# A Matrix Multiplication Routine that Updates Only the Upper or Lower Triangular Part of the Result Matrix

### Background

Intel® MKL provides the general purpose BLAS*  matrix multiply routines ?GEMM defined as follows:

`C := alpha*op(A)*op(B) + beta*C`

where alpha and beta are scalars, op(A) is an m-by-k matrix, op(B) is a k-by-n matrix, C is an m-by-n matrix, with op(X) being either X, or XT, or XH.

• 开发人员
• 合作伙伴
• 教授
• 学生
• Apple Mac 操作系统 X*
• Linux*
• Microsoft Windows* (XP, Vista, 7)
• Microsoft Windows* 8
• Unix*
• 企业客户端
• 云服务
• 服务器
• C/C++
• Fortran
• 高级
• 入门级
• 中级
• 英特尔® 数学核心函数库
• Learning Lab
• GEMM BLAS matrix multiplication
• DGEMM
• 开发工具
• 金融服务行业
• 优化

# Introduction to the Intel MKL Extended Eigensolver

Intel® MKL 11.0 Update 2 introduced a new component called Extended Eigensolver routines. These routines solve standard and generalized Eigenvalue problems for symmetric/Hermitian and symmetric/Hermitian positive definite sparse matrices. Specifically, these routines computes all the Eigenvalues and the corresponding Eigenvectors within a given search interval [λmin, λmax]:

• 开发人员
• 合作伙伴
• 教授
• 学生
• Linux*
• Microsoft Windows* (XP, Vista, 7)
• Microsoft Windows* 8
• Apple Mac 操作系统 X*
• Unix*
• 企业客户端
• 服务器
• C/C++
• Fortran
• 高级
• 入门级
• 中级
• 英特尔® 数学核心函数库
• Learning Lab
• MKL
• Eigensolver
• eigenvectors
• Eigenvalues
• sparse matrix
• intel math kernal library
• intel mkl
• 开发工具
• 大型企业
• 金融服务行业
• 英特尔® 酷睿™ 处理器
• Intel® Many Integrated Core Architecture
• 并行计算
• # Offload Runtime for the Intel® Xeon Phi™ Coprocessor

The Intel® Xeon Phi™ coprocessor platform has a software stack that enables new programming models.  One such model is offload of computation from a host processor to a coprocessor that is a fully-functional Intel® Architecture CPU, namely, the Intel® Xeon Phi™ coprocessor.  The purpose of that offload is to improve response time and/or throughput.  The attached paper presents the compiler offload software runtime infrastructure for the Intel® Xeon Phi™ coprocessor, which includes a production C/C++ and Fortran compiler that enables offload to that coprocessor, and an underlying Intel

• 开发人员
• 合作伙伴
• 教授
• 学生
• Linux*
• Microsoft Windows* (XP, Vista, 7)
• 服务器
• C/C++
• Fortran
• 高级
• 入门级
• 中级
• 英特尔® C++ 编译器
• 英特尔® 数学核心函数库
• Intel® MPI Library
• Intel® Cluster Studio XE
• 英特尔® Parallel Studio XE
• 消息传递接口
• OpenMP*
• 开发工具
• Intel® Many Integrated Core Architecture
• 并行计算

# Building OpenCV based embedded application using Intel® System Studio

We describe how to use Intel® System Studio to build the OpenCV based embedded application on Intel platforms. In this paper, we have considered a sample code that is part of OpenCV, how to use different components of Intel® System Studio to build OpenCV sample code.
• 开发人员
• 教授
• 学生
• Linux*
• Yocto 项目
• C/C++
• 入门级
• 英特尔® 集成性能原件
• 面向英特尔® 凌动™ 处理器的 Intel® Embedded Software Development Tool Suite
• 英特尔® System Studio
• OpenCV for embedded application
• Intel System Studio OpenCV
• OpenCV in Intel ARchitecture
• OpenCV with IPP
• 开发工具
• 嵌入式
• # Tuning the Intel MKL DFT functions performance on Intel® Xeon Phi™ coprocessors

Overview

Intel® Math Kernel Library (Intel® MKL) includes the optimized DFT transform functions on Intel® Xeon Phi™ coprocessors. These functions are carefully vectorized and threaded to take advantage of the hardware features. This article provides some performance tuning tips on running MKL DFT function on Intel Xeon Phi coprocessors.  We will start with some simple example code.

