Difference between revisions of "GPU610/DPS915 CUDA PI"

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== '''Team Members''' ==
 
== '''Team Members''' ==

Revision as of 23:55, 3 November 2013


GPU610/DPS915 | Student List | Group and Project Index | Student Resources | Glossary

CUDA PI Calcuation (Monte Carlo)

Team Pi CUDA

Welcome to GPU610AA Fall 2013 Team Pi CUDA Page.

My name is Peter Huang and I'm a student in the GPU610 class for the Fall Semester of 2013. Having no background whatsoever in parallel programming, I've decided to choose something that is out of my scope of understanding and interest (video game programming) to challenge myself. Thus, I've decided to investigate the benefits of parallel programming applied to the Monte Carlo statistical method to approximating the value of pi.

Announcements

N/A

Team Members

  1. Peter Huang

eMail All

Progress

Assignment 1

Introduction

For the initial profiling, I've decided to investigate the Monte Carlo Statistics Methodology of approximating the value of Pi. A brief explanation of Monte Carlo Pi calculation can be found here: https://www.youtube.com/watch?v=VJTFfIqO4TU

Source File(s)

Link: https://drive.google.com/file/d/0B8GUuIUqdEJES3VEOGRnYmRNaEk

Compilation and Running

Pi serial execution example.jpg

Serial Results

Pi serial results.jpg

Conclusion

Assignment 2

Introduction

In Phase 2, I've parallelized the serial program to run on a custom kernel on a CUDA-enabled device.

Compilation and Running

Pi cuda execution example.jpg

Parallel (CUDA) Results

Pi cuda results.jpg

Serial VS CUDA

Pi serial vs cuda results.jpg

Source File(s)

Link: https://drive.google.com/file/d/0B8GUuIUqdEJEbDBRNkhWYnpGSnM

Conclusion

Assignment 3

Agenda

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Progress

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Meetings

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Discussion

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