NVIDIA GPU Programming - Extended Training Course

Huawei Ascend is a family of AI processors designed for high-performance inference and training.

This instructor-led, live training (online or onsite) is aimed at intermediate-level AI engineers and data scientists who wish to develop and optimize neural network models using Huawei’s Ascend platform and the CANN toolkit.

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

• Set up and configure the CANN development environment.
• Develop AI applications using MindSpore and CloudMatrix workflows.
• Optimize performance on Ascend NPUs using custom operators and tiling.
• Deploy models to edge or cloud environments.

Format of the Course

• Interactive lecture and discussion.
• Hands-on use of Huawei Ascend and CANN toolkit in sample applications.
• Guided exercises focused on model building, training, and deployment.

Course Customization Options

• To request a customized training for this course based on your infrastructure or datasets, please contact us to arrange.

CANN (Compute Architecture for Neural Networks) serves as Huawei's comprehensive AI compute stack, designed specifically for the efficient deployment and optimization of AI models on Ascend AI processors.

This live, instructor-led training, available both online and onsite, is tailored for intermediate-level AI developers and engineers seeking to deploy trained AI models effectively on Huawei Ascend hardware. The course leverages the CANN toolkit alongside popular frameworks such as MindSpore, TensorFlow, and PyTorch.

Upon completion, participants will possess the skills to:

• Grasp the CANN architecture and its pivotal role within the AI deployment pipeline.
• Convert and adapt models from major frameworks into Ascend-compatible formats.
• Utilize tools such as ATC, OM model conversion utilities, and MindSpore for both edge and cloud inference tasks.
• Diagnose deployment challenges and optimize performance specifically on Ascend hardware.

Course Delivery Format

• Engaging lectures combined with practical demonstrations.
• Hands-on laboratory sessions utilizing CANN tools and Ascend simulators or physical devices.
• Application of practical deployment scenarios based on real-world AI models.

Customization Options

• For customized training solutions tailored to this course, please reach out to us to arrange specific requirements.

CloudMatrix is Huawei’s integrated platform for AI development and deployment, engineered to facilitate scalable, production-ready inference workflows.

This live, instructor-led training—available online or onsite—is tailored for AI professionals ranging from beginners to intermediates who aim to deploy and oversee AI models through the CloudMatrix platform, leveraging integration with CANN and MindSpore.

Upon completion, participants will be equipped to:

• Utilize CloudMatrix for packaging, deploying, and serving models.
• Optimize and convert models specifically for Ascend chipsets.
• Establish pipelines designed for both real-time and batch inference operations.
• Track deployment metrics and refine performance within production environments.

Course Format

• Engaging lectures paired with open discussions.
• Practical application of CloudMatrix through realistic deployment scenarios.
• Structured exercises emphasizing model conversion, optimization, and scaling.

Customization Options

• For tailored training aligned with your specific AI infrastructure or cloud setup, please reach out to us to discuss arrangements.

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

• 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.

Cambricon MLUs (Machine Learning Units) are dedicated silicon solutions engineered to streamline inference and training workloads across both edge and data centre environments.

This live, instructor-led training, available either online or on-site, is designed for intermediate-level developers seeking to construct and deploy AI models leveraging the BANGPy framework and Neuware SDK on Cambricon MLU hardware.

Upon completing this training, participants will be equipped to:

• Configure and establish the BANGPy and Neuware development environments.
• Build and fine-tune Python- and C++-based models for Cambricon MLUs.
• Deploy models to edge and data centre devices operating with the Neuware runtime.
• Incorporate ML workflows with MLU-specific acceleration capabilities.

Course Structure

• Engaging lectures and facilitated discussions.
• Practical application of BANGPy and Neuware for development and deployment.
• Supervised exercises centred on optimization, integration, and validation.

Customization Opportunities

• To tailor this training to your specific Cambricon device model or application scenario, please reach out to us to make arrangements.

CANN (Compute Architecture for Neural Networks) serves as Huawei's AI computing toolkit, designed to compile, optimize, and deploy AI models on Ascend AI processors.

This instructor-led live training, available online or onsite, is tailored for beginner-level AI developers seeking to understand where CANN fits within the model lifecycle—from training to deployment—and how it integrates with frameworks such as MindSpore, TensorFlow, and PyTorch.

Upon completion of this training, participants will be equipped to:

• Grasp the purpose and architectural design of the CANN toolkit.
• Configure a development environment using CANN and MindSpore.
• Convert and deploy a simple AI model onto Ascend hardware.
• Acquire the foundational knowledge necessary for future CANN optimization or integration projects.

Course Format

• Engaging lectures and discussions.
• Practical hands-on labs focused on basic model deployment.
• Detailed walkthroughs of the CANN toolchain and its integration points.

Customization Options

• Interested in a customized training experience? Please reach out to us to arrange specific requirements.

