Cambricon’s MLU chips serve as more than simple processors; they represent China’s strategic response to the need for scalable and efficient AI acceleration within cloud, edge, and data center ecosystems.
This instructor-led training provides engineers and AI developers with a comprehensive walkthrough of the Cambricon stack, covering the journey from deep learning model deployment to performance optimization on MLU hardware.
Training is available as live online sessions via interactive remote desktop, or as onsite programs in Gaia, where hands-on labs are designed to reflect the specific AI challenges that Cambricon technology addresses.
Whether you are expanding an AI laboratory or securing the future capabilities of your data center team, onsite sessions can be held at your facility in Gaia or at a NobleProg training center tailored for immersive technical development.
Commonly known as Cambricon AI, the MLU accelerator, or the Machine Learning Unit, this training supports teams aiming to build AI infrastructure that extends beyond the traditional GPU paradigm.
NobleProg – Your Local Training Provider
Holiday Inn Porto - Gaia
220, Rua Diogo Macedo, 220, Vila Nova de Gaia 4400-107 , Gaia, Portugal
From Porto by Metro
If you're coming from Porto city centre:
Take the Metro Line D (yellow line) toward Vila d’Este.
Get off at João de Deus.
From João de Deus, walk about 13 minutes to: Rua Diogo Macedo 220, 4400-107 Vila Nova de Gaia.
From Vila Nova de Gaia train station
If by “local train station” you mean Vila Nova de Gaia-Devesas:
The address is approximately 12 minutes walking from Vila Nova de Gaia station according to the accommodation's location information.
You can therefore walk directly rather than taking the metro.
Master the optimization of AI workloads on Ascend, Biren, and Cambricon through this practical training in Gaia. You will learn to benchmark models, uncover performance bottlenecks, and apply graph, kernel, and operator-level optimizations. Additionally, you will tune deployment pipelines to boost throughput and minimize latency across these leading platforms.
Migrate CUDA applications to Chinese GPU architectures such as Huawei Ascend and Biren in Gaia. This instructor-led course guides advanced programmers through code translation and performance optimization, featuring hands-on labs for porting CUDA codebases to new SDKs.
This instructor-led live training in Gaia empowers developers with the necessary skills to construct and deploy AI models utilizing BANGPy and Neuware on Cambricon MLUs. Learners will configure their environments, develop optimized models, and integrate MLU acceleration into edge and data center applications.
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