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所在平台: Udemy |
课程主页: https://www.udemy.com/course/matlab-parallel-programming-using-gpus-cores-and-cpus/
课程评论：没有评论
**MATLAB GPU与多核并行编程课程总结** 本课程旨在帮助学员、研究人员及MATLAB用户显著缩短程序执行时间。当前计算机普遍配备多核CPU和GPU，但许多用户未能充分利用这些并行计算资源。本课程正是为了填补这一空白，通过实际案例教授学员如何高效利用计算机的所有资源，并学会监控其使用情况。 课程内容涵盖以下几个核心章节： 1. **CPU、多核与GPU硬件基础**：首先介绍CPU、多核和GPU的基本硬件构成，帮助学员理解其工作原理，以便实现最佳利用率。 2. **多线程与多工作并行概念解析**： * **多线程**：作为一种内置机制，允许函数在多核上并行执行，但用户对核心数量和执行方式的控制有限。 * **多工作**：提供更灵活的并行执行方式，允许用户运行任何函数在多个核心上，并可精确控制核心数量以优化程序性能。本节通过实例对比并测量性能参数，清晰区分了两者的异同。 3. **GPU并行计算**：教授如何利用GPU上成百上千的并行核心来加速任何函数。课程详细讲解了实现最佳GPU性能的关键技巧和注意事项，并辅以大量示例。 4. **深度学习与神经网络并行训练**：学习如何在GPU或多核上并行训练神经网络。此外，还演示了如何将训练过程置于后台运行，从而在训练期间继续使用MATLAB。
This course helps students, researchers, and anyone using the MATLAB decrease the execution time they take to execute a program All computers today and the laptops have multi-cores and GPUs. But not all users use the to run or execute the programs in parallel. The purpose of the course is to fill this gap. Is to teach you with practical examples how to use all resources on your computer and also how to monitor them.The course is divided into many sections:The first is an introduction to the hardware of the CPUs, cores, and GPUs. It is better to understand the basic components of these items to be able to get the best utilization when you use them.The second section is explaining two concepts. The multi-threading and the multi-workers. The first is a built-in mechanism to run some functions in parallel using many cores but we can't control the number of cores and the way that the functions execute. The second one (multi-workers) is used to run any function on multiple cores but here we can control the number of cores to optimize the program execution. Also, I explained some examples and measured the performance parameters to differentiate between the two concepts.The third section is the GPU section. In the section, I explained how to run any function on the GPUs to make use of the hundred or thousands of cores that the GPUs have. There are some notations to get the best results and I explained all of these notations with examples.Deep learning and neural networks: in this section, you will learn how to train any neural network in parallel on GPUs or multi-cores. And also how to run the training process in the background in order to be able to use MATLAB while it is running.
