GPU 교육

GPU 교육

현지 강사 주도 라이브 GPU (그래픽 처리 장치) 교육 과정은 대화식 토론과 실습을 통해 GPU의 기본 사항 및 GPU 프로그래밍 방법을 보여줍니다. GPU 교육은 "현장 실습"또는 "원격 실습"으로 제공됩니다. 현장 실습은 고객 구내에서 현지에서 실시 할 수 있습니다. 대한민국 또는 NobleProg 기업 교육 센터에서 대한민국 . 원격 라이브 교육은 대화 형 원격 데스크톱을 통해 수행됩니다. NobleProg - 지역 교육 제공자

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Graphics Processing Unit (GPU)서브 카테고리

GPU코스 개요

코스 이름
Duration
Overview
코스 이름
Duration
Overview
14 시간
Overview
This course covers how to program GPUs for parallel computing. Some of the applications include deep learning, analytics, and engineering applications.
21 시간
Overview
This instructor-led, live training course in 대한민국 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 시간
Overview
This instructor-led, live training in 대한민국 (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 시간
Overview
This instructor-led, live training in 대한민국 (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.

향후GPU 코스

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