A numerical optimization-based methodology for application robustification: transforming applications for error tolerance
Sloan, Joseph A.
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https://hdl.handle.net/2142/24206
Description
Title
A numerical optimization-based methodology for application robustification: transforming applications for error tolerance
Author(s)
Sloan, Joseph A.
Issue Date
2011-05-25T15:04:15Z
Director of Research (if dissertation) or Advisor (if thesis)
Kumar, Rakesh
Department of Study
Electrical & Computer Eng
Discipline
Electrical & Computer Engr
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Keyword(s)
stochastic processors
fault tolerance
application robustification
Abstract
There have been several attempts at correcting process variation induced errors by identifying and masking these errors at the circuit and architecture level. These
approaches take up valuable die area and power on the chip. As an alternative, we explore the feasibility of an approach that allows these errors to occur freely
and handles them in software at the algorithmic level. In this thesis, we present a general approach to converting applications into an error tolerant form by recasting
these applications as numerical optimization problems, which can then be solved reliably via stochastic optimization. We evaluate the potential robustness
and energy benefits of the proposed approach using an FPGA-based framework that emulates timing errors in the floating point unit (FPU) of a Leon3 processor.
We show that stochastic versions of applications have the potential to produce good quality outputs in the face of timing errors under certain assumptions. We also show that good quality results are possible for both intrinsically robust algorithms as well as fragile applications under these assumptions.
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