Intel Math Kernel Library Changelog

What's new in Intel Math Kernel Library 11.2

• Intel MKL now provides optimizations for all Intel® Atom™ processors that support Intel® Streaming SIMD Extensions 4.1 (Intel® SSE4.1) and Intel® Streaming SIMD Extensions 4.2 (Intel® SSE4.2) instruction sets
• Introduced support for Intel® Advanced Vector Extensions 512 (Intel® AVX-512) instruction set with limited optimizations in BLAS, DFT and VML
• Introduced Verbose support for BLAS and LAPACK domains, which enables users to capture the input parameters to Intel MKL function calls
• Introduced support for Intel® MPI Library 5.0
• Introduced the Intel Math Kernel Library Cookbook (http://software.intel.com/en-us/mkl_cookbook) , a new document that describes how to use Intel MKL routines to solve certain complex problems
• Introduced the MKL_DIRECT_CALL or MKL_DIRECT_CALL_SEQ compilation feature that provides ?GEMM small matrix performance improvements for all processors (see the Intel® Math Kernel Library User's Guide for more details)
• Added the ability to link a Single Dynamic Library (mkl_rt) on Intel® Many Integrated Core Architecture (Intel® MIC Architecture)
• Added a customizable error handler.See the Intel Math Kernel Library Reference Manual description of mkl_set_exit_handler() for further details
• Extended the Intel® Xeon Phi™ coprocessor Automatic Offload feature with a resource sharing mechanism.See the Intel Math Kernel Library Reference Manual for the description of mkl_mic_set_resource_limit() function and the MKL_MIC_RESOURCE_LIMIT environment variable for further details
• Parallel Direct Sparse Solver for Clusters:
• Introduced Parallel Direct Sparse Solver for Clusters, a distributed memory version of Intel MKL PARDISO direct sparse solver
• Improved performance of the matrix gather step for distributed matrices
• Enabled reuse of reordering information on multiple factorization steps
• Added distributed CSR format, support of distributed matrices, RHS, and distributed solutions
• Added support of solving of systems with multiple right hand sides
• Added cluster support of factorization and solving steps
• Added support for pure MPI mode and support for single OpenMP thread in hybrid configurations
• BLAS:
• Improved threaded performance of ?GEMM for all 64-bit architectures supporting Intel® Advanced Vector Extensions 2 (Intel® AVX2)
• Optimized ?GEMM, ?TRSM, DTRMM for the Intel AVX-512 instruction set
• Improved performance of ?GEMM for outer product [large m, large n, small k] and tall skinny matrices [large m, medium n, small k] on Intel MIC Architecture
• Improved performance of ?TRSM and ?SYMM in Automatic Offload mode on Intel MIC Architecture
• Improved performance of Level 3 BLAS functions for 64-bit processors supporting Intel AVX2
• Improved ?GEMM performance on small matrices for all processors when MKL_DIRECT_CALL or MKL_DIRECT_CALL_SEQ is defined during compilation (see the Intel® Math Kernel Library User’s Guide for more details )
• Improved performance of DGER and DGEMM for the beta=1, k=1 case for 64-bit processors supporting Intel SSE4.2, Intel® Advanced Vector Extensions (Intel® AVX), and Intel AVX2 instruction sets
• Optimized (D/Z)AXPY for the Intel AVX-512 instruction set
• Optimized ?COPY for Intel AVX2 and AVX512 instruction sets
• Optimized DGEMV for Intel AVX-512 instruction set
• Improved performance of SSYR2K for 64-bit processors supporting Intel AVX and Intel AVX2
• Improved threaded performance of ?AXPBY for all Intel processors
• Improved DTRMM performance for the side=R, uplo={U,L}, transa=N, diag={N,U} cases for Intel AVX-512
• LINPACK:
• Improved performance of matrix generation in the heterogeneous Intel® Optimized MP LINPACK Benchmark for Clusters
• Intel MIC Architecture offload option of the Intel Optimized MP LINPACK Benchmark for Clusters package now supports Intel AVX2 hosts
• Improved performance of the Intel Optimized MP LINPACK for Clusters package for 64-bit processors supporting Intel AVX2
• LAPACK:
• Improved performance of ?(SY/HE)RDB
• Improved performance of ?(SY/HE)(EV/EVD) when eigenvectors are needed
• Improved performance of ?(SY/HE)(EV/EVR/EVD) when eigenvectors are not needed
• Improved performance of ?GELQF,?GELS and ?GELSS for underdetermined case (M less than N)
• Improved performance of ?GEHRD,?GEEV and ?GEES
• Improved performance of NaN checkers in LAPACKE interfaces
• Improved performance of ?GELSX, ?GGSVP
• Improved performance of ?GETRF
• Improved performance of (S/D)GE(SVD/SDD) when M>=N and singular vectors are not needed
• Improved performance of ?POTRF UPLO=U in Automatic Offload mode on Intel MIC Architecture
• Added Automatic Offload for ?SYRDB on Intel MIC Architecture, which speeds up ?SY(EV/EVD/EVR) when eigenvectors are not needed
• PBLAS and ScaLAPACK:
• Enabled Automatic Offload in P?GEMM routines for large distribution blocking factors
• Sparse BLAS:
• Optimized SpMV kernels for Intel AVX-512 instruction set
• Added release example for diagonal format use in Sparse BLAS
• Improved Sparse BLAS level 2 and 3 performance for systems supporting Intel SSE4.2, Intel AVX and Intel AVX2 instruction sets
• Intel MKL PARDISO:
• Added the ability to store Intel MKL PARDISO handle to the disk for future use at any solver stage
• Added pivot control support for unsymmetric matrices and out-of-core mode
• Added diagonal extraction support for unsymmetric matrices and out-of-core mode
• Added example demonstrating use of Intel MKL PARDISO as iterative solver for non-linear systems
• Added capability to free memory taken by original matrix after factorization stage if iterative refinement is disabled
• Improved memory estimation of out-of-core (OOC) portion size for reordering algorithm leading to improved factorization-solve performance in OOC mode
• Improved message output from Intel MKL PARDISO
• Added support of zero pivot during factorization for structurally symmetric cases
• Poisson library:
• Added example demonstrating use of the Intel MKL Poisson library as a preconditioner for linear systems solves
• Extended Eigensolver:
• Improved message output
• Improved examples
• Added input and output iparm parameters in predefined interfaces for solving sparse problems
• FFT:
• Optimized FFTs for the Intel AVX-512 instruction set
• Improved performance for non-power-of-2 length on Intel® MIC Architecture
• VML: Added v[d|s]Frac function computing fractional part for each vector element
• VSL RNG:
• Added support of ntrial=0 in Binomial Random Number Generator
• Improved performance of MRG32K3A and MT2203 BRNGs on Intel MIC Architecture
• Improved performance of MT2203 BRNG on CPUs supporting Intel AVX and Intel AVX2 instruction sets
• VSL Summary Statistics:
• Added support for group/pooled mean estimates (VSL_SS_GROUP_MEAN/VSL_SS_POOLED_MEAN)
• Data Fitting: Fixed incorrect behavior of the natural cubic spline construction function when number of breakpoints is 2 or 3
• Introduced an Intel MKL mode that ignores all settings specified by Intel MKL environment variables
• User can set up the mode by calling mkl_set_env_mode() routine which directs Intel MKL to ignore all environment settings specific to Intel MKL so that all Intel MKL related environment variables such as MKL_NUM_THREADS, MKL_DYNAMIC, MKL_MIC_ENABLE and others are ignored; users can instead set needed parameters via Intel MKL service routines such as mkl_set_num_threads() and mkl_mic_enable()