Wanneer mondiale GPU supply chains veranderen, biedt innovatie antwoord — en Biren treedt op als China's dure reactie op hoogprestatie AI-computing.
In deze door instructeurs geleide cursussen, onderzoeken de deelnemers de architectuur van Biren hands-on: het meester worden van geheugen doorvoer, het optimaliseren van parallelisme en het afstellen van deep learning modellen op BR100-klasse accelerators.
Training is beschikbaar als online live training via een interactieve remote desktop, of onsite live training in Enschede TU, met oefeningen geïnspireerd op real-world AI workloads op grote schaal.
Organisaties in Enschede TU kunnen onsite sessies op hun locaties organiseren of deelnemen aan teamgebaseerde cursussen op een NobleProg trainingscentrum in Enschede TU.
Ook bekend als Biren GPU, BR100, of Chinese AI accelerator, is deze cursuslijn essentieel voor teams die de toekomst van computatieve onafhankelijkheid verkennen.
Capitool 10 is gelegen tegenover de Universiteit Twente en op slechts vier minuten lopen van het treinstation Enschede Kennispark. Het pand ligt halverwege Enschede en Hengelo en is omgeven door bedrijven die verbonden zijn aan de universiteit; een gewilde omgeving voor start-ups en groeiende bedrijven. In de buurt van het pand vindt u bovendien de snelwegen naar Enschede, Hengelo en Amsterdam.
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.
Biren AI Accelerators are high-performance GPUs designed for AI and HPC workloads with support for large-scale training and inference.
This instructor-led, live training (online or onsite) is aimed at intermediate-level to advanced-level developers who wish to program and optimize applications using Biren’s proprietary GPU stack, with practical comparisons to CUDA-based environments.
By the end of this training, participants will be able to:
Understand Biren GPU architecture and memory hierarchy.
Set up the development environment and use Biren’s programming model.
Translate and optimize CUDA-style code for Biren platforms.
Apply performance tuning and debugging techniques.
Format of the Course
Interactive lecture and discussion.
Hands-on use of Biren SDK in sample GPU workloads.
Guided exercises focused on porting and performance tuning.
Course Customization Options
To request a customized training for this course based on your application stack or integration needs, please contact us to arrange.
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