Date of Award

Spring 5-2016

Document Type

Thesis

Degree Name

Master of Electrical Engineering (MEE)

Department

Electrical Engineering

First Advisor

Daniel Chang

Second Advisor

Yong Jin Kim

Third Advisor

Mario Simoni

Abstract

The NEUROSim framework consists of a compiler, assembler, and cycle-accurate processor simulator to facilitate computer architecture research. This framework provides a core instruction set common to many applications and a simulated datapath capable of executing these instructions. However, the core contribution of NEUROSim is its exible and extensible design allowing for the addition of instructions and architecture changes which target aspecic application. The NEUROSim framework is presented through the analysis of many system design decisions including execution forwarding, control change detection, FPU configuration, loop unrolling, recursive functions, self modifying code, branch predictors, and cache architectures. To demonstrate its exible nature, the NEUROSim framework is applied to specific domains including a modulo instruction intended for use in encryption applications, a multiply accumulate instruction analyzed in the context of digital signal processing,

Taylor series expansion and lookup table instructions applied to mathematical expression approximation, and an atomic compare and swap instruction used for sorting.

Comments

To my wife, Meg, for her constant encouragement and love. I am truly blessed to have you in my life. And to my parents, David and Dorothy, for their support, love, and wonderful examples.

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