Endre søk
RefereraExporteraLink to record
Permanent link

Direct link
Referera
Referensformat
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annet format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annet språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf
Performance Evaluation of Boids on the GPU and CPU
Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för kreativa teknologier.
2018 (engelsk)Independent thesis Basic level (degree of Bachelor), 10 poäng / 15 hpOppgave
Abstract [en]

Context. Agent based models are used to simulate complex systems by using multiple agents that follow a set of rules. One such model is the boid model which is used to simulate movements of synchronized groups of animals. Executing agent based models partially or fully on the GPU has previously shown to increase performance, opening up the possibility for larger simulations. However, few articles have previously compared a full GPU implementation of the boid model with a multi-threaded CPU implementation.

Objectives. The objectives of this thesis are to find how parallel execution of boid model performs when executed on the CPU and GPU respectively, based on the variables frames per second and average boid computation time per frame.

Methods. A performance benchmark experiment will be set up where three implementations of the boid model are implemented and tested.

Results. The collected data is summarized in both tables and graphs, showing the result of the experiment for frames per second and average boid computation time per frame. Additionally, the average results are summarized in two tables.

Conclusions. For the largest flock size the GPGPU implementation performs the best with an average FPS of 42 times over the single-core implementation while the multi-core implementation performs with an average FPS 6 times better than the single-core implementation. For the smallest flock size the single-core implementation is most efficient while the GPGPU implementation has 1.6 times slower average update time and the multi-cor eimplementation has an average update time of 11 times slower compared to the single-core implementation.

sted, utgiver, år, opplag, sider
2018. , s. 35
Emneord [en]
boid, ABM, agent based model, GPGPU
HSV kategori
Identifikatorer
URN: urn:nbn:se:bth-15970OAI: oai:DiVA.org:bth-15970DiVA, id: diva2:1191916
Fag / kurs
DV1478 Bachelor Thesis in Computer Science
Utdanningsprogram
DVGSP Game Programming
Veileder
Examiner
Tilgjengelig fra: 2018-03-22 Laget: 2018-03-20 Sist oppdatert: 2018-03-22bibliografisk kontrollert

Open Access i DiVA

fulltext(2585 kB)229 nedlastinger
Filinformasjon
Fil FULLTEXT01.pdfFilstørrelse 2585 kBChecksum SHA-512
fadbc74c6b01321023fd9d061180e17cb2331397523be9f491db152ace1160ea28abd5bfc83a5b064c8400357b2cdf6387f590fabc2c1ac6fbfae339eb358707
Type fulltextMimetype application/pdf

Av organisasjonen

Søk utenfor DiVA

GoogleGoogle Scholar
Totalt: 229 nedlastinger
Antall nedlastinger er summen av alle nedlastinger av alle fulltekster. Det kan for eksempel være tidligere versjoner som er ikke lenger tilgjengelige

urn-nbn

Altmetric

urn-nbn
Totalt: 996 treff
RefereraExporteraLink to record
Permanent link

Direct link
Referera
Referensformat
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annet format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annet språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf