一个2.41 μ w /MHz, 437-PE/mm2的22 nm FD-SOI CGRA与类risc代码生成

Tobias Kaiser, F. Gerfers
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摘要

虽然粗粒度可重构阵列(CGRAs)有潜力提高通用计算的能源效率,超越了冯·诺伊曼架构的限制,但它们在代码生成方面面临挑战。pasithea - 1是一种CGRA架构,旨在将高能效与类似risc的可编程性相结合。本文介绍了它的第一个硅原型和一个使用传统CPU编译技术的C编译器。传统的CGRAs代码生成需要昂贵的放置和路由步骤,与之相比,这种代码生成方法大大减少了编译时间和编译器的复杂性。对一组用c语言编写的基准程序进行了性能和功耗测试,平均实现了195.1 int32 MIPS/mW的能效和2.41μW/MHz的有功功率。峰值能效为558.2 MIPS/mW,峰值性能为97.5 MIPS/mW。加载/存储指令和指令传输被认为是Pasithea能效的关键因素。与具有最先进能效的MCU相比,Pasithea在四个基准程序中实现了更高的能效。每次基准测试运行的开关电容平均减少了约1.4倍。其0.75 mm2的核心面积和437 Plis/mm2的织物密度使其能够在成本敏感的应用中使用,并允许进一步升级。
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A 2.41-μW/MHz, 437-PE/mm2 CGRA in 22 nm FD-SOI With RISC-Like Code Generation
While coarse-grained reconfigurable arrays (CGRAs) have the potential to improve energy efficiency in general-purpose computing beyond the limitations of von Neumann architectures, they suffer from challenges in code generation. Pasithea-l is a CGRA architecture that aims to combine high energy efficiency with RISC-like programmability. This paper presents its first silicon prototype and a C compiler that uses conventional CPU compiler techniques. Compared to code generation for traditional CGRAs, which require expensive place and route steps, this method of code generation reduces compile times and compiler complexity significantly. Performance and power were measured for a set of benchmark programs written in C. On average, energy efficiency of 195.1 int32 MIPS/mW and active power of 2.41μW/MHz were achieved. Peak energy efficiency of 558.2 MIPS/mW and peak performance of 97.5 MIPS were measured. Load/store instructions and instruction transfers are identified as critical factors for energy efficiency in Pasithea. In comparison to an MCU with state-of-the-art energy efficiency, Pasithea achieves higher energy efficiency in four of the benchmarked programs. Switched capacitance per benchmark run was reduced by a factor of approximately 1.4, on average. Its 0.75 mm2 core area and fabric density of 437 Plis/mm2 enable use in cost-sensitive applications and permit further upscaling.
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Special Session Speakers Biography A 2.41-μW/MHz, 437-PE/mm2 CGRA in 22 nm FD-SOI With RISC-Like Code Generation A Low-power Neural 3D Rendering Processor with Bio-inspired Visual Perception Core and Hybrid DNN Acceleration Cachet: A High-Performance Joint-Subtree Integrity Verification for Secure Non-Volatile Memory FPGA Emulation of Through-Silicon-Via (TSV) Dataflow Network for 3D Standard Chip Stacking System
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