Linear Algebra

Intel® MKL BLAS provides optimized vector-vector (Level 1), matrix-vector (Level 2) and matrix-matrix (Level 3) operations for single and double precision real and complex types. Level 1 BLAS routines operate on individual vectors, e.g., compute scalar product, norm, or the sum of vectors. Level 2 BLAS routines provide matrix-vector products, rank 1 and 2 updates of a matrix, and triangular system solvers. Level 3 BLAS level 3 routines include matrix-matrix products, rank k matrix updates, and triangular solvers with multiple right-hand sides.

Intel® MKL LAPACK provides extremely well-tuned LU, Cholesky, and QR factorization and driver routines that can be used to solve linear systems of equations. Eigenvalue and least-squares solvers are also included, as are the latest LAPACK 3.3.1 interfaces and enhancements.

If your application already relies on the BLAS or LAPACK functionality, simply re-link with Intel® MKL to get better performance on Intel and compatible architectures.

Fast Fourier Transforms

Intel® MKL FFTs include many optimizations and should provide significant performance gains over other libraries for medium and large transform sizes. The library supports a broad variety of FFTs, from single and double precision 1D to multi-dimensional, complex-to-complex, real-to-complex, and real-to-real transforms of arbitrary length. Support for both FFTW* interfaces simplifies the porting of your FFTW-based applications.

Vector Math

Intel® MKL provides optimized vector implementations of computationally intensive core mathematical operations and functions for single and double precision real and complex types. The basic vector arithmetic operations include element-by-element summation, subtraction, multiplication, division, and conjugation as well as rounding operations such as floor, ceil, and round to the nearest integer. Additional functions include power, square root, inverse, logarithm, trigonometric, hyperbolic, (inverse) error and cumulative normal distribution, and pack/unpack. Enhanced capabilities include accuracy, denormalized number handling, and error mode controls, allowing users to customize the behavior to meet their individual needs.

Statistics

Intel® MKL includes random number generators and probability distributions that can deliver significant application performance. The functions provide the user the ability to pair Random-Number Generators such as Mersenne Twister and, Niederreiter with a variety of Probability Distributions including Uniform, Gaussian and Exponential.

Intel® MKL also provides computationally intensive core/building blocks for statistical analysis both in and out-of-core. This enables users to compute basic statistics, estimation of dependencies, data outlier detection, and missing value replacements. These features can be used to speed-up applications in computational finance, life sciences, engineering/simulations, databases, and other areas.

Data Fitting

Intel® MKL includes a rich set of splines functions for 1-dimensional interpolation. These are useful in a variety of application domains including data analytics (e.g. histograms), geometric modeling and surface approximation. Splines included are linear, quadratic, cubic, look-up, stepwise constant and user-defined.

What’s New

Conditional Bitwise Reproducible Results

When exact reproducible calculations are required, Intel® MKL gives developers control over the tradeoffs to maximize performance across a set of target processors while delivering identical floating point results

Optimized for Intel® Advanced Vector Extensions 2 (Intel® AVX2), Intel® microarchitecture code name Ivy Bridge and Intel® Many Integrated Core Architecture (Intel® MIC Architecture) processor architectures

Intel® MKL is optimized for the latest and upcoming processor architectures to deliver the best performance in the industry. Support for the new digital random number generator provides truly random seeding of statistical calculations.

Automatic offload and compute load balancing between Intel® Xeon® processor and Intel® Xeon Phi™ coprocessors

For Linear Algebra functionality, Intel® MKL can automatically determine the best way to utilize a system containing one or more Intel® MIC processors. The developer simply calls an MKL function and doesn’t have to worry about the details.

Data Fitting functions

A rich set of splines are now included to optimize 1-dimensional interpolation calculations used in a variety of application domains

Conditional Bitwise Reproducible Results

When exact reproducible calculations are required, Intel® MKL gives developers control over the tradeoffs to maximize performance across a set of target processors while delivering identical floating point results

Optimized for Intel® Advanced Vector Extensions 2 (Intel® AVX2), Intel® microarchitecture code name Ivy Bridge and Intel® Many Integrated Core Architecture (Intel® MIC Architecture) processor architectures

Intel® MKL is optimized for the latest and upcoming processor architectures to deliver the best performance in the industry. Support for the new digital random number generator provides truly random seeding of statistical calculations.

Automatic offload and compute load balancing between Intel® Xeon® processor and Intel® Xeon Phi™ coprocessors

For Linear Algebra functionality, Intel® MKL can automatically determine the best way to utilize a system containing one or more Intel® MIC processors. The developer simply calls an MKL function and doesn’t have to worry about the details.

Data Fitting functions

A rich set of splines are now included to optimize 1-dimensional interpolation calculations used in a variety of application domains