代写program、代做c/c++编程设计

日期：2024-05-24 08:29

2024.1 Multicore Computing, Project #3

(Due : 11:59pm, May 26)

Submission Rule

1. Create a directory {studentID#}_proj3 (example: 20203601_proj2). In the directory, create

subdirectories ‘prob1’ and ‘prob2’.

2.a For problem 1, write (i)’C with OpenMP’ source code prob1.c, and (ii)a document that reports

the parallel performance of your code into the directory "prob1". Insert the files (i), and (ii)

into the subdirectory ‘prob1’.

2.b For problem 2, write (i) ‘C with OpenMP’ source code prob2.c , and (ii) a document that

reports the parallel performance of your code. Insert (i) and (ii) into the subdirectory ‘prob2’.

2.c For problem 3, insert demo video files (.mp4) into the directory {studentID#}_proj3.

3. zip the directory {studentID#}_proj3 and submit the zip file into eClass homework board.

※ If possible, use quad-core/hexa-core/octa-core CPU (or CPU with more cores) rather than dual-core CPU for

your experimentation, which will better show the performance gains of the parallelism.

[Problem 1] In project 1, we looked at the JAVA program that computes the number of ‘prime numbers’ between 1

and 200000. The parallel implementation of a static approach based on bad work decomposition (i.e. just dividing

the entire range of the numbers into k consecutive sub-ranges, where k is the number of threads) may not give

satisfactory performance because (i) higher ranges have fewer primes and (ii) larger numbers are harder (i.e. taking

longer time) to test whether they are prime or not. Therefore thread workloads may become uneven and hard to

predict. For better performance, we implemented dynamic load balancing approach in project 1 where each thread

takes a number one by one and test whether the number is a prime number.

(i) Write ‘C with OpenMP’ code that computes the number of prime numbers between 1 and 200000. Your program

should take two command line arguments: scheduling type number (1 = “static with default chunk size”, 2 =

“dynamic with default chunk size”, 3 = “static with chunk size 10”, 4 = “dynamic with chunk size 10”), and

number of threads (1, 2, 4, 6, 8, 10, 12, 14, 16) as program input argument. Use schedule(static) ,

schedule(dynamic) , schedule(static, 10) and schedule(dynamic, 10). Your code should print

the execution time as well as the number of the prime numbers between 1 and 200000.

command line execution: > a.out scheduling_type# #_of_thread

execution example> a.out 1 8 <---- this means the program use “schedule(static)” using 8 threads.

(ii) Write a document (in PDF file format) 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 threads. There should be at least four graphs that show the

result of static and dynamic scheduling policies. The document that reports the parallel performance should contain

(a) in what environment (e.g. CPU type, memory size, OS type ...) the experimentation was performed, (b) tables

and graphs that show the execution time (unit:milisecond) for thread number = {1,2,4,6,8,10,12,14,16}. (c) The

document should also contain explanation on the results and why such results can be obtained.

exec time

(unit: ms)

chunk

size

1 2 4 6 8 10 12 14 16

static default

dynamic default

static 10

dynamic 10

performace

(1/exec time)

chunk

size

1 2 4 6 8 10 12 14 16

static default

dynamic default

static 10

dynamic 10[Problem 2] Parallelize prob2.c (see our class webpage project 3 announcement to access prob2.c) using

OpenMP. Your program should take three command line arguments: scheduling type number (1=static, 2=dynamic,

3=guided), chunk size, and number of threads as program input argument. Your code should print the execution time

and the result of PI calculation. Assume the number of steps num_steps = 10000000.

command line execution: > a.out scheduling_type# chunk_size #_of_thread

execution example> a.out 2 4 8 <---- this means dynamic scheduling (chunk size = 4) using 8 threads.

(i) submit the OpenMP source code prob2.c

(ii) Write a document (in PDF file format) that reports the parallel performance of your code. Your report should

contain (a) following tables and graphs that shows information in the tables, and (b) brief explanation and

interpretation on the results (including why such results can be obtained).

execution time

(unit:ms)

chunk

size

1 2 4 6 8 10 12 14 16

static

dynamic 1

guided

static

dynamic 5

guided

static

dynamic 10

guided

static

dynamic 100

guided

performace

(1/exec time)

chunk

size

1 2 4 6 8 10 12 14 16

static

dynamic 1

guided

static

dynamic 5

guided

static

dynamic 10

guided

static

dynamic 100

guided

[Problem 3] Create a demo video file (.mp4 format) that shows compilation and execution of your source files

(prob1.c, prob2.c). The size of the demo video file should be less than 50MB.