Parallelism Real TimeParallelism Real Time

Anca BatoriLavinia

BasarabăAnca

Brandimbur

“Politehnica” University of TimişoaraAutomation and Computing University

Computers Department

iunie 2010

ObjectivesObjectives

presenting the use of graphical processing units (GPU) to achieve significant improvements for real time systems

presenting the main steps for developing an application using CUDA

offering a source of resources

CConontentstentsIntroductionParallelism Application descriptionExperimentsConclusions

IntroductionIntroductionReal Time Systems are an

important area of research and development

Many applications: Airplanes, biomedical accelerators, nuclear power plants

Necessity of parallelism to achieve desired time limits

ParallelismParallelismCan be hardware and software

◦GPUs represent a combinationGPUs have certain characteristcs,

that CPUs do not poses, that can be useful for certain application◦More processing power, less

flexibilityThe application are developed

using CUBLAS

AArrcchitectuhitecturesresCPU CPU vsvs GPU GPU

Cores number 4Threads 2Cache memory

=> random address acces

Cores number 240Threads 1024Cache memory =>

fast access to consecutive addresses

Sursa: www.nvidia.com

Support Vector Machines Support Vector Machines (SVM)(SVM)

Possibilities to split two classes

SVMSVM geometrical geometrical representationrepresentation

CPU versus GPUCPU versus GPUSpeedup 54x for1000 imagesEven better results for bigger training

sets

Multiclass Multiclass SVMSVM

“One Against All” (OAA)training: M binary classifiers(M number of

classes)testing: strategy„the winner takes it all”

“One Against One” (OAO)training : M(M-1)/2 binary classifiers testing : strategy maximum number of votes

“Directed Acyclic Graph” (DAG)testing : decision tree

Multiclass AlgorithmsMulticlass Algorithms

NVIDIA GTX 280IDSIA sets

Training set dimension

Training time (secunde) Recognition percentage (%)

OAO DAG OAA OAO DAG OAA

100 15,183 15,183 7,092 84,94 84,45 67,39

300 129,188 129,188 77,438 88,37 87,91 82,19

1000 1806 1806 1452,7 90,73 89,84 82,94

Multiclass Multiclass AlgoritAlgorithhmmss

ConclusionsConclusionsIn the period of ubiquitous and

pervasive systems, real time systems are a very important field

Since CPUs do not evolve, so fast as they used to, there is a shift towards parallel programming and more and more systems are developed this way

GPUs can improve the execution time for an application 100x times

Thank youThank you