Building the example code

• 开发人员
• Linux*
• 服务器
• C/C++
• Fortran
• 入门级
• 中级
• 英特尔® 数学核心函数库
• MIC
• Xeon Phi
• DFT
• FFT
• performance
• 英特尔® SIMD 流指令扩展
• Intel® Many Integrated Core Architecture
• # Signal Processing Usage for Intel® System Studio – Intel® MKL vs. Intel® IPP

Employing performance libraries can be a great way to streamline and unify the computational execution flow for data intensive tasks, thus minimizing the risk of data stream timing issues and heisenbugs. Here we will describe the two libraries that can be used for signal processing within Intel® System Studio.

Intel® Integrated Performance Primitives (Intel®IPP)

• 开发人员
• Linux*
• Yocto 项目
• C/C++
• 入门级
• 中级
• Intel® Debugger
• 英特尔® 集成性能原件
• 面向英特尔® 凌动™ 处理器的 Intel® Embedded Software Development Tool Suite
• 英特尔® System Studio
• signal processing
• 嵌入式
• 英特尔® 凌动™ 处理器
• # GELS produces the wrong result with sequential version

Problem Description:

We have a number of customers report regarding incorrect behavior of GELS in Intel® MKL 11.0 if sequential library is linked.

Customer’s quote:”When I compile and run this program with Intel® Fortran Composer XE 2013(**), the output is totally wrong. Compiling and running with Intel FORTRAN Composer XE 2011 (*) gives the correct results.”

• 中级
• 英特尔® C++ Composer XE
• 英特尔® Fortran Composer XE
• 英特尔® 数学核心函数库
• # Statically linking MKL library and IPP library in same project produce the link errors

Problem Description:     Statically linking MKL and IPP in the same project produce the link errors like the following:

1>ipps_l.lib(pscopyg9as_g9.obj) : error LNK2005: _g9_ownsSet_32s_G9 already defined in mkl_core.lib(pscopyg9as_20120907.obj)

1>ipps_l.lib(pscopyg9as_g9.obj) : error LNK2005: _g9_ownsSet_16u_G9 already defined in mkl_core.lib(pscopyg9as_20120907.obj)

1>ipps_l.lib(pscopyg9as_g9.obj) : error LNK2005: _g9_ownsSet_8u_G9 already defined in mkl_core.lib(pscopyg9as_20120907.obj)

• 开发人员
• C/C++
• Fortran
• 中级
• 英特尔® 集成性能原件
• 英特尔® 数学核心函数库
• # Intel® System Studio - Multicore Programming with Intel® Cilk™ Plus

Intel System Studio not only provides a variety of signal processing primitives via Intel® Integrated Performance Primitives (Intel® IPP), and Intel® Math Kernel Library (Intel® MKL), but also allows developing high-performance low-latency custom code (Intel C++ Compiler with Intel Cilk Plus). Since Intel Cilk Plus is built into the compiler, it can be used where it demands an efficient threading runtime in order to extract parallelism. Therefore it's possible to effectively introduce multicore parallelism even without introducing it into each of the important algorithms e.g., by employing a parallel pattern called pipeline. For custom code (e.g., code that's not reused via a library), one can rely (in addition to auto-vectorization) on an extended Array Notation incl. elemental functions (kernels) to explicitly vectorize at a higher level compared to ISA-specific intrinsic functions.
• 开发人员
• 英特尔 AppUp® 开发人员
• 学生
• Linux*
• Yocto 项目
• C/C++
• 高级
• 入门级
• 中级
• 英特尔® C++ 编译器
• 英特尔® Cilk™ Plus
• 英特尔® 集成性能原件
• 英特尔® 数学核心函数库
• 英特尔® System Studio
• embedded c programming
• 嵌入式
• 并行计算
• 能效
• 线程
• 矢量化
• # Intel® MPI Library 4.1 Build 030 Readme

The Intel® MPI Library for Linux* and Windows* is a high-performance interconnect-independent multi-fabric library implementation of the industry-standard Message Passing Interface, v2.2 (MPI-2.2) specification. This package is for MPI users who develop on and build for IA-32 and Intel® 64 architectures on Linux* and Windows*, as well as customers running on the Intel® Xeon Phi™ coprocessor on Linux*. You must have a valid license to download, install and use this product.

• 开发人员
• Linux*
• 服务器
• C/C++
• Fortran
• Intel® MPI Library
• 消息传递接口
• 集群计算