# Difference between revisions of "TeamC"

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[[File:Chart.jpg]]<br> | [[File:Chart.jpg]]<br> | ||

− | Chart | + | Chart<br><br> |

+ | As We can see the chart above, the graph increases as the execution time increase.<br> | ||

+ | Also it is possible to know that time complexity of calculation of Pi using Monte Carlo method is O(1) | ||

+ | |||

=== Assignment 2 === | === Assignment 2 === | ||

+ | As i chose "Calculation of Pi using Monte Carlo method" for the first assignment, i have parallelized it to run on custom kernel on CUDA device. | ||

+ | |||

+ | ==== '''Results''' ==== | ||

+ | [[File:1000000_2.jpg]]<br> | ||

+ | Number of points = 1 Million<br> | ||

+ | [[File:5000000_2.jpg]]<br> | ||

+ | Number of points = 5 Million<br> | ||

+ | [[File:10000000_2.jpg]]<br> | ||

+ | Number of points = 10 Million<br> | ||

+ | [[File:50000000_2.jpg]]<br> | ||

+ | Number of points = 50 Million<br> | ||

+ | [[File:100000000_2.jpg]]<br> | ||

+ | Number of points = 100 Million<br> | ||

+ | [[File:200000000_2.jpg]]<br> | ||

+ | Number of points = 200 Million<br> | ||

+ | |||

+ | [[File:chart_2.jpg]]<br> | ||

+ | Chart<br><br> | ||

+ | |||

+ | === '''Compare''' === | ||

+ | [[File:Chart_both.jpg]]<br> | ||

+ | As we can see on the chart above, using parallel programming reduced the execution time dramatically as the number of points increases. | ||

=== Assignment 3 === | === Assignment 3 === |

## Latest revision as of 19:22, 31 October 2014

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

## Contents

# Project "Break Pi"

## Team Members

## Progress

### Assignment 1

**Introduction**

For the first assignment which is "Initial profiling", I chose "Calculation of Pi using Monte Carlo method" to profile.

**Results**

Number of points = 1 Million

Number of points = 5 Million

Number of points = 10 Million

Number of points = 50 Million

Number of points = 100 Million

Number of points = 200 Million

Chart

As We can see the chart above, the graph increases as the execution time increase.

Also it is possible to know that time complexity of calculation of Pi using Monte Carlo method is O(1)

### Assignment 2

As i chose "Calculation of Pi using Monte Carlo method" for the first assignment, i have parallelized it to run on custom kernel on CUDA device.

**Results**

Number of points = 1 Million

Number of points = 5 Million

Number of points = 10 Million

Number of points = 50 Million

Number of points = 100 Million

Number of points = 200 Million

**Compare**

As we can see on the chart above, using parallel programming reduced the execution time dramatically as the number of points increases.