Abstract
This letter presents a RISC-V System-on-Chip (SoC) with fully integrated switched-capacitor DC–DC converters, adaptive clock generators, mixed-precision floating-point vector accelerators, a 5-Gb/s serial memory interface, and an integrated power management unit (PMU) manufactured in 28-nm FD-SOI. The vector accelerator improves performance and energy per task on a matrix multiplication kernel by $15\times $ and $13\times $ , respectively, and end-to-end performance on machine learning and graph analytical workloads by $8\times $ – $12\times $ . Inclusion of microarchitectural counters and fine spatial power-domain granularity facilitate the predictive power-management algorithms that reduce energy per task by 13%–22% compared to the baseline scalar processor. System-level simulations of a range of SoC architectural variations with multiple cores and vector accelerators complement the silicon measurements.
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