Scheduling on Manycore and Heterogeneous Graphics Processors

<p>Through custom software schedulers that distribute work differently than built-in hardware schedulers, data-parallel and heterogenous architectures can be retargeted towards irregular task-parallel graphics workloads. This dissertation examines the role of a GPU scheduler and how it may s...

Full description

Bibliographic Details
Main Author: Tzeng, Stanley
Language:EN
Published: University of California, Davis 2014
Subjects:
Online Access:http://pqdtopen.proquest.com/#viewpdf?dispub=3602240
id ndltd-PROQUEST-oai-pqdtoai.proquest.com-3602240
record_format oai_dc
spelling ndltd-PROQUEST-oai-pqdtoai.proquest.com-36022402014-01-09T04:05:29Z Scheduling on Manycore and Heterogeneous Graphics Processors Tzeng, Stanley Computer Science <p>Through custom software schedulers that distribute work differently than built-in hardware schedulers, data-parallel and heterogenous architectures can be retargeted towards irregular task-parallel graphics workloads. This dissertation examines the role of a GPU scheduler and how it may schedule complicated workloads onto the GPU for efficient parallel processing. This dissertation examines the scheduler through three different properties of workloads: granularity, irregularity, and dependency. Then it moves onto heterogenous architectures and examine how scheduling decisions differ when scheduling for discrete versus heterogeneous chips. The dissertation conclues with future work in scheduling for both discrete and heterogeneous architectures. University of California, Davis 2014-01-04 00:00:00.0 thesis http://pqdtopen.proquest.com/#viewpdf?dispub=3602240 EN
collection NDLTD
language EN
sources NDLTD
topic Computer Science
spellingShingle Computer Science
Tzeng, Stanley
Scheduling on Manycore and Heterogeneous Graphics Processors
description <p>Through custom software schedulers that distribute work differently than built-in hardware schedulers, data-parallel and heterogenous architectures can be retargeted towards irregular task-parallel graphics workloads. This dissertation examines the role of a GPU scheduler and how it may schedule complicated workloads onto the GPU for efficient parallel processing. This dissertation examines the scheduler through three different properties of workloads: granularity, irregularity, and dependency. Then it moves onto heterogenous architectures and examine how scheduling decisions differ when scheduling for discrete versus heterogeneous chips. The dissertation conclues with future work in scheduling for both discrete and heterogeneous architectures.
author Tzeng, Stanley
author_facet Tzeng, Stanley
author_sort Tzeng, Stanley
title Scheduling on Manycore and Heterogeneous Graphics Processors
title_short Scheduling on Manycore and Heterogeneous Graphics Processors
title_full Scheduling on Manycore and Heterogeneous Graphics Processors
title_fullStr Scheduling on Manycore and Heterogeneous Graphics Processors
title_full_unstemmed Scheduling on Manycore and Heterogeneous Graphics Processors
title_sort scheduling on manycore and heterogeneous graphics processors
publisher University of California, Davis
publishDate 2014
url http://pqdtopen.proquest.com/#viewpdf?dispub=3602240
work_keys_str_mv AT tzengstanley schedulingonmanycoreandheterogeneousgraphicsprocessors
_version_ 1716623012715823104