Les cours de formation GPU (Graphics Processing Unit) en direct dirigés par un instructeur montrent, par le biais de discussions interactives et de travaux pratiques, les principes de base du GPU et la manière de les programmer. La formation GPU est disponible en tant que "formation en direct sur site" ou "formation en direct à distance". La formation en direct sur site peut être effectuée localement chez le client à Quebec ou dans des centres de formation d'entreprise NobleProg dans Quebec . La formation en direct à distance est réalisée au moyen d'un poste de travail distant et interactif. NobleProg - Votre prestataire de formation local
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Piotr Glazor - Nokia
Formation: NVIDIA GPU Programming - Extended
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Sous-catégories Graphics Processing Unit (GPU)
Plans de cours GPU
Nom du Cours
Durée
Aperçu
Nom du Cours
Durée
Aperçu
14 hours
Aperçu
Ce cours explique comment programmer des GPU pour le calcul parallèle. Certaines applications incluent l’apprentissage en profondeur, l’analyse et les applications techniques.
14 hours
Aperçu
CUDA (Compute Unified Device Architecture) is a parallel computing platform and API created by Nvidia.
This instructor-led, live training (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.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
This instructor-led, live training (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.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
21 hours
Aperçu
Cette formation en direct, animée par un instructeur, explique comment programmer des GPU pour le calcul parallèle, comment utiliser différentes plates-formes, comment utiliser la plate-forme CUDA et ses fonctionnalités et comment appliquer diverses techniques d'optimisation à l'aide de CUDA. Certaines applications incluent l'apprentissage en profondeur, l'analyse, le traitement d'images et les applications d'ingénierie.
14 hours
Aperçu
Video analytics refers to the technology and techniques used to process a video stream. A common application would be capturing and identifying live video events through motion detection, facial recognition, crowd and vehicle counting, etc.
This instructor-led, live training (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.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
This instructor-led, live training (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.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
Autres régions
Other countries
Conseil
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