search query: @keyword parallel computing / total: 13
reference: 3 / 13
« previous | next »
Author:Hulkkonen, Mikko
Title:Graphics processing unit utilization in circuit simulation
Grafiikkaprosessorin hyödyntäminen piirisimuloinnissa
Publication type:Master's thesis
Publication year:2011
Pages:[8] + 45      Language:   eng
Department/School:Radiotieteen ja -tekniikan laitos
Main subject:Teoreettinen sähkötekniikka   (S-55)
Supervisor:Valtonen, Martti
Instructor:Virtanen, Jarmo
Electronic version URL: http://urn.fi/URN:NBN:fi:aalto-201207022721
OEVS:
Electronic archive copy is available via Aalto Thesis Database.
Instructions

Reading digital theses in the closed network of the Aalto University Harald Herlin Learning Centre

In the closed network of Learning Centre you can read digital and digitized theses not available in the open network.

The Learning Centre contact details and opening hours: https://learningcentre.aalto.fi/en/harald-herlin-learning-centre/

You can read theses on the Learning Centre customer computers, which are available on all floors.

Logging on to the customer computers

  • Aalto University staff members log on to the customer computer using the Aalto username and password.
  • Other customers log on using a shared username and password.

Opening a thesis

  • On the desktop of the customer computers, you will find an icon titled:

    Aalto Thesis Database

  • Click on the icon to search for and open the thesis you are looking for from Aaltodoc database. You can find the thesis file by clicking the link on the OEV or OEVS field.

Reading the thesis

  • You can either print the thesis or read it on the customer computer screen.
  • You cannot save the thesis file on a flash drive or email it.
  • You cannot copy text or images from the file.
  • You cannot edit the file.

Printing the thesis

  • You can print the thesis for your personal study or research use.
  • Aalto University students and staff members may print black-and-white prints on the PrintingPoint devices when using the computer with personal Aalto username and password. Color printing is possible using the printer u90203-psc3, which is located near the customer service. Color printing is subject to a charge to Aalto University students and staff members.
  • Other customers can use the printer u90203-psc3. All printing is subject to a charge to non-University members.
Location:P1 Ark Aalto  759   | Archive
Keywords:CUDA
circuit simulation
diode model
parallel computing
CUDA
diodimalli
piirisimulointi
rinnakkaislaskenta
Abstract (eng): Graphics processing units (GPU) of today include hundreds of multi-threaded, multicore processors and a complex, high-bandwidth memory architecture, making them a good alternative to speed up general-purpose parallel computation where large data quantities are processed with same functions.
Some successful applications of GPU computation have also been introduced in the field of circuit simulation.
The objective of this thesis is to examine the GPU's computing potential in the APLAC circuit simulation software.
The realization of a diode model on a GPU device is also presented.

The nonlinear diode model was implemented on NVIDIA's Compute Unified Device Architecture (CUDA), that is a single-instruction, multiple-thread (SIMT) architecture.
A CUDA device was programmed using the CUDA C application programming interface, which is an extension of the standard C language.

The test results revealed that due to the diode's simple nonlinearity, its evaluation is computationally too light to gain any speed benefit from the GPU's computation power.
The required modifications to the circuit analysis structure and data handling resulted in a marginally longer total simulation time than initially.
However, when the diode model is made more complex by multiplying its evaluation, the CUDA implementation is faster than the original model.
This gives a rough estimate of how complex a model benefits from the GPU computation.

Although, the diode model evaluation was not faster on the GPU, this implementation is a good foundation for future CUDA applications in APLAC.
The next of these applications will be the computationally more complex BSIM3 transistor model, which will most likely benefit from the computing power of GPU devices.
Abstract (fin): Nykypäivän grafiikkaprosessorit (GPU) koostuvat sadoista monisäikeisistä, moniytimisistä prosessoreista ja monimutkaisesta korkean kaistanleveyden muistiarkkitehtuurista.
Tämän vuoksi niistä on tullut hyvä vaihtoehto nopeuttamaan rinnakkaistettua yleislaskentaa, jossa suuria datamääriä käsitellään samoilla funktioilla.
Myös piirisimuloinnin alalla on esitelty menestyksellisiä GPU-laskennan sovellutuksia.
Tämän opinnäytteen tavoitteena on tutkia GPU-laskennan mahdollisuuksia APLAC-piirisimulointiohjelmassa.
Työssä esitellään myös diodimallin laskennan toteutus GPU:lla.

Epälineaarinen diodimalli toteutettiin NVIDIAn CUDA-arkkitehtuurilla, joka on niin sanottu SIMT-arkkitehtuuri (single-instruction, multiple-thread) eli yksi käsky suoritetaan kerrallaan usealle säikeelle.
CUDA-laite ohjelmoitiin CUDA C -ohjelmointirajapinnalla, joka on standardin C-kielen laajennus.

Testitulokset paljastivat että diodin yksinkertaisesta epälineaarisuudesta johtuen sen laskenta on liian kevyt, jotta GPU:n tehokkuudesta olisi mitään nopeusetua.
Vaadittavat muutokset piirianalyysin rakenteeseen sekä datan hallintaan johtivat marginaalisesti alkuperäistä pidempään kokonaissimulointiaikaan.
Kun diodimallia monimutkaistetaan moninkertaistamalla sen laskenta, CUDA-toteutus on nopeampi kuin alkuperäinen malli.
Tämä antaa karkean arvion siitä kuinka monimutkainen malli hyötyy GPU-laskennasta.

Vaikka diodimalli ei ollutkaan nopeampi GPU:lla, tämä toteutus on hyvä perusta tuleville CUDA-sovelluksille APLACissa.
Näistä seuraavana on huomattavasti monimutkaisempi BSIM3-transistorimallin laskenta, joka mitä todennäköisimmin hyötyy GPU:n laskentatehosta.
ED:2011-11-07
INSSI record number: 42909
+ add basket
« previous | next »
INSSI