Date of Award

2018

Degree Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Graduate Group

Computer and Information Science

First Advisor

André M. DeHon

Abstract

For field-programmable gate arrays (FPGAs), fine-grained pre-computed alternative configurations, combined with simple test-based selection, produce limited per-chip specialization to counter yield loss, increased delay, and increased energy costs that come from fabrication defects and variation. This lightweight approach achieves much of the benefit of knowledge-based full specialization while reducing to practical, palatable levels the computational, testing, and load-time costs that obstruct the application of the knowledge-based approach. In practice this may more than double the power-limited computational capabilities of dies fabricated with 22nm technologies.

Contributions of this work:

• Choose-Your-own-Adventure (CYA), a novel, lightweight, scalable methodology to achieve defect and variation mitigation

• Implementation of CYA, including preparatory components (generation of diverse alternative paths) and FPGA load-time components

• Detailed performance characterization of CYA

– Comparison to conventional loading and dynamic frequency and voltage scaling (DFVS)

– Limit studies to characterize the quality of the CYA implementation and identify potential areas for further optimization

Additional Files

extra_files_deposited.zip (273664 kB)

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