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Optimizing Computer Applications for Latency: Part 2: Tuning Applications

For applications such as high frequency trading (HFT), search engines and telecommunications, it is essential that latency can be minimized. My previous article Optimizing Computer Applications for Latency, looked at the architecture choices that support a low latency application. This article builds on that to show how latency can be measured and tuned within the application software.

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  • Intel® VTune™ Amplifier
  • Face Beautification API for Intel® Graphics Technology

    This document highlights the C++ API for enabling applications to support Face Beautification It provides the list of available effects in Face Beautification supported by Intel Graphics Technology, C++ API definitions, and methods to enable an application to use the C++ Face Beautification API using the static library.
  • Game Development
  • Profiling Tensorflow* workloads with Intel® VTune™ Amplifier

    Machine learning applications are very compute intensive by their nature. That is why optimization for performance is quite important for them. One of the most popular libraries, Tensorflow*, already has an embedded timeline feature that helps understand which parts of the computational graph are causing bottlenecks but it lacks some advanced features like an architectural analysis.

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  • Artificial Intelligence
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  • Intel® Parallel Studio XE
  • Intel® VTune™ Amplifier
  • VTune
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  • timeline
  • JSON
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  • Using Intel® MPI Library on Intel® Xeon Phi™ Product Family

    This document is designed to help users get started writing code and running MPI applications using the Intel® MPI Library on a development platform that includes the Intel® Xeon Phi™ processor.
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  • Intel® Software Guard Extensions Tutorial Part 9: Power Events and Data Sealing

    In Part 9 of the Intel® SGX tutorial series we address complexities of the suspend and resume power cycle. We’ll examine data Intel SGX sealing capabilities and apply our learnings to the Tutorial Password Manager.
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    Connecting to SAP Cloud Platform* Internet of Things

    To get started using the SAP* IoT Starter Kit, you must first setup your account, by following the "Getting Started in the Cloud" steps listed at https://github.com/SAP/iot-starterkit#getting-started-in-the-cloud

    SAP Cloud Platform* Developer signup

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  • Connecting to AT&T* M2X* IoT using MQTT

     

    AT&T* M2X* IoT initial signup

    1.  Create an account on https://m2x.att.com, if you do not yet have one. If you already have an account, you can skip directly to "Adding your first device" below. 

    2.  Fill out your information when signing up. 

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  • 面向 Caffe* 的定制示例:异或和形状

    下载代码示例 [62.34 KB]

    简介

    Caffe* 是伯克利愿景和学习中心开发的一款深度学习框架,该框架使用 C++ 语言编写,拥有一个 C++ API,并与 Python 和 MATLAB 绑定。

    可通过 GitHub 网页https://github.com/BVLC/caffe 获取源代码、示例和文档。但是,对于新手开发人员而言,示例和文档带来了很多问题,开发人员需要花费大量的时间和精力进行学习,才能利用该框架自定义操作。

    本文通过两个示例展示了如何配置 Caffe,以及如何执行两种定制训练和分类任务:

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