Better-Than-Worst-Case: A Frequency Adaptation Asynchronous RISC-V Core with Vector Extension

In recent years, asynchronous circuits have become more popular in neural network chips and the Internet of Things (IoT) due to their potential advantages of low-power consumption and high performance. However, the existing design methods for asynchronous circuits are still constrained by critical paths, increasing power consumption and hindering the further improvement of performance. In this article, a fully digital design method for frequency adaptation asynchronous bundled-data (BD) circuits is proposed. The proposed method is straightforward, effective, widely applicable, and independent of asynchronous controllers. It allows to automatically work on different frequencies as required, which can improve performance and reduce power consumption, achieving better-than-worst-case. To verify the proposed method, an asynchronous RISC-V processor with vector acceleration extension is designed on both TSMC 65-nm process and field-programmable gate array (FPGA) platform. According to the postlayout simulation results, compared with its synchronous version, the asynchronous processor achieves a 10% speed improvement (from 227.3 to 250 MHz) with a 37% power reduction (from 135 to 85 $\mu$ W/MHz) under ideal conditions. Even under the worst conditions, the asynchronous processor achieves equivalent performance to the synchronous processor, while still reducing power consumption by 29% (from 133 to 95 mu W/MHz). On the FPGA platform, asynchronous processor also achieves higher speed while lower power consumption.