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We are going to be working on a CERN project called Drive_God_Lin (more info soon...)

Team Members

  1. Sezar Gantous
  2. Stephanie Bourque
  3. Dylan Segna
  4. Email All


Assignment 1


I decided to profile CERN project - Drive_God_Lin. After gprof the project with the test data provided I learned the following:

(summery of gprof)

Each sample counts as 0.01 seconds.
 %   cumulative   self              self     total          
time   seconds   seconds    calls  ms/call  ms/call  name   
39.98     26.68    26.68      524    50.92    50.92  ordres_
37.42     51.65    24.97   314400     0.08     0.08  zfunr_
12.69     60.12     8.47   314400     0.03     0.03  cfft_

As you can see, most the program's time is spent in the ordres() subroutine and zfunr() subroutine; both are localed in the fortran portion of the program (there is a c portion as well).

Furthermore, this program is already parallelized using openmp; which means it may be farther parallelized using cuda technology.

In these two subroutines (specially in orders()) there are a lot of nested loops, if statements, goto's, and even some sore of a search algorithm (in orders() only) that I'm certain it could be notably improved using cuda technology.



For assignment one I profiled a closest pair algorithm. The source code can be found here:

I was able to run the code successfully on Matrix and I believe it is a good candidate to parallelize. The closest() function generally eats up the most time and I believe that most of its remedial processes could be done by the GPU.

A useful reference site to help explain closest pair algorithms:

Assignment 2

Assignment 3