Cursuri GPU

Cursuri GPU

Programele de pregătire locală, instruite de un profesor grafic GPU (Unitatea de procesare grafică) demonstrează, prin discuții interactive și practici practice, fundamentele GPU-ului și modul de programare a unităților de procesare grafică. Pregătirea GPU este disponibilă ca "formare live la fața locului" sau "formare live la distanță". Training-ul live la fața locului poate fi efectuat la fața locului la sediul clientului România sau în centrele de formare corporativa NobleProg din România România . Instruirea live la distanță este realizată printr-un desktop interactiv, la distanță. NobleProg - Furnizorul dvs. de formare locală

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Graphics Processing Unit (GPU) Subcategories

Graphics Processing Unit (GPU) Course Outlines

Numele cursului
Durata
Sinoptic
Numele cursului
Durata
Sinoptic
14 hours
Sinoptic
Acest curs acoperă modul de programare a GPU urilor pentru calcul paralel. Unele dintre aplicații includ învățare profundă, analize și aplicații de inginerie.
21 hours
Sinoptic
This instructor-led, live training course in România 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 hours
Sinoptic
This instructor-led, live training in România (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.
14 hours
Sinoptic
This instructor-led, live training in România (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.

Upcoming Graphics Processing Unit Courses

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