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.
| Original language | English |
|---|---|
| Article number | 9144250 |
| Pages (from-to) | 210-213 |
| Number of pages | 4 |
| Journal | IEEE Solid-State Circuits Letters |
| Volume | 3 |
| DOIs | |
| Publication status | Published - 1 Jan 2020 |
| MoE publication type | A1 Journal article-refereed |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- Dynamic voltage scaling
- energy efficiency
- microprocessors
- system analysis and design
- system-on-chip
- vector processors
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