How to configure OpenMP in the Intel IPP library to maximize multi-threaded performance of the Intel IPP primitives.
Intel® PCC at the Hartree Centre is to enable UK academic and industrial codes to exploit the parallel and energy.
Modern high performance computers are built with a combination of resources including:
Não perca a palestra "Como otimizar seu código sem ser um "ninja" em Computação Paralela" da Intel que será ministrada durante a Semana sobre Programação Massivamente Paralela em Petrópolis, RJ, no Laboratório Nacional de Computação Científica. Data: 02/02/2016 - 11h30 Local: LNCC - Av. Getúlio Vargas, 333 - Quitandinha - Petrópolis/RJ
Contrast results for manually tuning financial data and using data layout templates in the Intel® C++ Compiler.
Applications often use files to store data from one run to the next, but high-capacity, non-volatile memory devices make it possible to store data more effectively than using a disk-based file system. This article describes how to design your application to take advantage of these memory devices, thereby avoiding the need for files to serve as persistent memory.
Intel’s non-uniform memory access (NUMA) strategy is based on several new memory technologies that promise significant improvements in both capability and performance. This article provides information on Multi-Channel DRAM (MCDRAM) and High-Bandwidth Memory (HBM), Non-volatile dual inline-memory modules (NVDIMMs), and Intel® Omni-Path Fabric (Intel® OP Fabric).
Do you have a problem that Intel non-uniform memory access (NUMA) hardware and the related tools and strategies can solve? The answer depends on the problem you are facing and if you can make decisions about choosing/changing your hardware, your software, or both. This article walks you through the decision.
Learn how to build an application that runs effectively on non-uniform memory access (NUMA) hardware. This article walks you through choosing the algorithm all the way through to measuring your application's performance.