As global GPU supply chains evolve, innovation provides the solution, with Biren standing out as a bold response to the need for high-performance AI computing.
Within these instructor-led programs, participants engage hands-on with Biren’s architecture, developing proficiency in memory throughput, optimizing parallelism, and fine-tuning deep learning models on BR100-class accelerators.
Training is accessible via interactive live online sessions through a remote desktop environment, or through onsite live training in Plovdiv. The curriculum incorporates exercises modeled after real-world, large-scale AI workloads.
Organizations in Plovdiv have the option to host onsite sessions at their own premises or participate in team-based courses at a NobleProg training center in Plovdiv.
Also known as the Biren GPU, BR100, or Chinese AI accelerator, this course track is vital for teams navigating the path toward computational independence.
NobleProg – Your Local Training Provider
Business Center Plovdiv
Han Kubrat St 1, Plovdiv, Bulgaria, 4017
This is the most modern business center in the city, with all the necessary functionalities, while being located in a green part of the city.
It is about 20 minutes by bus from the main train station as well as the city center.
Enhance AI workload performance on Ascend, Biren, and Cambricon through this practical training in Plovdiv. Master model benchmarking, pinpoint bottlenecks, and deploy graph, kernel, and operator-level optimizations. Refine deployment pipelines to optimize throughput and latency across these top-tier platforms.
Transition CUDA applications to Chinese GPU ecosystems, such as Huawei Ascend and Biren, within Plovdiv. This instructor-led course assists advanced programmers in code translation and performance refinement, featuring practical labs for porting CUDA codebases to emerging SDKs.
This live training on Plovdiv empowers developers to program and optimize applications on Biren AI accelerators. Learners will explore GPU architecture, configure the SDK, and adapt CUDA code for Biren. The course emphasizes performance tuning and debugging techniques.
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