Adaptive Explicitly Parallel Instruction Computing

Abstract

Current processors are programmed through a fixed interface called the Instruction Set Architecture (ISA). Consequently, a compiler targeting such a processor is forced to choose instructions from the provided instruction set while generating code for a given application. Often this instruction set is not a suitable match for the computational requirements of the application program. With in this context, we ask ourselves the following questions. 1. Can application performance be improved if the compiler had the freedom to pick the instruction set on a per application basis? 2. Can we build cost-effective processors that provide the ability to efficiently emulate compiler determined instruction sets and yet are not application specific? 3. Given that the desired processor capabilities are feasible, can the compiler determine an optimal set of instructions for a given application and generate code that can effectively exploit the processor capabilities? In this thesis, we provide sufficient evidence to answer these questions in the affirmative. Through a combination of architectural innovations and novel compilation techniques, this dissertation demonstrates that it is possible to attain significant improvement in performance, up to an order of magnitude in some cases, on general purpose and multimedia applications over comparable fixed ISA processors. We propose classes of microprocessors that allow application programs to add and subtract functional units yielding a dynamically varying instruction set interface to the running application without compromising current compatibility model.

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Document Details

Document Type
Technical Report
Publication Date
Dec 16, 2000
Accession Number
ADA440677

Entities

People

  • Surendranath Talla

Organizations

  • New York University

Tags

Communities of Interest

  • Advanced Electronics
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Application Software
  • Coding
  • Communication Networks
  • Computer Architecture
  • Computer Programming
  • Computer Programs
  • Computers
  • Data Compression
  • Digital Signal Processing
  • Field Programmable Gate Arrays
  • Floating Point Operations
  • Instruction Set Architecture
  • Operating Systems
  • Parallel Computing
  • Parallel Processing
  • Signal Processing
  • Speech Compression

Fields of Study

  • Computer science

Readers

  • Parallel and Distributed Computing.
  • Regression Analysis.
  • Systems Analysis and Design