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HeadCrab

726 bytes added, 11:31, 5 April 2016
Intro
== Intro ==
 
For this assignment I will be focusing on the Linear Algebra routines. I will use workshop six to demonstrate how BLAS can be used to significantly speed
up the calculations and compare them to other parallelization methods.
 
<u>Compared to</u>
#Serial
#Cilk
#Cilk with array notation and reduction
#Cilk with SIMD and reduction
#MKL CBLAS level 3
#CUDA CUBLAS level 3
#TBB
#OpenMP
 
 
'''Intel Math Kernel Library'''
This means that developers would have to make minor changes to their programs when
switching to MKL.
 
Intel MKL is also compatible with your choice of compilers, languages, operating systems, linking and threading models. One library solution across multiple environments means only one library to learn and manage.
For this assignment I will be focusing on the Linear Algebra routines.
 
== Source code ==
'''How to enable Intel MKL'''
 
<u>#include <mkl.h></u>
<u>Command line</u>
[[File:mkl.png]]
 
'''Fig 1 - Enable MKL'''
 
== Source code ==
 
[[File:mklcode.png]]
 
'''Fig 2 - MKL'''
 
 
 
 
[[File:TBB.png]]
 
'''Fig 3 - TBB'''
 
 
 
[[File:cuda.png]]
 
'''Fig 4 - CUDA'''
 
 
 
 
[[File:omp.png]]
 
'''Fig 5 - OpenMP'''
== Useful Link ==
# https://software.intel.com/en-us/intel-mkl/details
# https://software.intel.com/en-us/node/468380
# https://software.intel.com/sites/default/files/managed/4a/d6/mkl_11.2.1_lnx_userguide.pdf
== Progress ==
 
[[File:Data.png]]
 
'''Fig 6 - Recorded times'''
 
 
 
 
[[File:rlachart.png]]
 
'''Fig 7 - Graph of times'''
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