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.