NobleProg Training Place, City Albuquerque, NM - Regus at Marquette Avenue

Albuquerque, NM - Regus at Marquette Avenue

500 Marquette Ave NW, Albuquerque, United States, 87102

The venue is easily accessible by car via I‑25 and I‑40, with ample parking available in nearby public garages and surface lots. For those arriving from out of town, Albuquerque International Sunport is located just 5 miles away, providing convenient air travel access. Additionally, the location is well-served by public transit, within walking distance of several ABQ RIDE bus routes and near the Downtown Rail Runner station.

Santa Fe, NM - Regus at Washington Avenue

150 Washington Avenue, Santa Fe, United States, 87501

The venue is easily accessible by car via I‑25, with secure parking available both on site and in nearby private garages. For those traveling by air, Albuquerque International Sunport (ABQ) is located approximately 60 miles to the south, with shuttle and rental car options readily available. Public transit is also a convenient option, with multiple Santa Fe Trails bus routes and the Rail Runner shuttle stop within walking distance.

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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