An analytical model for multilevel performance prediction of Multi-FPGA systems

Power limitations in semiconductors have made explicitly parallel device architectures such as Field-Programmable Gate Arrays (FPGAs) increasingly attractive for use in scalable systems. However, mitigating the significant cost of FPGA development requires efficient design-space exploration to plan and evaluate a range of potential algorithm and platform choices prior to implementation. The authors propose the RC Amenability Test for Scalable Systems (RATSS), an analytical model which enables straightforward, fast, and reasonably accurate performance prediction prior to implementation by extending current modeling concepts to multi-FPGA designs. RATSS provides a comprehensive strategic model to evaluate applications based on the computation and communication requirements of the algorithm and capabilities of the FPGA platform. The RATSS model targets data-parallel applications on current scalable FPGA systems. Three case studies with RATSS demonstrate nearly 90% prediction accuracy as compared to corresponding implementations.