É sabido que a API das aplicações Windows Store não disponibiliza algumas funções comuns para trabalhar com Threads, como a CreateThread e aquelas que trabalham com chaves TLS (Thread-local storage). Esta é mais uma grande oportunidade para migrar o seu desenvolvimento de aplicações de um paralelismo baseado em threads para um paralelismo baseado em tarefas. Este post demonstra as instruções passo-a-passo para escrever um exemplo que usa paralelismo e que pode passar pela validação do Windows App Certification Kit (WACK).
Tutorial
Optimization of a Parallel Application for Multi-Core Environments
(This work was done by Vivek Lingegowda during his internship at Intel.)
Optimization of Data Read/Write in a Parallel Application
(This work was done by Vivek Lingegowda during his internship at Intel.)
An Introduction to Cilk™ Plus Reducers
If you are new to Cilk™ Plus, you have probably been impressed by how easy it is to turn a serial program into a parallel program. You’ve also realized, though, that adding cilk_sync or cilk_for to a program doesn’t automatically solve the harder parts of parallel programming: dealing with data races, and coordinating work that is done in parallel.
Intel® System Studio Training Materials
Here are useful slide decks to enhance your learning of Intel System Studio:
- Overview
- Build and Design
Do It Yourself - Chromium Web Application Container
EmbeddedWorld Signal Processing and Power Management Workshop
This is the conference paper describing Intel® System Studio in great detail in-lieu of the Signal Processing and Power Management Workshop.
Memory profiling techniques using Intel System Studio
To Download this article :- 
memory-profiling-using-intel-system-studio.pdf (344.62 KB)
Introduction
One of the problems with developing embedded systems is the detection of memory errors; like
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.
License Agreement:
Pages
