Suzhou, Jinghope Plaza

11/F, 11/F, Tower 2, 88 Hua Chi Street, SIP, Suzhou, China, 215021

Situated right in the core of the Suzhou industry zone, The Regus Centre is on the 11th floor of Jinghope Plaza. Jinghope Plaza is a mixed use complex comprising a high-end shopping mall, 5 star hotel and international Grade A office building. It is one of the most prestigious landmarks in the financial center of Suzhou. Advanced facilities and central location attract many Fortune 500 companies such as Nokia, Philips and 3M. Jinghope Plaza has easy access to excellent facilities and amenities in Suzhou. Metro Line 1 Times Square station is just in the basement of the complex. The high-speed train station which provides easy transportation to Shanghai and Nanjing is only a 5 minutes drive from the centre.

Jinhe Plaza

11th Floor, No. 2, 88 Huachi Street, Industrial Park, Suzhou, China, 215021

The center of Jinhe Plaza is located at the core of Suzhou Industrial Zone, on the east bank of Jinji Lake. Jinhe Plaza is a comprehensive building, including high-end shopping malls, five-star hotels, international Grade A office buildings, and Regus is located on the eleventh floor of the building. As the most famous landmark in Suzhou Financial Center, with its advanced facilities and central location, it has attracted many Fortune 500 companies such as Nokia, Philips and 3M. Jinhe Plaza provides easy access to all major core areas of Suzhou. Metro Line 1 Times Square Station is located on the basement of the building, while the High Speed ​​Rail Station to Shanghai and Nanjing is a 5-minute drive away.

Explore Our Courses

Performance Optimization on Ascend, Biren, and Cambricon

 21 Hours

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.
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Migrating CUDA Applications to Chinese GPU Architectures

 21 Hours

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.
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Cambricon MLU Development with BANGPy and Neuware

 21 Hours

Cambricon MLUs (Machine Learning Units) are specialized AI chips optimized for inference and training in edge and datacenter scenarios.

This instructor-led, live training (online or onsite) is aimed at intermediate-level developers who wish to build and deploy AI models using the BANGPy framework and Neuware SDK on Cambricon MLU hardware.

By the end of this training, participants will be able to:

  • Set up and configure the BANGPy and Neuware development environments.
  • Develop and optimize Python- and C++-based models for Cambricon MLUs.
  • Deploy models to edge and data center devices running Neuware runtime.
  • Integrate ML workflows with MLU-specific acceleration features.

Format of the Course

  • Interactive lecture and discussion.
  • Hands-on use of BANGPy and Neuware for development and deployment.
  • Guided exercises focused on optimization, integration, and testing.

Course Customization Options

  • To request a customized training for this course based on your Cambricon device model or use case, please contact us to arrange.
Read more...

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Upcoming Courses

Cambricon MLU Development with BANGPy and Neuware

2025-10-13 09:30
21 hours
Jinhe Plaza

Performance Optimization on Ascend, Biren, and Cambricon

2025-10-27 09:30
21 hours
Suzhou, Jinghope Plaza

Cambricon MLU Development with BANGPy and Neuware

2025-11-10 09:30
21 hours
Jinhe Plaza

Migrating CUDA Applications to Chinese GPU Architectures

2025-11-24 09:30
21 hours
Suzhou, Jinghope Plaza

Migrating CUDA Applications to Chinese GPU Architectures

2025-12-08 09:30
21 hours
Jinhe Plaza

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