Web-Books
in the Austria-Forum
Austria-Forum
Web-Books
Informatik
Algorithms for Scheduling Problems
Page - 181 -
  • User
  • Version
    • full version
    • text only version
  • Language
    • Deutsch - German
    • English

Page - 181 - in Algorithms for Scheduling Problems

Image of the Page - 181 -

Image of the Page - 181 - in Algorithms for Scheduling Problems

Text of the Page - 181 -

Algorithms 2018,11, 76 It supports low overhead DMA transfers between internal memory, external memory, memory-mappedperipherals, linkports,hostprocessors,andotherDSPs,providinghighperformance for I/Oalgorithms. Flexible instructionsetsandhigh-level language-friendlyDSPsupport theeaseof implementation ofdigital signalprocessingwith lowcommunicationsoverheadinscalablemultiprocessingsystems. Withsoftware that isprogrammable formaximumflexibilityandsupportedbyeasy-to-use, low-cost development tools,DSPsenabledesigners tobuild innovative featureswithhighefficiency. TheDSPcombinesverywidememorywidthswith execution sixfloating-point and2464-bit fixed-pointoperations fordigital signalprocessing. Itmaintainsasystem-on-chipscalablecomputing design, including24Mbitofon-chipDRAM,six4Kwordcaches, integratedI/Operipherals, ahost processor interface, DMAcontrollers, LVDS link ports, and shared bus connectivity forGlueless Multiprocessingwithoutspecialbridgesandchipsets. It typicallyusestwomethodstocommunicatebetweenprocessornodes. Thefirstoneisdedicated point-to-pointcommunicationthroughlinkports.Othermethodusesasinglesharedglobalmemory tocommunicate throughaparallelbus. For full performanceof sucha combinedarchitecture, sophisticated resourcemanagement is necessary. Specifically,multiple instructionsmustbedispatchedtoprocessingunits simultaneously, andfunctionalparallelismmustbecalculatedbeforeruntime. In thispaper,wedescribeanapproach for scheduling imageprocessingworkflowsusing the networksofaDSP-cluster (Figure1). Figure1.Digital signalprocessor (DSP)cluster. 2.Model 2.1. BasicDefinitions Weaddressanoffline (deterministic)non-preemptive, clairvoyantworkflowschedulingproblem onaparallel clusterofDSPs. DSP-clustersconsistofm integratedmodules (IM) IM1, IM2, . . . , IMm. Letkibethesizeof IMi (numberofDSP-processors). Letnworkflowjobs J1, J2, . . . , Jnbescheduledonthecluster. A workflow is a composition of tasks subject to precedence constraints. Workflows are modeled as a Directed Acyclic Graph (DAG) Gj = ( Vj,Ej ) , where Vj is the set of tasks, and Ej= { (i,k) ∣∣ i,k∈Vj, i = k},withnocycles. Eacharc (i,k) isassociatedwithacommunicationtimedi,k representingthecommunicationdelay, if iandkareexecutedondifferentprocessors. Task imustbecompleted,anddatamustbe transmitted duringdi,kprior towhenexecutionof taskk is initiated. If iandkareexecutedonthesameprocessor, nodata transmissionbetweenthemisneeded;hence, communicationdelay isnotconsidered. Eachworkflow task i is a sequential application (thread) anddescribed by the tuple ( r′i,p ′ i ) , withreleasedate r′i, andexecutiontime p ′ i. 181
back to the  book Algorithms for Scheduling Problems"
Algorithms for Scheduling Problems
Title
Algorithms for Scheduling Problems
Authors
Frank Werner
Larysa Burtseva
Yuri Sotskov
Editor
MDPI
Location
Basel
Date
2018
Language
English
License
CC BY 4.0
ISBN
978-3-03897-120-7
Size
17.0 x 24.4 cm
Pages
212
Keywords
Scheduling Problems in Logistics, Transport, Timetabling, Sports, Healthcare, Engineering, Energy Management
Categories
Informatik
Technik
Web-Books
Library
Privacy
Imprint
Austria-Forum
Austria-Forum
Web-Books
Algorithms for Scheduling Problems