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Mr.Wolf: An Energy-Precision Scalable Parallel Ultra Low Power SoC for IoT Edge Processing Antonio Pullini , Davide Rossi , Igor Loi , Giuseppe Tagliavini , and
MrWolf是一款面向物联网边缘的并行超低功耗SoC,具有能效比高的特点。
40nm CMOS, 108μW内存保持功耗, 1.6Gbit/s数据传输速率, 850MMAC/s峰值性能
物联网边缘超低功耗RISC-V并行计算能效比
▸创新点1:采用RISC-V核心的小型MCU架构(系统创新)。该SoC集成了一个仅12 kgates的超小型RISC-V MCU核心,作为基础控制单元,实现了极低的静态功耗(108μW全保持内存),同时支持通过任务卸载机制将计算密集型任务分配给八核计算集群。
▸创新点2:配备八核浮点计算引擎(架构创新)。该SoC集成一个可动态启用的八核浮点计算集群,支持32位整数(850 MMAC/s)和浮点(500 MFMAC/s)乘加运算,峰值能效达15 MMAC/s/mW(整数)和9 MFMAC/s/mW(浮点),实现了计算能力与能效的精准扩展。
▸创新点3:高效的IO子系统(电路创新)。采用自主IO子系统设计,支持1.6 Gbit/s高速外设数据直接内存访问(DMA),传输功耗低于2.5 mW,解决了传统MCU外设带宽瓶颈问题。
▸创新点4:异构计算电源管理(系统创新)。通过片上电源转换和分级电源管理技术,实现MCU、计算集群和IO子系统的能量比例供电,在153 mW总功耗下达成16.4 GOp/s算力和274 MOp/s/mW能效。
Abstract
This paper presents Mr.Wolf, a parallel ultra-low power (PULP) system on chip (SoC) featuring a hierarchical architecture with a small (12 kgates) microcontroller (MCU) class RISC-V core augmented with an autonomous IO subsystem for efficient data transfer from a wide set of peripherals. The small core can offload compute-intensive kernels to an eight-core floating-point capable of processing engine available on demand. The proposed SoC, implemented in a 40-nm LP CMOS technol- ogy, features a 108- µW fully retentive memory (512 kB). The IO subsystem is capable of transferring up to 1.6 Gbit/s from exter- nal devices to the memory in less than 2.5 mW. The eight-core compute cluster achieves a peak performance of 850 million of 32-bit integer multiply and accumulate per second (MMAC/s) and 500 million of 32-bit floating-point multiply and accumulate per second (MFMAC/s) −1 GFlop/s—with an energy efficiency up to 15 MMAC/s/mW and 9 MFMAC/s/mW. These building blocks are supported by aggressive on-chip power conversion and management, enabling energy-proportional heterogeneous com- puting for always-on IoT end nodes improving performance by several orders of magnitude with respect to traditional single-core MCUs within a power envelope of 153 mW. We demonstrated the capabilities of the proposed SoC on a wide set of near-sensor processing kernels showing that Mr.Wolf can deliver performance up to 16.4 GOp/s with energy efficiency up to 274 MOp/s/mW on real-life applications, paving the w