View source for GPU610/Team DAG

{{GPU610/DPS915 Index | 20131}}
= Team DAG =
== Team Members == 
# [mailto:cschreiber@myseneca.ca?subject=DPS915-Project Chris Schreiber], Team Lead
[mailto:cschreiber@myseneca.ca?subject=DPS915-Projectt Email All]

== 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. 

(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_
|}
 
Drive_God_lin.c - Contains OpenMP pragma for parallelization already.  This should be converted over to a CUDA kernel to across Many -Cores instead of the avail CPU threads (or specified  OPT_NUM_THREADS = 1).   Because the test run used 1 optimal number of threads, the program executes serially.  This produces a profile with the maximum percentages of time being used by 3 of the Fortran methods.

The first priority is to examine how the  parallel pragma in the Drive_God_lin.c program divides up the task in to more CPU threads (forking), and if that process or smaller steps of that process can be re-written to be called by CUDA threads.

A parallel region is a block of code that will be executed by multiple threads. This is the fundamental OpenMP parallel construct.

From the Drive_God_lin.c  code:

while (readDrivingTerms(drivingTermsFile, &turns, dataFilePath, sizeof(dataFilePath))) {

... /* loop containing code to parse datafile terms from the DrivingTermsFilePath. */

/* includes File IO
#pragma omp parallel for private(i, horizontalBpmCounter, verticalBpmCounter, kk, maxamp, calculatednattunex, calculatednattuney)

  for (i = pickstart; i < maxcounthv; ++i) {

...

    // call to sussix4noise  Fortran program code.

}

OpenMP     provides three directives that are merely conveniences:

PARALLEL      DO / parallel for
PARALLEL      SECTIONS
PARALLEL      WORKSHARE (fortran only)

For     the most part, these directives behave identically to an individual     PARALLEL directive being immediately followed by a separate work-sharing     directive.
Most     of the rules, clauses and restrictions that apply to both directives are     in effect. See the OpenMP API for details.
An     example using the PARALLEL DO / parallel for combined directive is shown     below.

eg: #pragma omp parallel for \

   shared(a,b,c,chunk) private(i) \

   schedule(static,chunk)

  for (i=0; i < n; i++)

    c[i] = a[i] + b[i];

 

The private list for the variables, and no shared - identifies that each of the threads created for this parallel execution will have their own copy of each variable.

 

 

 

The important Loop prior to the Fortran Call  is below:

for (kk = 0; kk < MAXTURNS; ++kk) {

                doubleToSend[kk] = matrix[horizontalBpmCounter][kk];

                doubleToSend[kk + MAXTURNS] = matrix[verticalBpmCounter][kk];

                doubleToSend[kk + 2 * MAXTURNS] = 0.0;

                doubleToSend[kk + 3 * MAXTURNS] = 0.0;

            }

 

            /* This calls the external Fortran code (tbach) */

            sussix4drivenoise_(&doubleToSend[0], &tune[0], &amplitude[0], &phase[0], &allfreqsx[0], &allampsx[0], &allfreqsy[0], &allampsy[0], sussixInputFilePath);

 

This sets the array of data 'doubleToSend[]' from the data buffers read from the data files previously.

The later restriction on the efficiency of the existing code in addition to the file IO is the inclusion of a CRITICAL pragma, which restricts the execution of that block of code to 1 thread at a time.  This may be difficult to convert or optimize for CUDA since these sections of code appear to make frequent use if file IO, and parallel IO may not be available in the operating environment.

=== Assignment 2 ===
=== Assignment 3 ===