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

Huawei Ascend comprises a series of AI processors engineered for high-performance inference and model training.

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

Upon completing this course, participants will be capable of:

• Configuring and setting up the CANN development environment.
• Creating AI applications via MindSpore and CloudMatrix workflows.
• Enhancing performance on Ascend NPUs through custom operators and tiling techniques.
• Deploying models into edge or cloud environments.

Course Format

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

Customization Options

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

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

This instructor-led training session, available both online and onsite, targets intermediate-level AI developers and engineers looking to efficiently deploy trained AI models onto Huawei Ascend hardware. The course utilizes the CANN toolkit along with tools like MindSpore, TensorFlow, or PyTorch.

Upon completing this training, participants will be equipped to:

• Gain a solid understanding of the CANN architecture and its critical role in the AI deployment pipeline.
• Convert and adapt models from popular frameworks into formats compatible with Ascend processors.
• Utilize tools such as ATC, OM model conversion utilities, and MindSpore for inference on both edge devices and cloud environments.
• Diagnose deployment challenges and optimize performance specifically for Ascend hardware.

Course Format

• Interactive lectures combined with live demonstrations.
• Practical hands-on labs using CANN tools alongside Ascend simulators or physical devices.
• Real-world deployment scenarios based on actual AI models.

Customization Options for the Course

• For those interested in a customized training version of this course, please contact us to arrange details.

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 session is available either online or onsite. It targets beginner-level AI developers looking to grasp how CANN integrates into the model lifecycle—from training through to deployment—and how it collaborates with popular frameworks such as MindSpore, TensorFlow, and PyTorch.

Upon completing this training, participants will be capable of:

• Comprehending the purpose and architecture of the CANN toolkit.
• Establishing a development environment utilizing CANN and MindSpore.
• Converting and deploying a simple AI model onto Ascend hardware.
• Acquiring foundational knowledge to support future CANN optimization or integration initiatives.

Format of the Course

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

Course Customization Options

• For those interested in customized training for this course, please reach out to us to arrange it.

The Ascend CANN toolkit from Huawei facilitates robust AI inference on edge hardware, including the Ascend 310. This toolkit offers critical utilities for compiling, optimizing, and deploying machine learning models in environments where computational power and memory are limited.

This instructor-led live training, available online or in-person, targets intermediate AI developers and integrators looking to deploy and optimize their models on Ascend edge devices using the CANN toolchain.

Upon completing this course, participants will be capable of:

• Preparing and converting AI models for the Ascend 310 using CANN utilities.
• Constructing efficient inference pipelines utilizing MindSpore Lite and AscendCL.
• Enhancing model performance within constrained compute and memory settings.
• Deploying and monitoring AI applications in practical edge scenarios.

Course Format

• Interactive lectures combined with live demonstrations.
• Practical lab exercises featuring edge-specific models and scenarios.
• Live deployment demonstrations on both virtual and physical edge hardware.

Customization Options

• For tailored training options, please contact us to make arrangements.

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

This instructor-led live training session (available online or onsite) targets advanced-level AI developers and system engineers who aim to optimize inference performance by leveraging CANN’s sophisticated toolset, including the Graph Engine, TIK, and capabilities for custom operator development.

Upon completing this training, participants will be able to:

• Gain a comprehensive understanding of CANN's runtime architecture and performance lifecycle.
• Utilize profiling tools and the Graph Engine to conduct thorough performance analysis and optimization.
• Develop and optimize custom operators using TIK and TVM.
• Address memory bottlenecks and significantly improve model throughput.

Course Format

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

Course Customization Options

• To request a tailored training session for this course, please contact us to arrange it.

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

This instructor-led live training, available online or onsite, is targeted at intermediate-level AI professionals looking to build, deploy, and optimize vision and language models using the CANN SDK for production environments.

Upon completion of this training, participants will be capable of:

• Deploying and optimizing computer vision (CV) and NLP models using CANN and AscendCL.
• Utilizing CANN tools to convert models and seamlessly 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 combined with live demonstrations.
• Practical hands-on labs focusing on model deployment and performance profiling.
• Live pipeline design exercises using real-world CV and NLP use cases.

Course Customization Options

• For customized training arrangements, please contact us directly.

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

This instructor-led, live training session—available both online and on-site—is designed for experienced system developers aiming to construct, deploy, and fine-tune custom operators for AI models leveraging CANN’s TIK programming model and TVM compiler integration.

Upon completing this training, participants will achieve the following:

• Develop and test custom AI operators using the TIK DSL for Ascend processors.
• Embed custom operations into the CANN runtime and execution graph.
• Utilize TVM for operator scheduling, auto-tuning, and benchmarking tasks.
• Debug and optimize instruction-level performance tailored to specific computation patterns.

Course Format

• Interactive lectures combined with live demonstrations.
• Practical coding exercises involving operators via TIK and TVM pipelines.
• Testing and tuning performed on Ascend hardware or within simulator environments.

Customization Options for the Course

• For those seeking a tailored training experience for this course, please reach out to us to arrange it.