WindRosePOC

CMPE275 : Project1 Submission Repository

-Actual data size: ~200GB not included in the folder.
-Sample data size: ~0.5GB included in the project Data folder.
-Performance tested on: 2.5GHz dual-core Intel Core i5 processor (Turbo Boost up to 3.1GHz) with 3MB L3 cache
-Instructions to Run the Project:
   1.Clone the repo
   2.cd /WindRosePOC
   3.cd src_MPI : To run various algorithms using MPI techniques.
   4.cd src_OpenMP : To run various algorithms using openMP techniques.

Information about source files:
Source folder: src_MPI
   1.Serial.cpp : Procedural serial code with the usage of local containers to store intermediary data in vectors and 2Darrays. 
      * g++ -std=c++1y Serial.cpp
      * ./a.out
      * Observation : Takes the longest time to process the files. (~60 seconds)
   2.SerialModified.cpp : Procedural serial code without the usage of local containers to store intermediary data.
      * g++ -std=c++1y SerialModified.cpp
      * ./a.out
      * Observation : Takes considerably less time to process the files. (~15 seconds for two station ids)
   3.MPITaskDivision.cpp : Parallelized code using OpenMPI Send and receive prototypes that spawns two processes 
                           to process data for two station ids.
      * mpic++ -std=c++1y MPITaskDivision.cpp
      * mpirun -np 2 a.out
      * Observation : Gives 2x performance when compared to the Serial code. (~8 seconds for two station ids)
   4.MP+MPI.cpp : Hybrid parallelized code optimized using Open MPI send and receive prototypes and openMP parallel for 
                  pragma directives.
      * mpic++ -fopenmp -std=c++1y MP+MPI.cpp
      * mpirun -np 3 a.out
      * Observation : Gives 2x performance. (~7 seconds)


Description of OpenMP Files:
src_OpenMP/Serial01.cpp : Algorithm# 1 Storing Filtered Raw Data in a Local Container 
src_OpenMP/Parallel01_01.cpp : Strategy# 1 Parallelising data processing using local containers
src_OpenMP/Parallel01_02.cpp : Strategy# 2 Parallelising data read and processing
src_OpenMP/Parallel01_03.cpp : Strategy# 3 Parallelising data processing by accessing elements according to the fixed strip width
src_OpenMP/Serial02.cpp : Algorithm# 2  Without Using a Local Container for Storing Input Raw Data
src_OpenMP/Parallel02_01: Strategy# 1 Parallelising data read and processing using 2-D local containers
src_OpenMP/Parallel02_02: Strategy# 2 Parallelising data read and processing using 3-D shared container

Instructions for compiling OpenMP code:

   1.g++ -fopenmp -std=c++11 Parallel01_01.cpp -o Parallel01_01.O
   2.To run : ./Parallel01_01.O
   3.Example station ids to give at run time : "E3467", "A28";

Swig Instructions:

1. Make an interface file named "filname.i".
2. Add the module name that you want to use in your higher level language(like python).
3. Add required header files and functions that you want to use in the %{""""""" %} section.
4. Now compile the file using swig.

Compilation with Swig Instructions:

Use the following commands for compilation (Don't include "" in your commands)

1. swig -c++ -python "filename.i"
2. g++ -c -fpic -fopenmp "filename.cpp"
3. g++ -c -fpic -fopenmp "filename_wrap.cxx" -I "path to <Python.h>"
4. g++ -shared "cpp oject file" "wraper object file" -o "_outpufile.so" -fopenmp
5. Go to Python console(use command python).

Using Swig in higher level language

1. import outputfile
2. outputfile.callFunction()