Introduction to Parallel Programming video lecture series – Part 01 “Why Parallel? Why Now?”

Authored by 0

The lecture given here is the first part in the “Introduction to Parallel Programming” video series.

Last updated on 01/08/2012 - 11:18

Beacon Mountain: A Development Environment for Android Apps

Authored by Jerry Makare (Intel)

Learn about Beacon Mountain - Intel's development environment for creating applications for Intel Atom and ARM*-based devices running Android* operating systems.

Last updated on 25/03/2014 - 08:18

Touch Response Measurement, Analysis, and Optimization for Windows* Applications

Authored by thomas-pantels (Intel)

By Tom Pantels, Sheng Guo, Rajshree Chabukswar

Last updated on 22/08/2014 - 14:05

Optimized Pseudo Random Number Generators with AVX2

Authored by gaston-hillar

Intel® Math Kernel Library includes powerful and versatile random number generators that have been optimized to take full advantage of Intel

Last updated on 16/07/2014 - 13:14

Tips and Tricks to Optimize Android Apps on x86

Authored by Colleen Culbertson (Intel)

Intel has a vested interest in helping developers provide Android applications that run well (or even best) on Intel architecture.

Last updated on 03/07/2014 - 10:33

Will my Android App still run with ART instead of Dalvik?

Authored by Colleen Culbertson (Intel)


With Android L, the virtual machine compiler will move to ART (Android RunTime) and only ART for 64 bit. So what do we know about ART vs Dalvik and what does it mean for App code?

Last updated on 12/08/2014 - 07:50

Understanding the corner cases of Vectorization Intensity

Authored by Sumedh Naik (Intel)

Correct performance analysis of an application is absolutely vital to optimize the performance on any architecture.

Last updated on 23/09/2014 - 11:28

Update Now: What’s New in Intel® Compilers and Libraries

Authored by Ronald W Green (Intel) Build fast code faster with the compilers and libraries in the new Intel® Compiler Version 15.

Last updated on 02/10/2014 - 11:40

Diagnostic 15414: Loop was not vectorized: loop body became empty after optimizations

Authored by Devorah H. (Intel)

Product Version: Intel(R) Visual Fortran Compiler XE

Last updated on 03/10/2014 - 12:51

Optimizing LAMMPS* for Intel® Xeon Phi™ Coprocessors

Authored by admin
LAMMPS* is a large scale atomic/molecular massively parallel simulator distributed by Sandia National Laboratories. Last updated on 19/03/2015 - 05:48