A 3-D CPU-FPGA-DRAM Hybrid Architecture for Low-Power Computation

Xianmin Chen, Niraj K. Jha

Research output: Contribution to journalArticle

4 Scopus citations

Abstract

The power budget is expected to limit the portion of the chip that we can power ON at the upcoming technology nodes. This problem, known as the utilization wall or dark silicon, is becoming increasingly serious. With the introduction of 3-D integrated circuits (ICs), it is likely to become more severe. Thus, how to take advantage of the extra transistors, made available by Moore's law and the onset of 3-D ICs, within the power budget poses a significant challenge to system designers. To address this challenge, we propose a 3-D hybrid architecture consisting of a CPU layer with multiple cores, a field-programmable gate array (FPGA) layer, and a DRAM layer. The architecture is designed for low power without sacrificing performance. The FPGA layer is capable of supporting a large number of accelerators. It is placed adjacent to the CPU layer, with a communication mechanism that allows it to access CPU data caches directly. This enables fast switches between these two layers. This architecture reduces the power and energy significantly, at better or similar performance. This then alleviates the dark silicon problem by letting us power ON more components to achieve higher performance. We evaluate the proposed architecture through a new framework we have developed. Relative to the out-of-order CPU, the accelerators on the FPGA layer can reduce function-level power by 6.9� and energy-delay product (EDP) by 7.2�, and application-level power by 1.9� and EDP by 2.2�, while delivering similar performance. For the entire system, this translates to a 47.5% power reduction relative to a baseline system that consists of a CPU layer and a DRAM layer. This also translates to a 72.9% power reduction relative to an alternative system that consists of a CPU layer, an L3 cache layer, and a DRAM layer.

Original languageEnglish (US)
Article number7300466
Pages (from-to)1649-1662
Number of pages14
JournalIEEE Transactions on Very Large Scale Integration (VLSI) Systems
Volume24
Issue number5
DOIs
StatePublished - May 2016

All Science Journal Classification (ASJC) codes

  • Software
  • Hardware and Architecture
  • Electrical and Electronic Engineering

Keywords

  • 3-D integrated circuit (IC)
  • CPU
  • DRAM
  • field-programmable gate array (FPGA)
  • hybrid architecture
  • low power

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