MKL Libraries
MKL Libraries
The Intel Math Kernel Library (MKL) is a very useful package. It provides optimised and documented versions of a large number of common mathematical routines. It supports both C and Fortran interfaces for most of these. It features the following routines:
- Basic Linear Algebra Subprograms (BLAS); vector, matrix-vector, matrix-matrix operations.
- Sparse BLAS Levels 1, 2, and 3.
- LAPACK routines for linear equations, least squares, eigenvalue, singular value problems and Sylvester's equations problems.
- ScaLAPACK Routines.
- PBLAS routines for distributed vector, matrix-vector and matrix-matrix operation.
- Direct and iterative sparse solver routines.
- Vector Mathematical Library (VML) for computing mathematical functions on vector arguments.
- Vector Statistical Library (VSL) for generating pseudorandom numbers and for performing convolution and correlation.
- General Fast Fourier Transform (FFT) functions for fast computation of Discrete FFTs.
- Cluster FFT functions.
- Basic Linear Algebra Communication Subprograms (BLACS)
- GNU multiple precision arithmetic library.
If your code depends on standard libraries such as BLAS or LAPACK, it is recommended that you link against the MKL versions for optimal performance.
Parallelism in a program can be achieved at the process level as in most MPI development or at the thread level as in OpenMP development, or in some mix of these approaches, a so-called hybrid code. The most common mode of development on our systems is MPI based, as this allows you write programs which can run across many nodes. Often such codes will want to call routines provided by MKL. However many of these routines are themselves parallel so at the node level one is left with two levels of parallelism contenting with one and other. To eliminate this the MKL module sets the environment variable MKL_NUM_THREADS=1. If you are writing hybrid code or pure OpenMP code that uses MKL you may need to override this setting. Chapter 6 of the MKL userguide explains in detail how this and other related environment variables can be used. Note if you have used a version of MKL older than 10.0 you should be aware that MKL's method for controlling thread numbers has changed.
This issue can also be addressed by explicitly linking the sequential version of the libraries which can be found in the $MKLROOT/lib/intel64 directory and are identified by a _sequential in the name. Note you are also required to link the pthread library.
Extensive high quality MKL documentation can be found in the $MKLROOT/doc. Remember that when a code is linked against MKL it will be necessary for you to have the MKL module loaded via the submit script when running the code.
