control automatically. Optimized configurations to use on the real chip are obtained with this methodology and allow to measure the power consumption. The experimental results show a power reduction of 14.2% in average, when compared to a previously-used mapping method which cannot consider body bias and pipeline structure. In addition, the proposed method enables users to select a mapping from various solutions depending on performance requirement and trade-off possibilities (e.g. throughput vs power consumption).
UR - http://www.scopus.com/inward/record.url?scp=85056622273&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85056622273&partnerID=8YFLogxK
U2 - 10.1145/3241793.3241806
DO - 10.1145/3241793.3241806
M3 - Conference contribution
AN - SCOPUS:85056622273
T3 - ACM International Conference Proceeding Series
BT - Proceedings of the 9th International Symposium on Highly-Efficient Accelerators and Reconfigurable Technologies, HEART 2018
PB - Association for Computing Machinery
T2 - 9th International Symposium on Highly-Efficient Accelerators and Reconfigurable Technologies, HEART 2018
Y2 - 20 June 2018 through 22 June 2018
ER -