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如何利用 Windows* 版英特尔® 线程调节器来分析 Linux* 应用

Instructions for how-to use the "Enabling collector for Linux*" to collect Intel® Thread Profiler data on a Linux* system and view the results with the Intel® Thread Profiler for Windows*, part of the Intel® VTune Performance Analyzer for Windows*.
Authored by Eric W Moore (Intel) Last updated on 05/25/2018 - 15:30
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循环修改增强数据并行性能

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.
Authored by admin Last updated on 07/05/2019 - 14:48
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面向英特尔® 至强融核™ 协处理器(和英特尔® 至强® 处理器)架构应用的浮点计算 R2R 再现性

 

问题

如果在相同处理器上针对相同输入数据重新运行相同的程序,得到的结果相同吗?

Authored by Last updated on 03/21/2019 - 12:08
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粒度与并行性能

One key to attaining good parallel performance is choosing the right granularity for the application. Granularity is the amount of real work in the parallel task. If granularity is too fine, then performance can suffer from communication overhead.
Authored by admin Last updated on 07/05/2019 - 19:53
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整理您的数据和代码: 数据和布局 - 第 2 部分

Apply the concepts of parallelism and distributed memory computing to your code to improve software performance. This paper expands on concepts discussed in Part 1, to consider parallelism, both vectorization (single instruction multiple data SIMD) as well as shared memory parallelism (threading), and distributed memory computing.
Authored by David M. Last updated on 07/06/2019 - 16:40
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避免线程之间发生堆冲突

避免线程之间发生堆冲突 (PDF 256KB)

摘要

Authored by admin Last updated on 07/05/2019 - 19:59
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检测线程应用中的内存带宽饱和度

检测线程应用中的内存带宽饱和度 (PDF 231KB)

Authored by admin Last updated on 07/05/2019 - 19:58
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英特尔® OpenVINO™ 工具套件分发版助力加速基于深度学习的大规模反向运动学

使用深度学习部署工具套件 (DLDT) 部署深度学习算法,以解决角色的反向运动学 (IK) 问题。
Authored by Tai Ha (Intel) Last updated on 09/03/2019 - 18:27
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利用英特尔® 线程构建模块(英特尔® TBB)优化 MSC. Software SimXpert*

MSC.Software SimXpert* is a fully integrated simulation environment for performing multidiscipline based analysis with a graphical interface designed to facilitate the end-to-end simulations. This article describes the threading of SimXpert.
Authored by Last updated on 08/01/2019 - 09:30
Article

OpenVINO™ 工具套件版本说明

OpenVINO™ 2018 R3 Release - Gold release of the Intel® FPGA Deep Learning Acceleration Suite accelerates AI inferencing workloads using Intel® FPGAs that are optimized for performance, power, and cost, Windows* support for the Intel® Movidius™ Neural Compute Stick, Python* API preview that supports the inference engine, Open Neural Network Exchange (ONNX) Model Zoo provides initial support for...
Authored by Deanne Deuermeyer (Intel) Last updated on 10/22/2018 - 23:52