AI Inference and Deployment with CloudMatrix Training Course

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

This instructor-led, live training (available online or onsite) is targeted at intermediate-level AI engineers and data scientists who aim 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 effectively.
• Develop AI applications leveraging MindSpore and CloudMatrix workflows.
• Enhance performance on Ascend NPUs through the use of custom operators and tiling techniques.
• Deploy models to edge or cloud environments seamlessly.

Format of the Course

• Interactive lecture and discussion sessions.
• Practical hands-on use of Huawei Ascend and the CANN toolkit in sample applications.
• Guided exercises focused on building, training, and deploying models.

Course Customization Options

• For a customized training tailored to your infrastructure or datasets, please contact us to arrange.

CANN (Compute Architecture for Neural Networks) is Huawei’s AI computing stack designed for deploying and optimizing AI models on Ascend AI processors.

This instructor-led, live training (available online or onsite) is targeted at intermediate-level AI developers and engineers who aim to deploy trained AI models efficiently on Huawei Ascend hardware using the CANN toolkit and tools such as MindSpore, TensorFlow, or PyTorch.

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

• Understand the architecture of CANN and its role in the AI deployment pipeline.
• Convert and adapt models from popular frameworks into Ascend-compatible formats.
• Utilize tools like ATC, OM model conversion, and MindSpore for edge and cloud inference.
• Diagnose deployment issues and optimize performance on Ascend hardware.

Format of the Course

• Interactive lecture and demonstration.
• Hands-on lab work using CANN tools and Ascend simulators or devices.
• Practical deployment scenarios based on real-world AI models.

Course Customization Options

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

This instructor-led, live training in Uzbekistan (online or onsite) is aimed at beginner-level to intermediate-level AI engineers and software developers who wish to gain a foundational understanding of AI engineering principles and practices.

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

• Understand the core concepts and technologies behind AI and machine learning.
• Implement basic machine learning models using TensorFlow and PyTorch.
• Apply AI techniques to solve practical problems in software development.
• Manage and maintain AI projects using best practices in AI engineering.
• Recognize the ethical implications and responsibilities involved in developing AI systems.

This instructor-led, live training in Uzbekistan (online or onsite) is aimed at intermediate-level to advanced-level AI professionals and software developers who wish to build intelligent applications using AI and ML.

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

• Understand the advanced concepts and technologies behind AI and ML.
• Analyze and visualize data to inform AI/ML model development.
• Build, train, and deploy AI/ML models effectively.
• Create intelligent applications that can solve real-world problems.
• Evaluate the ethical implications of AI applications in various industries.

CANN (Compute Architecture for Neural Networks) is 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 targeted at beginner-level AI developers who want to understand how CANN integrates into the model lifecycle from training to deployment, and how it works with frameworks such as MindSpore, TensorFlow, and PyTorch.

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

• Comprehend the purpose and architecture of the CANN toolkit.
• Set up a development environment using CANN and MindSpore.
• Convert and deploy a simple AI model on Ascend hardware.
• Acquire foundational knowledge for future CANN optimization or integration projects.

Format of the Course

• Interactive lectures and discussions.
• Hands-on labs involving simple model deployment.
• Step-by-step guidance through the CANN toolchain and integration points.

Course Customization Options

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

Huawei's Ascend CANN toolkit facilitates robust AI inference on edge devices like the Ascend 310. This toolkit offers essential tools for compiling, optimizing, and deploying models in environments with limited compute and memory resources.

This instructor-led, live training (available both online and onsite) is designed for intermediate-level AI developers and integrators who want 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 deployment on the Ascend 310 using CANN tools.
• Construct lightweight inference pipelines with MindSpore Lite and AscendCL.
• Enhance model performance in settings with constrained compute and memory.
• Deploy and monitor AI applications in practical edge use cases.

Format of the Course

• Interactive lectures and demonstrations.
• Hands-on lab work with models and scenarios specific to edge devices.
• Live deployment examples on either 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, ranging from the low-level CANN SDK to the high-level MindSpore framework, provides a seamless and integrated environment optimized for AI development and deployment on Ascend hardware.

This instructor-led, live training (available both online and onsite) is designed for technical professionals at beginner to intermediate levels who want to gain a comprehensive understanding of how CANN and MindSpore work together to support the entire AI lifecycle management and infrastructure decisions.

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

• Grasp the layered architecture of Huawei’s AI compute stack.
• Recognize how CANN facilitates model optimization and hardware-level deployment.
• Assess the MindSpore framework and toolchain in comparison to industry alternatives.
• Integrate Huawei's AI stack into enterprise or cloud/on-prem environments effectively.

Format of the Course

• Interactive lectures and discussions.
• Live system demonstrations and case studies.
• Optional guided labs focusing on the model flow from MindSpore to CANN.

