When global GPU supply chains shift, innovation answers — and Biren emerges as China’s bold response to high-performance AI computing.
In these instructor-led courses, participants explore Biren’s architecture hands-on: mastering memory throughput, optimizing parallelism, and tuning deep learning models on BR100-class accelerators.
Training is available as online live training through an interactive remote desktop, or onsite live training in Lyon, featuring exercises inspired by real-world AI workloads at scale.
Organizations in Lyon can host onsite sessions at their facilities or join team-based courses at a NobleProg training center in Lyon.
Also referred to as Biren GPU, BR100, or Chinese AI accelerator, this course track is essential for teams navigating the future of computational independence.
NobleProg – Your Local Training Provider
Lyon, Swisslife Tower
NobleProg Lyon, 10 Place Charles Béraudier, Lyon, france, 69000
Located 200 meters far from the train station TGV, Swisslife Tower is today the most representative building of this quarter of Lyon. The Business Center offers you a perfect location for your training.
Gares TGV
100meters from Gare TGV Part-Dieu , porte du Rhône Exit
Aéroport
30 minutes from Lyon Saint Exupéry (Satolas)
Rhône Express from Saint Exupéry airport (Terminus Gare part-Dieu)
Ascend, Biren, and Cambricon represent the leading AI hardware platforms in China, each providing distinct acceleration and profiling capabilities for enterprise-scale AI workloads.
This instructor-led live training, available online or onsite, is designed for advanced AI infrastructure and performance engineers seeking to optimize model inference and training workflows across these diverse Chinese AI chip ecosystems.
Upon completion of this training, participants will be equipped to:
Benchmark models across Ascend, Biren, and Cambricon platforms.
Identify system bottlenecks and inefficiencies in memory and compute resources.
Implement optimizations at the graph, kernel, and operator levels.
Tune deployment pipelines to enhance throughput and reduce latency.
Course Format
Interactive lectures and discussions.
Practical application of profiling and optimization tools on each respective platform.
Guided exercises centered on real-world tuning scenarios.
Customization Options
To request a customized version of this course tailored to your specific performance environment or model architecture, please contact us to arrange.
Chinese GPU architectures, including Huawei Ascend, Biren, and Cambricon MLUs, provide alternatives to CUDA specifically designed for the domestic AI and high-performance computing (HPC) markets.
This instructor-led live training, available either online or onsite, targets advanced GPU developers and infrastructure specialists looking to migrate and optimize existing CUDA applications for deployment on Chinese hardware platforms.
Upon completion of this training, participants will be able to:
Assess the compatibility of current CUDA workloads with Chinese chip alternatives.
Port CUDA codebases to Huawei CANN, Biren SDK, and Cambricon BANGPy environments.
Compare performance metrics and identify key optimization opportunities across different platforms.
Address practical challenges related to cross-architecture support and deployment.
Format of the Course also allows for the evaluation of participants.
Interactive lectures and discussions.
Hands-on labs for code translation and performance comparison.
Guided exercises focusing on multi-GPU adaptation strategies.
Course Customization Options
To request customized training tailored to your specific platform or CUDA project, please contact us to arrange it.
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 also allows for the evaluation of participants.
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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