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 Porto Alegre can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Porto Alegre - Platinum Building
Carlos Gomes Avenue, 700, Porto Alegre, Brazil, 90480-000
Platinum Building has many amenities close by. The Boa Vista district is a major corporate center in this sophisticated and progressive port city. Also the business center is six kilometers from the international airport and well served by public transport.
Porto Alegre - Guaiba Business Center
Av. Dolorez Alcaraz Caldas, 90 Porto Alegre RS, Praia de Belas, Brasil, 90110-180
Be at the centre of a lively business district in Praia De Belas, surrounded by courthouses and government offices. Centro Empresarial Guaiba is a distinctive Class A building in the thriving state capital of Porto Alegre.
This instructor-led, live training in Porto Alegre (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 Porto Alegre (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.
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