Online or onsite, instructor-led live CUDA (Compute Unified Device Architecture) training courses demonstrate through interactive hands-on practice how to use a CUDA-enabled GPU for general purpose processing.
CUDA training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Onsite live CUDA (Compute Unified Device Architecture) trainings in Newcastle can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Newcastle
116 Quayside, Newcastle upon Tyne, united kingdom, NE1 3DY
The Newcastle Quayside Centre is in a prestigious riverside location close to the River Tyne occupying three floors of a five-storey building with a glass front and modern interior. The views of the famous Tyne Bridge and recently built Millennium Bridge are stunning. The recently restored Baltic Centre for Contemporary Art is directly opposite, next to the Sage Gateshead performing arts and conference centre. The vibrant and energetic city of Newcastle is a modern, attractive and compact location with a strong identity where businesses prosper and people enjoy a quality of life that is second to none. This area is among the most successful in the UK for attracting investment from abroad and is already the preferred location of many Far Eastern and US companies entering the European market. Over 130 investors from 15 countries have chosen to locate in and around the city, joining a business community of over 17,000 companies.
This instructor-led, live training in Newcastle (online or onsite) is aimed at beginner-level system administrators and IT professionals who wish to install, configure, manage, and troubleshoot CUDA environments.
By the end of this training, participants will be able to:
Understand the architecture, components, and capabilities of CUDA.
This instructor-led, live training in Newcastle (online or onsite) is aimed at intermediate-level 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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Testimonials (1)
Very interactive with various examples, with a good progression in complexity between the start and the end of the training.
Jenny - Andheo
Course - GPU Programming with CUDA and Python
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