首页 > 科技
2024.1 Multicore Computing, Project #1
(Due : April 18, 11:59pm)
Submission Rule
1. Create a directory "proj1". In the directory, create two subdirectories, “problem1” and
“problem2”.
2. In each of the directory “problem1” and “problem2”, Insert (i)JAVA source code, (ii)a document
that reports the parallel performance of your code, and (iii) video file (.mp4 format) that shows
compilation and execution of your code. You may use your smartphone camera or screen recorder
program to generate this video file. The document that reports the parallel performance should
contain (a) in what environment (e.g. CPU type, number of cores, memory size, OS type ...) the
experimentation was performed, (b) tables and graphs that show the execution time
(unit:milisecond) for the number of entire threads = {1,2,4,6,8,10,12,14,16,32}. (c) The
document should also contain explanation/analysis on the results and why such results are
obtained with sufficient details. (d) The document should also contain screen capture image of
program execution and output. In the document (i.e. report), you should briefly explain how to
compile and execute the source code you submit. You should use JAVA language.
3. zip the directory "proj1" into "proj1.zip" and submit the zip file into eClass homework board.
※ If possible, please experiment in a PC equipped with a CPU that has 4 or more cores.
problem 1. Following JAVA program (pc_serial.java) computes the number of ‘prime numbers’ between 1 and
200000 using a single thread.
(i) Implement multithreaded version of pc_serial.java using static load balancing (using block decomposition),
static load balancing (using cyclic decomposition), and dynamic load balancing. Submit the multithreaded JAVA
codes ("pc_static_block.java", "pc_static_cyclic.java" and "pc_dynamic.java"). Your program should
print the (1) execution time of each thread and (2) program execution time and (3) the number of ‘prime numbers’.
FYI, the static load balancing approach performs work division and task assignment while you do programming,
which means your program pre-determines which thread tests which numbers. A static load balancing approach can
use a block decomposition method or a cyclic decomposition method.
For example, assuming 4 threads and 200000 numbers, task assignment using
domain decomposition method: {0-49999}, {50000-99999}, {100000-149999}, {150000-199999}
cyclic decomposition method (task size: 10 numbers, which means each task-unit has 10 numbers): {1~10, 41~50,
81~90, ...} {11~20, 51~60, 91~100, ...}, {21~30, 61~70, 101~110, ...}, {31~40, 71~80, 111~120, ...}.
The dynamic load balancing approach assigns tasks to threads during execution time. For example, we may let each
thread take a number one by one and test whether the number is a prime number or not. (The recommended size
for one task is 10, which means each thread processes 10 numbers as one unit of task. However, you may choose
another task size if you think it would be better.
(ii) Write a document that reports and the parallel performance of your code. The graphs and tables that show the
execution time when using 1, 2, 4, 6, 8, 10, 12, 14, 16, 32 threads. You should include graphs, for static load
balancing (block), for static load balancing (cyclic), and for dynamic load balancing. Your document also should
mention which CPU type (dualcore? or quadcore?, hyperthreading on?, clock speed) was used for executing your
code. Your document should also include your interpretation of the parallel results.
exec time 1 2 4 ... 32
static (block)
static (cyclic)
[task size : 10
numbers]
dynamic
[task size : 10
numbers]
performace
(1/exec time)
1 2 4 ... 32
static (block)
static (cyclic)
[task size : 10
numbers]
dynamic
[task size : 10
numbers]
(iii) Create a demo video file (.mp4 format) that shows compilation and execution of your codes (Showing execution
using two threads and four threads for each of static(block), static(cyclic), and dynamic cases is enough for the
demo video file.). The size of the demo video file should be less than 30MB. (You may use KakaoTalk that
automatically reduces the video size when trying to transmit the video.)
Problem 2. (i) Given a JAVA source code for matrix multiplication (the source code MatmultD.java is available
on our class webpage), modify the JAVA code to implement parallel matrix multiplication that uses multi-threads.
You should use a static load balancing approach. You may choose either block decomposition method or cyclic
decomposition method. You may also choose the size of each task. Your program should print as output (1) the
execution time of each thread, (2) execution time when using all threads, and (3) sum of all elements in the
resulting matrix. Use the matrix mat500.txt (available on our class webpage) as file input (standard input) for the
performance evaluation. mat500.txt contains two matrices that will be used for multiplication.
command line execution example in cygwin terminal> java MatmultD 6 < mat500.txt
In eclipse, set the argument value and file input by using the menu [Run]->[Run Configurations]->{[Arguments],
[Common -> Input File].
Here, 6 means the number of threads to use, < mat500.txt means the file that contains two matrices is given as
standard input.
(ii) Write a document that reports the parallel performance of your code. The graph that shows the execution time
when using 1, 2, 4, 6, 8, 10, 12, 14, 16, 32 threads. Your document also should mention decomposition method
(block or cyclic?), task size, and CPU type (quadcore?, clock speed) that was used for executing your code.
1 2 4 ... 32
exec time
1 2 4 ... 32
performace
(1/exec time)
(iii) Create a demo video file (.mp4 format) that shows compilation and execution of your codes (showing execution
using two threads and four threads is enough for the demo video file.). The size of the demo video file should be
less than 30MB. (You may use KakaoTalk that automatically reduces the video size when trying to transmit the
video.)
请加QQ:99515681 邮箱:99515681@qq.com WX:codinghelp
- 搜索
-
- 04-10重塑企业生产力!2025金智维企业级智能体暨AI+新品发布会成功举办,引领人机协同新范式
- 04-10数坤科技:引领医疗大模型全能时代
- 04-10“惊蛰号”——全球首艘内河全航程自动驾驶试验船顺利下水
- 04-10喜报丨易智瑞公司通过上海数据交易所数商资格认证
- 04-10打造酒业全面预算管理最佳实践,企云方助力金徽酒打造“数智化”全面预算平台
- 04-09安世亚太电力设备级数字孪生与AI虚拟传感解决方案
- 04-09铼赛智能Edge mini斩获2025法国设计大奖 | 重新定义数字化齿科美学
- 04-09口腔数字化大变革,这场行业大会带你率先把握未来机遇!
- 04-082025 年 Control4 中国区客户启动会在杭州成功举办,开启高端智能家居新征程
- 04-08多模态能力的进化,是AI眼镜成为生活必需品的关键