Optimizing the data placement and transformation for multi‐bank CGRA computing system
Zhongyuan Zhao1, Yantao Liu1, Weiguang Sheng1,a, Tushar Krishna2, Qin Wang1 and Zhigang Mao1
1Department of Micro/NaNo Electronics, Shanghai Jiao Tong University, Shanghai, China
awgshenghit@sjtu.edu.cn
2School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia
ABSTRACT
This paper provides a data placement optimization approach for Coarse‐Grained Reconfigurable Architecture (CGRA) based computing platform in order to simultaneously optimize the performance of CGRA execution and data transformation between main memory and multi‐bank memory. To achieve this goal, we have developed a performance model to evaluate the efficiency of data transformation and CGRA execution. This model is used for comparing the performances difference when using different data placement strategies. We search for the optimal data placement method by firstly choosing the method which generates the best CGRA execution efficiency from the candidates who can generate the optimal data transformation efficiency. Then we choose the best data placement strategy by comparing the performance of the selected strategy with the one generated through existing multi‐bank optimization algorithm. Evaluation shows our approach is capable of optimizing the performance to 2.76x of state‐of‐the‐art method when considering both data‐transformation and CGRA execution efficiency.
Keywords: CGRA, Data placement optimization, Multibank memory.