Course Customization Options

• For a customized training tailored to your specific needs, please contact us to arrange.

CANN SDK (Compute Architecture for Neural Networks) is Huawei’s AI computing foundation that enables 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 designed for advanced-level AI developers and system engineers who want to enhance 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:

• Comprehend CANN's runtime architecture and performance lifecycle.
• Utilize profiling tools and the Graph Engine for performance analysis and optimization.
• Develop and optimize custom operators using TIK and TVM.
• Address memory bottlenecks and improve model throughput.

Format of the Course

• Interactive lectures and discussions.
• Hands-on labs with real-time profiling and operator tuning.
• Optimization exercises using edge-case deployment scenarios.

Course Customization Options

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

The CANN SDK (Compute Architecture for Neural Networks) offers robust tools for deploying and optimizing real-time AI applications in computer vision and natural language processing, particularly on Huawei Ascend hardware.

This instructor-led, live training (available both online and onsite) is designed for intermediate-level AI practitioners who aim to build, deploy, and optimize vision and language models using the CANN SDK for production scenarios.

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

• Deploy and optimize computer vision (CV) and natural language processing (NLP) models using CANN and AscendCL.
• Utilize CANN tools for model conversion and integration into live pipelines.
• Enhance inference performance for tasks such as detection, classification, and sentiment analysis.
• Construct real-time CV/NLP pipelines suitable for edge or cloud-based deployment scenarios.

Format of the Course

• Interactive lecture with demonstrations.
• Hands-on lab sessions focusing on model deployment and performance profiling.
• Live pipeline design using practical CV and NLP use cases.

Course Customization Options

• For a customized training session tailored to your specific needs, please contact us to arrange.

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

This instructor-led, live training (available online or on-site) is designed for advanced-level system developers who aim to build, deploy, and fine-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 operations into the CANN runtime and execution graph.
• Utilize 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.

Chinese GPU architectures like Huawei Ascend, Biren, and Cambricon MLUs provide CUDA alternatives specifically designed for the local AI and HPC markets.

This instructor-led, live training (online or onsite) is targeted at advanced-level GPU programmers and infrastructure specialists who want to migrate and optimize existing CUDA applications for deployment on Chinese hardware platforms.

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

• Assess the compatibility of existing CUDA workloads with Chinese chip alternatives.
• Adapt CUDA codebases to Huawei CANN, Biren SDK, and Cambricon BANGPy environments.
• Evaluate performance and pinpoint optimization opportunities across platforms.
• Tackle practical challenges in supporting and deploying cross-architecture solutions.

Format of the Course

• Interactive lectures and discussions.
• Hands-on code translation and performance comparison labs.
• Guided exercises focusing 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.

This instructor-led, live training in is aimed at anyone who wants to ensure their organization is compliant, minimizes risks, and empowers your workforce to leverage AI safely and ethically.

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

• Understand how AI systems function and their potential applications.
• Identify risks and limitations associated with AI systems.
• Adhere to relevant legal and ethical requirements.

This instructor-led, live training in Uzbekistan (online or onsite) is aimed at beginner-level IT professionals who wish to gain a foundational understanding of intelligent applications and how they can be applied in various industries.

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

• Understand the history, principles, and impact of artificial intelligence.
• Identify and apply different machine learning algorithms.
• Manage and analyze data effectively for AI applications.
• Recognize the practical applications and limitations of AI in different sectors.
• Discuss the ethical considerations and societal implications of AI technology.

This instructor-led, live training in Uzbekistan (online or onsite) is aimed at intermediate-level to advanced-level data scientists, engineers, and AI practitioners who wish to master the intricacies of intelligent applications and leverage them to solve complex, real-world problems.

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

• Implement and analyze deep learning architectures.
• Apply machine learning at scale in a distributed computing environment.
• Design and execute reinforcement learning models for decision-making.
• Develop sophisticated NLP systems for language understanding.
• Utilize computer vision techniques for image and video analysis.
• Address ethical considerations in the development and deployment of AI systems.

Ascend, Biren, and Cambricon are prominent AI hardware platforms in China, each providing specialized acceleration and profiling tools designed for large-scale AI workloads.

This instructor-led, live training (available online or on-site) is tailored for advanced AI infrastructure and performance engineers who aim to optimize model inference and training workflows across various Chinese AI chip platforms.

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

• Evaluate models on Ascend, Biren, and Cambricon platforms.
• Pinpoint system bottlenecks and inefficiencies in memory and computation.
• Implement optimizations at the graph level, kernel level, and operator level.
• Adjust deployment pipelines to enhance throughput and reduce latency.

Format of the Course

• Interactive lecture and discussion sessions.
• 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 program based on your specific performance environment or model type, please contact us to arrange.