Intel(R) Advisor XE 2013 Update 4 has a very valuable feature to help reduce time it takes to run analyses.
The Summary Statistics (SSL) is a subcomponent of the Vector Statistical Library (VSL) included in the Intel® Math Kernel Library (Intel® MKL). The library provides rich set of functions to compute various statistical estimates for multi-dimensional datasets.
The STREAM benchmark (http://www.cs.virginia.edu/stream/) a synthetic benchmark program, written in standard Fortran 77 (with a corresponding version in C). It measures the the performance of four long vector operations. These operations are:
name kernel bytes per iteration | FLOPS per iteration
COPY: a(i) = b(i) 16 0
This Configuration and Deployment Guide explores designing and building object storage environments based on OpenStack* Swift* in cloud environments, where responsiveness and enery costs are critical factors. High-performance, energy-efficient microservers, such as those based on the latest generation of Intel® Atom™ processors and Intel® Xeon® E3 processors, meet these requirements. The guide uses data from recent benchmarks conducted by Intel® Software and Services Group on Intel Atom processor and Intel Xeon E3 processor-based microservers.
Intel(R) Advisor XE 2013 helps developers discover what parts of their software programs scale well. Determining scalability of a piece of code is essential to determine if it is worth parallelizing and if so, the size of an actual machine which can exploit such scalabile code.
One of the best known C++ threading libraries Intel® Threading Building Blocks (Intel® TBB) was recently updated to a new release 4.2. The updated version contains several key new features comparing to previous release 4.1. Some of them were already released in Intel TBB 4.1 updates.
Starting in 11.0 the Intel(R) C++ Compiler has supported some of the C++11 features (previously called C++0x). With the latest release of Intel C++ Composer XE for Windows*, Linux* and Mac OS* X 2013 SP1, more C++11 features are supported.
To improve the performance of applications and kernels we are constantly on the search for novel Best Known Methods or BKMs, but as our searches grow more esoteric, it is important to keep in mind the basics and how many performance improvements rely on them. This article will describe some common BKMs for improving parallel performance and show their application over this spectrum of processor architectures. The advice collected here should help you speed up your code, whether running on an Intel® Xeon Phi™ coprocessor or an Intel Xeon process