Arjang Hassibi Thesis

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My dissertation, Look me up at DBLP for another view on my publications.

Some of the links below are to the ACM database (so they can affect the ACM’s popularity statistics).

Floating-point numbers, for example, approximate real-number arithmetic to save space and time over arbitrary-precision numerical representation.

This document focuses on the study of approximate computing and system-level techniques that apply this theory to create new trade-offs.

The general idea is to spend less energy on retaining or accessing data; in return, there is a small probability that bits will flip in the memory.

Drg Assignment - Arjang Hassibi Thesis

SRAM structures spend significant static power on retaining data, so they represent another opportunity for fidelity trade-offs [@hybrid-sram; @sramerrors; @partially-forgetful].

This section deals with hardware-oriented approximation techniques.

We categorize the techniques according to the hardware component they affect.

It's a living document meant to exhaustively catalog everything we know about approximation along with the earlier work that influenced it.

It's also a collaborative, open-source project: to contribute, see its home on Git Hub.

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