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 training capabilities.

This instructor-led live training session, available both online and onsite, targets intermediate-level data scientists and AI engineers looking to develop and optimize neural network models utilizing Huawei’s CANN toolkit and Ascend platform.

Upon completing this training, attendees will be equipped to:

• Establish and configure the CANN development environment.
• Create AI applications leveraging CloudMatrix workflows and MindSpore.
• Enhance performance on Ascend NPUs through tiling and custom operators.
• Deploy models to either cloud or edge environments.

Course Format

• Practical use of Huawei Ascend and the CANN toolkit within sample applications.
• Interactive discussions and lectures.
• Guided exercises centered on model building, training, and deployment.

Customization Options for the Course

• For tailored training aligned with your specific infrastructure or datasets, please get in touch with us to make arrangements.

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

This instructor-led live training session, available either online or onsite, is tailored for intermediate-level AI developers and engineers seeking to efficiently deploy trained AI models onto Huawei Ascend hardware. Participants will utilize the CANN toolkit alongside tools such as MindSpore, TensorFlow, or PyTorch.

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

• Gaining a deep understanding of the CANN architecture and its pivotal role within the AI deployment pipeline.
• Converting and adapting models originating from popular frameworks into formats compatible with Ascend.
• Leveraging tools such as ATC, OM model conversion, and MindSpore for both edge and cloud inference tasks.
• Diagnosing deployment-related issues and optimizing performance specifically on Ascend hardware.

Course Format

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

Course Customization Options

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

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 training, available online or onsite, is tailored for beginner-level AI developers seeking to grasp how CANN integrates into the model lifecycle, spanning from training to deployment, and its interoperability with frameworks such as MindSpore, TensorFlow, and PyTorch.

Upon completion of this course, 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 to Ascend hardware.
• Acquiring foundational knowledge to support future CANN optimization or integration projects.

Course Format

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

Customization Options for the Course

• For tailored training arrangements, please contact us to discuss your needs.

Huawei's Ascend CANN toolkit empowers powerful AI inference on edge devices like the Ascend 310. It provides crucial tools for compiling, optimizing, and deploying models in environments with limited compute and memory capacity.

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

Upon completing this training, participants will be able to:

• Prepare and convert AI models for the Ascend 310 using CANN tools.
• Construct lightweight inference pipelines utilizing MindSpore Lite and AscendCL.
• Optimize model performance within constrained compute and memory settings.
• 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.

Course Customization Options

• To request a 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 framework, enabling developers to fine-tune and maximize the performance of neural networks deployed on Ascend AI processors.

This instructor-led live training (available online or onsite) is designed for advanced AI developers and system engineers seeking to optimize inference performance through CANN’s sophisticated toolset, including the Graph Engine, TIK, and custom operator development.

Upon completing this training, participants will be able to:

• Grasp 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 enhance model throughput.

Course Format

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

Customization Options

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

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 (NLP), particularly on Huawei Ascend hardware.

This instructor-led training, available online or onsite, targets intermediate 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 able to:

• Deploy and optimize CV and NLP models utilizing CANN and AscendCL.
• Leverage CANN tools to convert models and integrate them into operational pipelines.
• Enhance inference performance for tasks such as object detection, classification, and sentiment analysis.
• Construct real-time CV/NLP pipelines tailored for edge or cloud-based deployment scenarios.

Course Format

• Interactive lectures and live demonstrations.
• Practical lab sessions focused on model deployment and performance profiling.
• Real-time pipeline design using practical CV and NLP use cases.

Customization Options

• For customized training arrangements for this course, please contact us directly.

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

This live, instructor-led training (available online or onsite) is designed for advanced system developers looking to build, deploy, and fine-tune custom operators for AI models by leveraging CANN’s TIK programming model and TVM compiler integration.

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

• Write and test custom AI operators using the TIK DSL for Ascend processors.
• Integrate custom operators 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.

Course Format

• Interactive lectures and live demonstrations.
• Hands-on coding exercises for operators using TIK and TVM pipelines.
• Testing and tuning performed on Ascend hardware or simulators.

Course Customization Options

• For information on requesting customized training for this course, please contact us to make arrangements.