Improving Performance of Codes with Large/Irregular Stride Memory Access Patterns via High Performance Reconfigurable Computers

Parallel codes with large-stride/irregular-stride (L/I) memory access patterns, e.g., sparse matrix and linked list codes, often perform poorly on mainstream clusters because of the general purpose processor (GPP) memory hierarchy. High performance reconfigurable computers (HPRCs) are parallel computing clusters containing multiple GPPs and field programmable gate arrays (FPGAs) connected via a high-speed network. In this research, simple 64-bit floating-point parallel codes are used to illustrate the performance impact of L/I memory accesses in software (SW) and FPGA-augmented (FA) codes and to assess the benefits of mapping L/I-type codes onto HPRCs. The experiments reveal that large-stride SW codes, particularly those involving data reuse, experience severe performance degradation compared with unit-stride SW codes. In contrast, large-stride FA codes experience minimal degradation compared with unit-stride FA codes. More importantly, for codes that involve data reuse, the experiments demonstrate performance improvements of up to nearly tenfold for large-stride FA codes compared with large-stride SW codes.