What if your AI models ran faster, trained smarter, and deployed seamlessly from edge to cloud? Huawei Ascend makes that possible.
These instructor-led courses unlock the potential of Ascend AI processors, guiding engineers through hands-on projects with MindSpore, model compression, and chip-level optimization.
Courses are delivered via online live training through an interactive remote desktop, or as onsite live training in Graz with labs focused on real production workloads.
Onsite sessions can be hosted at your facilities in Graz or arranged at a NobleProg corporate training center in Graz to support collaborative, team-based learning.
Also known as Ascend AI, Huawei Ascend 910, or Ascend Computing, this training helps you move beyond generic AI hardware and into purpose-built performance.
NobleProg – Your Local Training Provider
NobleProg Graz
Waagner-Biro-Strasse 47, Graz, Austria, 8020
Overview
Our training facilities are located at Waagner-Biro-Strasse 47 in Graz. Our spacious training rooms are located directly in the old town and offer optimal training conditions for your needs.
Directions
The NobleProg training facilities are best reached via the A9 motorway and the federal highway 67.
Parking spaces
There are parking spaces in the streets around our training rooms as well as the ContiPark multi-storey car park.
Local infrastructure
There are numerous restaurants in the downtown area and hotels are also within walking distance.
CloudMatrix is Huawei’s unified AI development and deployment platform designed to support scalable, production-grade inference pipelines.
This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level AI professionals who wish to deploy and monitor AI models using the CloudMatrix platform with CANN and MindSpore integration.
By the end of this training, participants will be able to:
Use CloudMatrix for model packaging, deployment, and serving.
Convert and optimize models for Ascend chipsets.
Set up pipelines for real-time and batch inference tasks.
Monitor deployments and tune performance in production settings.
Format of the Course
Interactive lecture and discussion.
Hands-on use of CloudMatrix with real deployment scenarios.
Guided exercises focused on conversion, optimization, and scaling.
Course Customization Options
To request a customized training for this course based on your AI infrastructure or cloud environment, please contact us to arrange.
Ascend, Biren, and Cambricon are leading AI hardware platforms in China, each offering unique acceleration and profiling tools for production-scale AI workloads.
This instructor-led, live training (online or onsite) is aimed at advanced-level AI infrastructure and performance engineers who wish to optimize model inference and training workflows across multiple Chinese AI chip platforms.
By the end of this training, participants will be able to:
Benchmark models on Ascend, Biren, and Cambricon platforms.
Identify system bottlenecks and memory/compute inefficiencies.
Apply graph-level, kernel-level, and operator-level optimizations.
Tune deployment pipelines to improve throughput and latency.
Format of the Course
Interactive lecture and discussion.
Hands-on use of profiling and optimization tools on each platform.
Guided exercises focused on practical tuning scenarios.
Course Customization Options
To request a customized training for this course based on your performance environment or model type, please contact us to arrange.
Chinese GPU architectures such as Huawei Ascend, Biren, and Cambricon MLUs offer CUDA alternatives tailored for local AI and HPC markets.
This instructor-led, live training (online or onsite) is aimed at advanced-level GPU programmers and infrastructure specialists who wish to migrate and optimize existing CUDA applications for deployment on Chinese hardware platforms.
By the end of this training, participants will be able to:
Evaluate compatibility of existing CUDA workloads with Chinese chip alternatives.
Port CUDA codebases to Huawei CANN, Biren SDK, and Cambricon BANGPy environments.
Compare performance and identify optimization points across platforms.
Address practical challenges in cross-architecture support and deployment.
Format of the Course
Interactive lecture and discussion.
Hands-on code translation and performance comparison labs.
Guided exercises focused on multi-GPU adaptation strategies.
Course Customization Options
To request a customized training for this course based on your platform or CUDA project, please contact us to arrange.
Huawei Ascend is a family of AI processors designed for high-performance inference and training.
This instructor-led, live training (online or onsite) is aimed at intermediate-level AI engineers and data scientists who wish to develop and optimize neural network models using Huawei’s Ascend platform and the CANN toolkit.
By the end of this training, participants will be able to:
Set up and configure the CANN development environment.
Develop AI applications using MindSpore and CloudMatrix workflows.
Optimize performance on Ascend NPUs using custom operators and tiling.
Deploy models to edge or cloud environments.
Format of the Course
Interactive lecture and discussion.
Hands-on use of Huawei Ascend and CANN toolkit in sample applications.
Guided exercises focused on model building, training, and deployment.
Course Customization Options
To request a customized training for this course based on your infrastructure or datasets, please contact us to arrange.
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