FPGA Based Acceleration of the Linpack Benchmark: A High Level Code Transformation Approach

Due to their increasing resource densities, field programmable gate arrays (FPGAs) have become capable of efficiently implementing large scale scientific applications involving floating point computations. In this paper FPGAs are compared to a high end microprocessor with respect to sustained performance for a popular floating point CPU performance benchmark, namely LINPACK 1000. A set of translation and optimization steps have been applied to transform a sequential C description of the LINPACK benchmark, based on a monolithic memory model, into a parallel Handel-C description that utilizes the plurality of memory resources available on a realistic reconfigurable computing platform. The experimental results show that the latest generation of FPGAs, programmed using Handel-C, can achieve a sustained floating point performance up to 6 times greater than the microprocessor while operating at a clock frequency that is 60 times lower. The transformations are applied in a way that could be generalized, allowing efficient compilation approaches for the mapping of high level descriptions onto FPGAs.