代做Cross-Platform留学生作业、代写OptimisedCode作业、代写C/C++程序作业、代做C/C++课程设计作业
Scalable Cross-Platform Software Design: Optimisation Coursework#1
25% of the module mark: Marking Scheme on Moodle
Part 1: Code Optimisation.
Summary: On Moodle there is a very poorly written computational program, ToBeOptimisedCode.cpp. It is a “made
up“ code that doesn’t actually do anything useful, but it has many features common to a range of large-scale
numerical simulation codes in engineering. This is a rather poorly written code for a number of reasons!
I compiled it with g++ -o task ToBeOptimisedCode.cpp and ran it with time./task on Jenna node comp00. The run
time data on the screen was,
real 0m14.322s
user 0m13.998s
sys 0m0.022s
Objective: Your task is to improve the C coding of the algorithm to minimise the run time; you must not change the
code’s function in any way. Changing language, direct use of machine code or parallelisation is not allowed.
Please make sure you get exactly the same results: run the original code as above and make a copy of the file
produced, data_out. Then for any new version check for identical results by doing,
diff data_out original_ data_out
You should get no differences at all.
Specific Assessment Requirements:
Submission through the Moodle page by the deadline shown there. Submit a single zip file containing all files required
to simply load and run your project. A brief pdf document is required that briefly describes:
a) A copy of the original listing annotated with brief comments to identify poor programming style and where you
think there is scope to improve the code: comments should cover both “coding bad practice” and “speedup”
possibilities.
b) Your optimised code (suitably documented).
c) A brief (1/2 page) pdf summarising the results of your optimisation including discussion of modifications that
you tried that did not yield benefits and any resources (e.g. profiling) that you drew on.
Part 2: Characterisation of the Jenna platform.
Setup a very simple serial C program to add two double precision arrays.
a[i]=b[i]+c[i+offset] for all 0<i<n-offset.
The arrays are to be dynamically allocated. The arrays b and c are to be initialised so that b[i]=c[i]=i
Time the execution of the loop above (i.e. excluding the array setup and initialisation).
To get reasonable timing accuracy it may be necessary to wrap an outer loop around the above loop so as to repeat
the above sum-loop many times.
To do the timings you might use gettimeofday, but there are alternatives – if you trust them and they are sufficiently
accurate.
#include <sys/time.h>
struct timeval start_time,end_time;
gettimeofday(&start_time,NULL);
// Your code to time
gettimeofday(&end_time,NULL);
cout<<"\n\ngettimeofday wall time="<<
end_time.tv_sec - start_time.tv_sec+(end_time.tv_usec-start_time.tv_usec)/1e6;
Specific Assessment Requirements:http://www.6daixie.com/contents/13/2093.html
a) With offset=0, investigate and plot the timings for different n.
b) Based upon the previous results, select a few "interesting" values of n and repeat for different offset values.
c) Now repeat (a) and (b) using OpenMP to parallelise the loop.
d) You should expect that static scheduling will give the best performance for (c). Please design, implement nd
characterise an alternative loop-based test where dynamic scheduling might prove advantageous.
Required results: Submit both your test codes and the results obtained and in a brief report (< 2pages excluding
graphs) summarise, discuss and explain what you observe.
因为专业，所以值得信赖。如有需要，请加QQ：99515681 或邮箱：[email protected]
微信：codinghelp