Huawei's Ascend CANN toolkit enables powerful AI inference on edge devices such as the Ascend 310. CANN provides essential tools for compiling, optimizing, and deploying models where compute and memory are constrained.

This instructor-led, live training (online or onsite) is aimed at intermediate-level AI developers and integrators who wish to deploy and optimize models on Ascend edge devices using the CANN toolchain.

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

• Prepare and convert AI models for Ascend 310 using CANN tools.
• Build lightweight inference pipelines using MindSpore Lite and AscendCL.
• Optimize model performance for limited compute and memory environments.
• Deploy and monitor AI applications in real-world edge use cases.

Format of the Course

• Interactive lecture and demonstration.
• Hands-on lab work with edge-specific models and scenarios.
• Live deployment examples on virtual or physical edge hardware.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Huawei’s AI stack — from the low-level CANN SDK to the high-level MindSpore framework — offers a tightly integrated AI development and deployment environment optimized for Ascend hardware.

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level technical professionals who wish to understand how the CANN and MindSpore components work together to support AI lifecycle management and infrastructure decisions.

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

• Understand the layered architecture of Huawei’s AI compute stack.
• Identify how CANN supports model optimization and hardware-level deployment.
• Evaluate the MindSpore framework and toolchain in relation to industry alternatives.
• Position Huawei's AI stack within enterprise or cloud/on-prem environments.

Format of the Course

• Interactive lecture and discussion.
• Live system demos and case-based walkthroughs.
• Optional guided labs on model flow from MindSpore to CANN.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

CANN SDK (Compute Architecture for Neural Networks) is Huawei’s AI compute foundation that allows developers to fine-tune and optimize the performance of deployed neural networks on Ascend AI processors.

This instructor-led, live training (online or onsite) is aimed at advanced-level AI developers and system engineers who wish to optimize inference performance using CANN’s advanced toolset, including the Graph Engine, TIK, and custom operator development.

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

• Understand CANN's runtime architecture and performance lifecycle.
• Use profiling tools and Graph Engine for performance analysis and optimization.
• Create and optimize custom operators using TIK and TVM.
• Resolve memory bottlenecks and improve model throughput.

Format of the Course

• Interactive lecture and discussion.
• Hands-on labs with real-time profiling and operator tuning.
• Optimization exercises using edge-case deployment examples.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

The CANN SDK (Compute Architecture for Neural Networks) provides powerful deployment and optimization tools for real-time AI applications in computer vision and NLP, especially on Huawei Ascend hardware.

This instructor-led, live training (online or onsite) is aimed at intermediate-level AI practitioners who wish to build, deploy, and optimize vision and language models using the CANN SDK for production use cases.

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

• Deploy and optimize CV and NLP models using CANN and AscendCL.
• Use CANN tools to convert models and integrate them into live pipelines.
• Optimize inference performance for tasks like detection, classification, and sentiment analysis.
• Build real-time CV/NLP pipelines for edge or cloud-based deployment scenarios.

Format of the Course

• Interactive lecture and demonstration.
• Hands-on lab with model deployment and performance profiling.
• Live pipeline design using real CV and NLP use cases.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

CANN TIK (Tensor Instruction Kernel) and Apache TVM enable advanced optimization and customization of AI model operators for Huawei Ascend hardware.

This instructor-led, live training (online or onsite) is aimed at advanced-level system developers who wish to build, deploy, and tune custom operators for AI models using CANN’s TIK programming model and TVM compiler integration.

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

• Write and test custom AI operators using the TIK DSL for Ascend processors.
• Integrate custom ops into the CANN runtime and execution graph.
• Use TVM for operator scheduling, auto-tuning, and benchmarking.
• Debug and optimize instruction-level performance for custom computation patterns.

Format of the Course

• Interactive lecture and demonstration.
• Hands-on coding of operators using TIK and TVM pipelines.
• Testing and tuning on Ascend hardware or simulators.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

GPU solutions from China, including Huawei Ascend, Biren, and Cambricon MLUs, provide viable CUDA alternatives designed specifically for regional AI and HPC requirements.

This live, instructor-led session, available either online or onsite, is targeted at senior GPU developers and infrastructure experts aiming to adapt and refine existing CUDA applications for use on Chinese hardware platforms.

Upon completion, participants will be equipped to:

• Assess the compatibility of current CUDA workloads with Chinese chip options.
• Transfer CUDA codebases to Huawei CANN, Biren SDK, and Cambricon BANGPy environments.
• Benchmark performance and pinpoint optimization opportunities across different platforms.
• Navigate the practical issues involved in cross-architecture support and deployment.

Course Structure

• Engaging lectures and discussions.
• Practical labs for code conversion and performance analysis.
• Structured exercises concentrating on multi-GPU adaptation tactics.

Tailoring Options

• To arrange a bespoke training program aligned with your specific platform or CUDA project, please get in touch with us to make the necessary arrangements.

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.