广州现场GPU培训

广州现场GPU培训

本地,讲师指导的现场GPU(图形处理单元)培训课程通过交互式讨论和动手实践演示了GPU的基本原理以及如何编程GPU。 GPU培训可用作“现场实时培训”或“远程实时培训”。现场培训可以在当地的客户场所进行广州或者在NobleProg的企业培训中心广州 。远程实时培训通过交互式远程桌面进行。 NobleProg - 您当地的培训机构

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广州 - 广东国际大厦

广东国际大厦7楼

广州, Guangdong 越秀区环市东路339号 510098 ,
广东国际大厦
在广州的培训中心学习GPU。 广东国际大厦中心坐落于著名的环市东路CBD中心,是一座拥有五星级皇冠酒店、甲级办公楼和酒店式公寓的综合大楼。 大厦毗邻广东电视台大楼、黄花岗剧院、花园饭店和白云宾馆。其他附近设施包括大型商场、购物中心、银行、餐馆等。 周围设有便利的公共交通,周边的地铁、出租车和公交车可通往广州的其他地区以及广州国际机场。 广东国际大厦已吸引了众多外国领事馆、贸易采购公司,以及许多金融服务公司入驻。 查看更多

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广州现场Graphics Processing Unit (GPU)课程大纲

课程名称
课程时长
课程概览
课程名称
课程时长
课程概览
14小时
课程概览
This course covers how to program GPUs for parallel computing. Some of the applications include deep learning, analytics, and engineering applications.
21小时
课程概览
This instructor-led, live training course in 广州 covers how to program GPUs for parallel computing, how to use various platforms, how to work with the CUDA platform and its features, and how to perform various optimization techniques using CUDA. Some of the applications include deep learning, analytics, image processing and engineering applications.
14小时
课程概览
This instructor-led, live training in 广州 (online or onsite) is aimed at developers who wish to build hardware-accelerated object detection and tracking models to analyze streaming video data.

By the end of this training, participants will be able to:

- Install and configure the necessary development environment, software and libraries to begin developing.
- Build, train, and deploy deep learning models to analyze live video feeds.
- Identify, track, segment and predict different objects within video frames.
- Optimize object detection and tracking models.
- Deploy an intelligent video analytics (IVA) application.
14小时
课程概览
This instructor-led, live training in 广州 (online or onsite) is aimed at developers who wish to use CUDA to build Python applications that run in parallel on NVIDIA GPUs.

By the end of this training, participants will be able to:

- Use the Numba compiler to accelerate Python applications running on NVIDIA GPUs.
- Create, compile and launch custom CUDA kernels.
- Manage GPU memory.
- Convert a CPU based application into a GPU-accelerated application.
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