Parallel Programming

Intel Inspector XE 2011 automatically finds memory errors, deadlocks and other conditions that could lead to deadlocks, data races, thread . Some specific issues associated with debugging multithreaded applications will be discussed in this article.

by Rajshree Chabukswar, Adam T. Lake, and Mary R. Lee, Intel® Software Solutions Group Introduction Learn how to decouple rendering and physical simulation in a multi-threaded environment with a ...

Introduction This white paper is the fourth in a series of white papers on OpenCL describing how to set up and use events in multithreaded design. This white paper will go over various design choices ...

The Intel® Performance Counter Monitor provides sample C++ routines and utilities to estimate the internal resource utilization of the latest Intel® Xeon® and Core™ processors and gain a significant performance boost.

Non-blocking system calls allow the competing thread to return on an unsuccessful attempt to the lock, and allow useful work to be done, thereby avoiding wasteful utilization of execution resources at the same time.

Application programmers sometimes write hand-coded synchronization routines rather than using constructs provided by a threading API in order to reduce synchronization overhead or provide different functionality than existing constructs offer.

Using AVX Without Writing AVX Code (PDF 260KB) Abstract Intel® Advanced Vector Extensions (Intel® AVX) is a new 256-bit instruction set extension to Intel® Streaming SIMD Extensions (Intel® SSE) and ...

Tasks are a lightweight alternative to threads that provide faster startup and shutdown times, better load balancing, an efficient use of available resources, and a higher level of abstraction.

Load balancing an application workload among threads is critical to performance. The key objective for load balancing is to minimize idle time on threads.

When confronted with nested loops, the granularity of the computations that are assigned to threads will directly affect performance. Loop transformations such as splitting and merging nested loops can make parallelization easier and more productive.

GOptimize Data Structures and Memory Access Patterns to Improve Data Locality (PDF 782KB) Abstract Cache is one of the most important resources of modern CPUs: it’s a smaller and faster part of the m ...

Curing Thread Imbalance Using Intel® Parallel Amplifier (PDF 302KB) Abstract One of the performance-inhibiting factors in threaded applications is load imbalance. Balancing the workload among thread ...