Difference between revisions of "GPU610/Team DAG"
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Profile of the Drive_God_lin program utilizing only 1 core/thread on the CPU (forcing serialized execution of all OpenMP Pragmas in the C+ and Fortran code) showed 4 primary targets to rewrite using CUDA kernels. | Profile of the Drive_God_lin program utilizing only 1 core/thread on the CPU (forcing serialized execution of all OpenMP Pragmas in the C+ and Fortran code) showed 4 primary targets to rewrite using CUDA kernels. | ||
All 4 of these procedure calls are part of the Fortran library included for executing the analysis. There are some portions of the 'main' method in the Drive_God_lin.c code which include a parallel OpenMP pragma, and this could also be tuned for some improvement for initialization of the data arrays, but may not provide improvement for the reading of the data file. | All 4 of these procedure calls are part of the Fortran library included for executing the analysis. There are some portions of the 'main' method in the Drive_God_lin.c code which include a parallel OpenMP pragma, and this could also be tuned for some improvement for initialization of the data arrays, but may not provide improvement for the reading of the data file. | ||
| − | |||
| + | (Each sample counts as 0.01 seconds.) | ||
| − | |||
| − | + | {| class="wikitable" border="1" | |
| + | |+ Methods most likely to offer parallel improvements via CUDA kernels (Top 5 based on Flat Profile). | ||
| + | (Each sample counts as 0.01 seconds.) | ||
| + | ! %Time !! Cum Sec !! Self Sec !! Calls !! Self ms/Call !! Total ms/call !! Name | ||
| + | |- | ||
| + | | 47.66 || 9.99 || 9.99 || 314400 || 0.03 || 0.03 || zfunr_ | ||
| − | + | |- | |
| + | | 30.45 || 16.73 || 6.38 || 524 || 12.18 || 12.18 || ordres_ | ||
| + | |- | ||
| − | + | | 10.84 || 18.64 || 2.27 || 314400 || 0.01 || 0.01 || cfft_ | |
| − | + | |- | |
| − | + | | 3.53 || 19.38 || 0.74 || 314400 || 0.00 || 0.04 || tunelasr_ | |
| − | + | |- | |
| − | + | | 3.34 || 20.08 || 0.70 || 1048 || 0.67 || 13.42 || spectrum_ | |
| + | |} | ||
| + | |||
| + | The method call with the highest time per call is the ordres_ method. This indicates it may be the best target for a parallel implementation. | ||
=== Assignment 2 === | === Assignment 2 === | ||
=== Assignment 3 === | === Assignment 3 === | ||
Revision as of 13:28, 4 March 2013
GPU610/DPS915 | Student List | Group and Project Index | Student Resources | Glossary
Contents
Team DAG
Team Members
- Chris Schreiber, Team Lead
Progress
Assignment 1
Project selection discussed with Chris Szalwinski. Configuring local working environment and hardware for working with the CERN project source code.
Profile of the Drive_God_lin program utilizing only 1 core/thread on the CPU (forcing serialized execution of all OpenMP Pragmas in the C+ and Fortran code) showed 4 primary targets to rewrite using CUDA kernels. All 4 of these procedure calls are part of the Fortran library included for executing the analysis. There are some portions of the 'main' method in the Drive_God_lin.c code which include a parallel OpenMP pragma, and this could also be tuned for some improvement for initialization of the data arrays, but may not provide improvement for the reading of the data file.
(Each sample counts as 0.01 seconds.)
| %Time | Cum Sec | Self Sec | Calls | Self ms/Call | Total ms/call | Name |
|---|---|---|---|---|---|---|
| 47.66 | 9.99 | 9.99 | 314400 | 0.03 | 0.03 | zfunr_ |
| 30.45 | 16.73 | 6.38 | 524 | 12.18 | 12.18 | ordres_ |
| 10.84 | 18.64 | 2.27 | 314400 | 0.01 | 0.01 | cfft_ |
| 3.53 | 19.38 | 0.74 | 314400 | 0.00 | 0.04 | tunelasr_ |
| 3.34 | 20.08 | 0.70 | 1048 | 0.67 | 13.42 | spectrum_ |
The method call with the highest time per call is the ordres_ method. This indicates it may be the best target for a parallel implementation.
