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→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 calculationsand 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
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.
'''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'''
