Convolutional neural networks on a multi-FPGA platform

机器学习是使用计算机算法，可以从数据中学习并对数据进行预测。最近机器学习算法的突破使机器学习成为高性能计算中增长最快的应用之一。一个简单的例子是当你要用你的智能手机拍照时识别人脸。 卷积神经网络(CNN)是一种机器学习算法，能够对图像中的目标进行高精度检测。众所周知，CNN在图形处理单元(GPU)上运行良好，图形处理单元(GPU)是最初设计用于在计算机显示器上进行图形处理的并行处理设备，现在也用于许多计算应用。GPU的一个重要问题是它们会耗费大量的电力。现场可编程门阵列(现场可编程门阵列)是一种可编程芯片技术，也可用于实现计算电路。现场可编程门阵列的一个重要优势是，它们比GPU耗电少得多，但目前它们在CNN计算中的表现不如GPU。然而，使用几个现场可编程门阵列可能会克服这一问题。该提案将研究一种多现场可编程门阵列实现CNN的方法。 Evertz总部位于安大略省伯灵顿，是一家为广播和电影行业开发和制造高性能计算系统的公司。他们的系统主要基于多个现场可编程门阵列进行视频处理，并将视频流从多个来源切换到多个目的地。该提案将调查CNN与Evertz平台的整合，以增强其产品。例如，新功能就是搜索电影档案，找到汉弗莱·鲍嘉出现过的电影。

Machine learning is the use of computer algorithms that can learn from and make predictions about data. Recent breakthroughs in machine learning algorithms have made machine learning one of the fastest growing applications for high-performance computing. A simple example would be to identify faces as you are about to take a picture using your smart phone. The Convolutional Neural Network (CNN) is a machine learning algorithm capable of high-accuracy object detection in images. CNNs are known to run well on graphic processing units (GPUs), which are parallel processing devices originally designed for doing the graphics on computer displays and now also used for many computing applications. A significant issue with GPUs is that they dissipate significant power. Field-programmable gate arrays (FPGAs) are a programmable chip technology that can also be used to implement computing circuits. An important advantage of FPGAs is that they dissipate much less power than GPUs, but they currently do not perform as well as GPUs on CNN computations. However, the use of several FPGAs may overcome this issue. This proposal will investigate a multi-FPGA approach to CNNs. Evertz, based in Burlington, Ontario, is a company that develops and manufactures high-performance computing systems for the broadcast and film industry. Their systems are based primarily on multiple FPGAs to do video processing and switching video streams from multiple sources to multiple destinations. This proposal will investigate the integration of CNNs into the Evertz platform to enhance their products. An example new feature would be to search through an archive of movies and find the ones where Humphrey Bogart appears.