A MapReduce scratchpad memory for multi-core cloud computing applications
Phoenix MapReduce is a multi-core programming framework that is used to automatically parallelize and schedule programs. This paper presents a novel scratchpad memory architecture that is used accelerate MapReduce applications by indexing and processing the key/value pairs. The proposed scratchpad memory scheme can be mapped onto programmable logic or multi-core processors chips as a coprocessor to accelerate MapReduce applications. The proposed architecture has been implemented in a Zynq FPGA with two embedded ARM cores. The performance evaluation shows that the proposed scheme can reduce up to 2.3  the execution time and up to 1.7  the energy consumption.
scratchpad memory multi-core phoenix mapreduce execution time energy consumption data-centers