A hybrid Nano/CMOS dynamically reconfigurable system—Part II: Design optimization flow

  • Authors:
  • Wei Zhang;Niraj K. Jha;Li Shang

  • Affiliations:
  • Princeton University, Princeton, NJ;Princeton University, Princeton, NJ;University of Colorado, Boulder, CO

  • Venue:
  • ACM Journal on Emerging Technologies in Computing Systems (JETC)
  • Year:
  • 2009

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Abstract

In Part I of this work, a hybrid nano/CMOS reconfigurable architecture, called NATURE, was described. It is composed of CMOS reconfigurable logic and interconnect fabric, and nonvolatile nano on-chip memory. Through its support for cycle-by-cycle runtime reconfiguration and a highly-efficient computation model, temporal logic folding, NATURE improves logic density and area-delay product by more than an order of magnitude compared to existing CMOS-based field-programmable gate arrays (FPGAs). NATURE can be fabricated using mainstream photo-lithography fabrication techniques. Thus, it offers a currently commercially feasible architecture with high performance, superior logic density, and excellent runtime design flexibility. In Part II of this work, we present an integrated design and optimization flow for NATURE, called NanoMap. Given an input design specified in register-transfer level (RTL) and/or gate-level VHDL, NanoMap optimizes and implements the design on NATURE through logic mapping, temporal clustering, temporal placement, and routing. As opposed to other design tools for traditional FPGAs, NanoMap supports and leverages temporal logic folding by integrating novel mapping techniques. It can automatically explore and identify the best temporal logic folding configuration, targeting area, delay or area-delay product optimization. A force-directed scheduling technique is used to optimize and balance resource usage across different folding cycles. By supporting logic folding, NanoMap can provide significant design flexibility in performing area-delay trade-offs under various user-specified constraints. We present details of the mapping procedure and results for different architectural instances. Experimental results demonstrate that NanoMap can judiciously trade off area and delay targeting different optimization goals, and effectively exploit the advantages of NATURE. Part I of this work will appear in JETC Vol. 5, No. 4.