Manual cpu dispatch may be used to write code that will be executed only on Intel processors with support for Intel® Advanced Vector Extensions, such as 2nd generation Intel® Core™ processors (formerly code named “Sandy Bridge”), 3rd generation Intel® Core™ processors (formerly code named "Ivy Bridge") or future processors with support for Intel Advanced Vector Extensions 2..
Use the Intel Compiler 11.1 or 12.0 with the switch /QxAVX (Windows*) or -xavx (Linux*) to compile applications for Intel® Advanced Vector Extensions (Intel® AVX).
This article provides an overview of the methods available in Intel® Parallel Composer, along with a comparison of their key benefits.
Get a high-level overview of the automatic parallelization and vectorization methods used by the Intel® C++ and Fortran Compilers.
This article contains a training materials (in PDF format) on Intel® MKL Sparse Solvers which includes details of PARDISO/DSS, Iterative Solvers features and performance.
Sparse BLAS routines can be useful to implement iterative methods for solving large sparse systems of equations or eigenvalue problems
Introduction and functionalities of Intel MKL
Webinar slides - Dr. Tim Mattson, Principal Engineer at Intel's Microprocessor Technology Labs, will lead a webinar focused on actual code and the parallel programming APIs available to software developers. Tim will begin with an overview of the high level issues that apply to the task of creating a parallel program and then move on to consider the most commonly used parallel algorithms. He will then discuss the major parallel programming APIs (OpenMP*, MPI, and Windows* threads) showing how they are used with different algorithms and different platforms. After attending this webinar, developers should be conversant with major concurrent APIs and algorithms and be well positioned to start incorporating these techniques in their applications.
Webinar slides - New innovations bring new challenges. For many C/C++ developers, introducing parallelism means spending hours tuning an application for multicore performance. Learn techniques with a new performance tuning profiler found in Intel® Parallel Studio and quickly identify performance issues. Using application source code, Intel parallelism expert Gary Carleton demonstrates how developers can quickly solve the three most common performance issues: (1) bottlenecks, (2) locks and waits, and (3) amount and locations of threads. Windows* developers now have a tool that brings new levels of transparency for quickly and accurately tuning threaded applications for optimal performance. Recommended companion technical webinar: The Good, the Bad, and the Ugly: Improve Parallel Application Quality and Performance.