Changes

There are many different implementations of these subprograms available. These different implementations are created with different purposes or platforms in mind. Intel's oneAPI implementation heavily focuses on performance, specifically with x86 and x64 in mind.

[[File:BLAS.png]]

A sparse matrix is matrix that is mostly empty, these are common in machine learning applications. Using standard linear algebra functions would lead to poor performance and would require greater amounts of storage. Specially written sparse linear algebra functions have better performance and can better compress matrices to save space.

==== Fast Fourier Transforms ====

Enabling technology today such as most digital communications, audio compression, image compression, satellite tv, FFT is at the heart of it.

A fast Fourier transform (FFT) is an algorithm that computes the discrete Fourier transform (DFT) of a sequence, or its inverse (IDFT).

==== Random Number Generator ====

All RNG routines can be categorized in several different categories.

The generation of numbers is done in 2 steps:

Data Fitting routines use the following workflow to process a task:

Data Fitting functions:

==== Summary Statistics ====

Summary Statistics calculate:

Additional Features:

==== Vector Math ====

There are two main set of functions for the Vector Math library that the intel MKL uses they are:

=== Code Samples ===

[File:https://wiki.cdot.senecacollege.ca/w/imgs/Intel_Math_Kernel_Library.pdf]