A defect tolerant self-organizing nanoscale SIMD architecture

Journal Article

The continual decrease in transistor size (through either scaled CMOS or emerging nano-technologies) promises to usher in an era of tera to peta-scale integration. However, this decrease in size is also likely to increase defect densities, contributing to the exponentially increasing cost of top-down lithography. Bottom-up manufacturing techniques, like self assembly, may provide a viable lower-cost alternative to top-down lithography, but may also be prone to higher defects. Therefore, regardless of fabrication methodology, defect tolerant architectures are necessary to exploit the full potential of future increased device densities.This paper explores a defect tolerant SIMD architecture. A key feature of our design is the ability of a large number of limited capability nodes with high defect rates (up to 30%) to self-organize into a set of SIMD processing elements. Despite node simplicity and high defect rates, we show that by supporting the familiar data parallel programming model the architecture can execute a variety of programs. The architecture efficiently exploits a large number of nodes and higher device densities to keep device switching speeds and power density low. On a medium sized system (∼1cm 2 area), the performance of the proposed architecture on our data parallel programs matches or exceeds the performance of an aggressively scaled out-of-order processor (128-wide, 8k reorder buffer, perfect memory system). For larger systems (>1cm 2), the proposed architecture can match the performance of a chip multiprocessor with 16 aggressively scaled out-of-order cores. Copyright © 2006 ACM.

Full Text

Duke Authors

Cited Authors

  • Patwardhan, JP; Johri, V; Dwyer, C; Lebeck, AR

Published Date

  • December 1, 2006

Published In

  • International Conference on Architectural Support for Programming Languages and Operating Systems Asplos

Start / End Page

  • 241 - 251

Digital Object Identifier (DOI)

  • 10.1145/1168857.1168888

Citation Source

  • Scopus