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摘要:
In the era of Internet of Things, the battery life of edge devices must be extended for sensing connection to the Internet. We aim to reduce the power consumption of the microprocessor embedded in such devices by using a novel dynamically reconfigurable accelerator. Conventional microprocessors consume a large amount of power for memory access, in registers, and for the control of the processor itself rather than computation;this decreases the energy efficiency. Dynamically reconfigurable accelerators reduce such redundant power by computing in parallel on reconfigurable switches and processing element arrays (often consisting of an arithmetic logic unit (ALU) and registers). We propose a novel dynamically reconfigurable accelerator “DYNaSTA” composed of a dynamically reconfigurable data path and static ALU arrays. The static ALU arrays process instructions in parallel without registers and improve energy efficiency. The dynamically reconfigurable data path includes registers and many switches dynamically reconfigured to resolve operand dependencies between instructions mapped on the static ALU array, and forwards appropriate operands to the static ALU array. Therefore, the DYNaSTA accelerator has more flexibility while improving the energy efficiency compared with the conventional dynamically reconfigurable accelerators. We simulated the power consumption of the proposed DYNaSTA accelerator and measured the fabricated chip. As a result, the power consumption was reduced by 69% to 86%, and the energy efficiency improved 4.5 to 13 times compared to a general RISC microprocessor.
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篇名 A High Performance and Energy Efficient Microprocessor with a Novel Restricted Dynamically Reconfigurable Accelerator
来源期刊 电路与系统(英文) 学科 工学
关键词 EMBEDDED MICROPROCESSOR RECONFIGURABLE LOW-POWER ACCELERATOR Digital Circuit Architecture
年,卷(期) 2017,(5) 所属期刊栏目
研究方向 页码范围 134-147
页数 14页 分类号 TN92
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EMBEDDED
MICROPROCESSOR
RECONFIGURABLE
LOW-POWER
ACCELERATOR
Digital
Circuit
Architecture
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研究去脉
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期刊影响力
电路与系统(英文)
月刊
2153-1285
武汉市江夏区汤逊湖北路38号光谷总部空间
出版文献量(篇)
286
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0
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0
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