An FPGA-cluster-accelerated match engine for content-based image retrieval

Abstract

In this paper, a high-performance match engine for content-based image retrieval is proposed. Highly customized floating-point(FP) units are designed, to provide the dynamic range and precision of standard FP units, but with considerably less area than standard FP units. Match calculation arrays with various architectures and scales are designed and evaluated. An CBIR system is built on a 12-FPGA cluster. Inter-FPGA connections are based on standard 10-Gigabyte Ethernet. The whole FPGA cluster can compare a query image against 150 million library images within 10 seconds, basing on detailed local features. Compared with the Intel Xeon 5650 server based solution, our implementation is 11.35 times faster and 34.81 times more power efficient.