Approximate Computing in Digital Design.

Date of Submission

December 2016

Date of Award

Winter 12-12-2017

Institute Name (Publisher)

Indian Statistical Institute

Document Type

Master's Dissertation

Degree Name

Master of Technology

Subject Name

Computer Science


Advance Computing and Microelectronics Unit (ACMU-Kolkata)


Banerjee, Ansuman (ACMU-Kolkata; ISI)

Abstract (Summary of the Work)

In recent times, approximate computing is being looked at as a viable alternative for reducing the energy consumption of programs, while marginally compromising on the correctness of their computation. The idea behind approximate computing is to introduce approximations at various levels of the execution stack, with an attempt to realize the resource hungry computations on low resource consuming approximate hardware blocks. Approximate computing for program transformation faces a serious challenge of automatically identifying core program areas/statements where approximations can be introduced, with a quantifiable measure of the resulting program correctness compromise. Introducing approximations randomly can cause performance deterioration without much energy advantage, which is undesirable. In this thesis, we introduce a verification-guided method to automatically identify program blocks which lend themselves to easy approximations, while not compromising significantly on program correctness. Our method is based on identifying regions of code which are less influential for the computation of the program outputs and therefore, can be compromised with, however still having a potential of significant resource reduction. We take the help of assertions to quantify the effect of the resulting transformations on program outputs. We show experimental results to support our proposal.


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Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.


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