Synthesis of Custom Processors based on Extensible Platforms

Abstract|Eciency and exibility are critical, but often con ict-ing, design goals in embedded system design. The recent emergence of extensible processors promises a favorable tradeo between e-ciency and exibility, while keeping design turnaround times short. Current extensible processor design ows automate several tedious tasks, but typically require designers to manually select the parts of the program that are to be implemented as custom instructions. In this work, we describe an automatic methodology to select custom instructions to augment an extensible processor, in order to maximize its eciency for a given application program. We demon-strate that the number of custom instruction candidates grows rapidly with program size, leading to a large design space, and that the quality (speedup) of custom instructions varies signicantly across this space, motivating the need for the proposed ow. Our methodology features cost functions to guide the custom instruction selection process, as well as static and dynamic pruning techniques to eliminate inferior parts of the design space from consideration. Further, we employ a two-stage process, wherein a limited num-ber of promising instruction candidates are rst selected, and then evaluated in more detail through cycle-accurate instruction set sim-ulation and synthesis of the corresponding hardware, to identify the custom instruction combinations that result in the highest program speedup or maximize speedup under a given area constraint. We have evaluated the proposed techniques using a state-of-the-art extensible processor platform, in the context of a commercial design ow. Experiments with several benchmark programs indi-cate that custom processors synthesized using automatic custom instruction selection can result in large improvements in perfor-mance (upto 5.4X, average of 3.4X), energy (upto 4.5X, average of 3.2X), and energy-delay product (upto 24.2X, average of 12.6X), while speeding up the design process signicantly. I