Energy-Efficient String Search Architectures on a Fine-Grained Many-Core Platform

This paper presents three energy-efficient methods for searching and filtering streamed data on a fine-grained manycore processor array: parallel, serial, and all-in-one. All three architectures aim to provide programmable flexibility with low energy consumption. Experimental results show that for one keyword search, the parallel and serial architectures consume 2× less energy per workload than the all-in-one architecture. For two or more keyword searches, the all-in-one architecture achieves up to 2.6× higher throughput per area over the parallel architecture, and 25.6× over the serial architecture. Scaled results show that the serial and parallel designs provide 211× increased throughput per area, and yield 155× energy reduction when compared to a traditional processor (Intel Core i7 3667U). The proposed architectures are modular and easily scalable.