Understanding Huawei’s AI Compute Stack: From CANN to MindSpore Training Course

Huawei Ascend represents a suite of AI processors engineered to deliver high-performance capabilities for both inference and training tasks.

This instructor-led live training session, available either online or onsite, is designed for AI engineers and data scientists at an intermediate level who aim to develop and refine neural network models utilizing Huawei’s Ascend platform alongside the CANN toolkit.

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

• Establish and configure the CANN development environment.
• Create AI applications leveraging MindSpore and CloudMatrix workflows.
• Enhance performance on Ascend NPUs through the use of custom operators and tiling techniques.
• Deploy models across edge or cloud infrastructure.

Course Delivery Format

• Engaging lectures paired with interactive discussions.
• Practical application of Huawei Ascend and the CANN toolkit within sample projects.
• Guided exercises targeting model construction, training, and deployment.

Customization Opportunities

• For tailored training based on your specific infrastructure or datasets, please reach out to us to make arrangements.

CANN (Compute Architecture for Neural Networks) serves as Huawei's comprehensive AI compute stack, designed for deploying and optimizing AI models on Ascend AI processors.

This instructor-led, live training session, available both online and onsite, targets intermediate-level AI developers and engineers seeking to efficiently deploy trained AI models onto Huawei Ascend hardware. The curriculum utilizes the CANN toolkit alongside popular frameworks such as MindSpore, TensorFlow, and PyTorch.

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

• Comprehend the CANN architecture and its critical function within the AI deployment pipeline.
• Convert and adapt models from leading frameworks into formats compatible with Ascend devices.
• Leverage tools such as ATC, OM model conversion, and MindSpore for both edge and cloud inference applications.
• Identify deployment challenges and optimize performance on Ascend hardware.

Course Format

• Interactive lectures combined with live demonstrations.
• Practical lab exercises utilizing CANN tools, Ascend simulators, or physical devices.
• Real-world deployment scenarios based on existing AI models.

Customization Options

• For personalized training requirements, please contact us to arrange a customized session.

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

This instructor-led live training, available in online or onsite formats, is tailored for beginner-level AI developers. It provides a clear understanding of how CANN integrates into the end-to-end model lifecycle—from training through to deployment—and demonstrates its compatibility with major frameworks such as MindSpore, TensorFlow, and PyTorch.

Upon completing this training, participants will be equipped to:

• Grasp the fundamental purpose and architectural design of the CANN toolkit.
• Configure a development environment utilizing both CANN and MindSpore.
• Successfully convert and deploy a basic AI model onto Ascend hardware.
• Acquire the foundational knowledge necessary for future initiatives involving CANN optimization or integration.

Course Format

• Engaging lectures combined with interactive discussions.
• Practical, hands-on labs focused on simple model deployment.
• Detailed, step-by-step walkthroughs of the CANN toolchain and key integration points.

Customization Options

• For organizations seeking tailored training solutions, please reach out to us to arrange a customized session.

Huawei's Ascend CANN toolkit empowers powerful AI inference on edge devices like the Ascend 310. It provides the essential tools needed to compile, optimize, and deploy models in environments where computing power and memory are limited.

This instructor-led, live training (available online or onsite) is designed for intermediate 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 the Ascend 310 using CANN tools.
• Build lightweight inference pipelines using MindSpore Lite and AscendCL.
• Optimize model performance for environments with constrained compute and memory.
• Deploy and monitor AI applications in real-world edge scenarios.

Course Format

• Interactive lectures and demonstrations.
• Hands-on labs featuring edge-specific models and scenarios.
• Live deployment examples on virtual or physical edge hardware.

Customization Options

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

The CANN SDK (Compute Architecture for Neural Networks) serves as Huawei’s foundational AI compute platform, empowering developers to fine-tune and maximize the performance of neural networks deployed on Ascend AI processors.

This instructor-led live training session, available both online and onsite, is tailored for advanced AI developers and system engineers aiming to boost inference performance through CANN’s sophisticated toolset. Key areas include the Graph Engine, TIK, and custom operator development.

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

• Comprehend the runtime architecture and performance lifecycle within CANN.
• Leverage profiling tools and the Graph Engine for detailed performance analysis and optimization.
• Develop and refine custom operators utilizing TIK and TVM.
• Address memory bottlenecks and enhance model throughput.

Course Format

• Interactive lectures and group discussions.
• Practical labs featuring real-time profiling and operator tuning.
• Optimization exercises grounded in real-world edge-case deployment scenarios.

Customization Options

• For organizations seeking tailored training for this course, please contact us to arrange specifics.

The CANN SDK (Compute Architecture for Neural Networks) equips developers with robust deployment and optimization tools for real-time AI applications in computer vision and NLP, specifically tailored for Huawei Ascend hardware.

This instructor-led live training, available online or onsite, targets intermediate-level AI practitioners aiming to build, deploy, and optimize vision and language models via the CANN SDK for production environments.

Upon completion, participants will be capable of:

• Deploying and optimizing CV and NLP models utilizing CANN and AscendCL.
• Employing CANN utilities to convert models and integrate them into active pipelines.
• Enhancing inference performance for tasks such as detection, classification, and sentiment analysis.
• Constructing real-time CV/NLP pipelines suitable for edge or cloud-based deployment scenarios.

Course Format

• Interactive lectures accompanied by demonstrations.
• Practical labs focused on model deployment and performance profiling.
• Live pipeline design exercises using real-world CV and NLP use cases.

Customization Options

• For customized training arrangements for this course, please reach out to us.

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

This instructor-led, live training, available both online and onsite, is designed for advanced system developers aiming to build, deploy, and fine-tune custom operators for AI models. The curriculum leverages CANN’s TIK programming model alongside TVM compiler integration.

Upon completing this training, participants will be equipped to:

• Develop and test custom AI operators utilizing the TIK DSL for Ascend processors.
• Seamlessly integrate custom operators into the CANN runtime and execution graphs.
• Apply TVM for operator scheduling, automatic tuning, and performance benchmarking.
• Debug and optimize instruction-level performance across various custom computation patterns.

Course Format

• Engaging lectures combined with practical demonstrations.
• Practical coding exercises for operators using TIK and TVM pipelines.
• Testing and tuning activities performed on Ascend hardware or emulators.

Course Customization Options

• For inquiries regarding customized training for this course, please reach out to us to arrange a session.