Austin, TX – Regus at Dobie Center

2021 Guadalupe Street, Suite 260, Austin, United States, 78705

The venue is located in the vibrant West Campus neighborhood near the University of Texas at the Dobie Center, easily reachable by car via I‑35 or I‑35 Frontage Road and Loop 1, with on-site and street parking nearby. From Austin–Bergstrom International Airport (AUS), about 11 miles southeast, a taxi or rideshare takes around 20–25 minutes via TX‑71 West and I‑35 North. Public transit users can take Capital Metro routes to the University of Texas/Dobie Mall stop directly in front of the building, placing it within a short walk for attendees without cars.

Austin, TX - Regus - Littlefield Congress

106 E 6th St, Austin, United States, 78701

The venue is conveniently situated near I‑35 and US‑183, making it easily accessible by car, with both public and garage parking options—such as the Littlefield Garage at 508 Brazos—located within walking distance. For those using public transportation, the venue is just a short walk from the Downtown Station (CapMetro) and is served by several bus routes. Travelers arriving by air will find that Austin-Bergstrom International Airport is approximately 8 miles away, providing straightforward access to and from the venue.

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:

  • Evaluate models on Ascend, Biren, and Cambricon platforms.
  • Identify system bottlenecks and memory/compute inefficiencies.
  • Implement graph-level, kernel-level, and operator-level optimizations.
  • Adjust deployment pipelines to enhance throughput and reduce latency.

Format of the Course

  • Interactive lecture and discussion.
  • Practical use of profiling and optimization tools on each platform.
  • Guided exercises focused on real-world tuning scenarios.

Course Customization Options

  • To request a customized training for government based on your specific performance environment or model type, please contact us to arrange.
Read more...

Migrating CUDA Applications to Chinese GPU Architectures

 21 Hours

Chinese GPU architectures, including Huawei Ascend, Biren, and Cambricon MLUs, offer CUDA alternatives specifically designed for the 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 for government use.

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

  • Evaluate the compatibility of existing CUDA workloads with Chinese chip alternatives.
  • Port CUDA codebases to Huawei CANN, Biren SDK, and Cambricon BANGPy environments.
  • Compare performance metrics and identify optimization opportunities across different platforms.
  • Address practical challenges in supporting and deploying applications across multiple architectures.

Format of the Course

  • Interactive lecture and discussion sessions.
  • 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 specific platform or CUDA project, please contact us to arrange.
Read more...

Cambricon MLU Development with BANGPy and Neuware

 21 Hours

Cambricon MLUs (Machine Learning Units) are specialized AI chips designed to optimize inference and training in edge and data center environments.

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 for government applications.

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

  • Set up and configure the BANGPy and Neuware development environments for government use.
  • Develop and optimize Python- and C++-based models for Cambricon MLUs in alignment with public sector workflows.
  • Deploy models to edge and data center devices running Neuware runtime, ensuring compliance with governance standards.
  • Integrate machine learning workflows with MLU-specific acceleration features to enhance performance and accountability.

Format of the Course

  • Interactive lecture and discussion focused on government applications.
  • Hands-on use of BANGPy and Neuware for development and deployment in a public sector context.
  • Guided exercises centered on optimization, integration, and testing tailored to government needs.

Course Customization Options

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

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Upcoming Courses

Performance Optimization on Ascend, Biren, and Cambricon

2026-01-19 09:30
21 hours
Austin, TX - Regus - Littlefield Congress
$ 4054 (Online)
$ 4054 (Classroom)

Cambricon MLU Development with BANGPy and Neuware

2026-02-02 09:30
21 hours
Austin, TX – Regus at Dobie Center
$ 4054 (Online)
$ 4054 (Classroom)

Cambricon MLU Development with BANGPy and Neuware

2026-02-16 09:30
21 hours
Austin, TX - Regus - Littlefield Congress
$ 4054 (Online)
$ 4054 (Classroom)

Migrating CUDA Applications to Chinese GPU Architectures

2026-03-02 09:30
21 hours
Austin, TX – Regus at Dobie Center
$ 4054 (Online)
$ 4054 (Classroom)

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