Multi-Mode Transprecision Sparse Matrix-Vector Multiplication Engine for PageRank

Today, with the advance of Internet search system and social networks, PageRank algorithm is widely used to calculate importance of many web pages and rank them. In PageRank calculation, Sparse Matrix-Vector Multiplication (SpMV) operations are the bottleneck for performance improvement. In this paper, we apply transprecision technique to SpMV unit to shorten the execution time of floating-point multiply-add. To optimize the transprecision calculation, the proposed floating-point multiply-add engine support multi-mode operation - two half-precision Single Instruction Multiple Data (SIMD) units and one single-precision unit with minimal hardware overhead.