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

The Huawei Ascend series comprises AI processors engineered for high-performance inference and training operations.

This instructor-led, live training session, available online or in-person, is designed for intermediate-level AI engineers and data scientists seeking to develop and optimize neural network models utilizing Huawei’s Ascend platform and the CANN toolkit. This curriculum is tailored for government agencies requiring advanced AI infrastructure expertise.

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

• Establish and configure the CANN development environment.
• Develop AI applications through MindSpore and CloudMatrix workflows.
• Enhance performance on Ascend NPUs by implementing custom operators and tiling techniques.
• Deploy models to edge or cloud environments for government use cases.

Course Format

• Interactive lectures and facilitated discussions.
• Hands-on application of Huawei Ascend and the CANN toolkit within sample applications.
• Guided exercises emphasizing model construction, training, and deployment.

Course Customization Options

• To request a customized training program aligned with specific infrastructure or dataset requirements, please contact us to arrange a consultation for government stakeholders.

This live training in US guides intermediate AI developers in deploying models on Ascend processors using the CANN toolkit. The curriculum covers converting frameworks like PyTorch and TensorFlow, optimizing performance, and debugging issues to support efficient edge and cloud inference scenarios for government use.

CANN (Compute Architecture for Neural Networks) constitutes Huawei’s artificial intelligence computing toolkit, designed to compile, optimize, and deploy AI models on Ascend AI processors for government and public sector applications.

This instructor-led, live training session (available online or onsite) is designed for entry-level AI developers seeking to comprehend the integration of CANN within the model lifecycle, from training through to deployment, and its interoperability with frameworks such as MindSpore, TensorFlow, and PyTorch.

Upon completion of this training, participants will possess the capability to:

• Comprehend the objectives and architectural design of the CANN toolkit.
• Establish a development environment incorporating CANN and MindSpore.
• Convert and deploy basic AI models onto Ascend hardware.
• Acquire foundational knowledge supporting future CANN optimization and integration projects.

Instructional Methodology

• Interactive lectures and facilitated discussions.
• Practical laboratory exercises involving simple model deployment.
• Detailed walkthrough of the CANN toolchain and integration points.

Customization Options for the Course

• To request a tailored training program for this course, please contact the designated office to arrange suitable provisions.

Huawei’s Ascend CANN toolkit facilitates robust AI inference capabilities on edge devices, including the Ascend 310. CANN provides critical tools for compiling, optimizing, and deploying models in environments with restricted compute and memory resources, supporting operational efficiency for government applications.

This instructor-led live training, available online or onsite, is designed for intermediate-level AI developers and integrators tasked with deploying and optimizing models on Ascend edge devices using the CANN toolchain.

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

• Prepare and convert AI models for the Ascend 310 platform using CANN tools.
• Develop lightweight inference pipelines utilizing MindSpore Lite and AscendCL.
• Optimize model performance in environments with limited compute and memory capacities.
• Deploy and monitor AI applications in practical edge scenarios relevant to public sector operations.

Course Delivery Format

• Interactive lectures accompanied by technical demonstrations.
• Hands-on laboratory exercises focused on edge-specific models and operational scenarios.
• Live deployment examples executed on virtual or physical edge hardware.

Customization Options for Course Content

• To request tailored training materials for this course, please contact our team to discuss specific requirements.

The CANN SDK (Compute Architecture for Neural Networks) serves as Huawei’s foundational AI computing platform, enabling developers to calibrate and enhance the operational efficiency of neural networks deployed on Ascend AI processors.

This instructor-led, live instruction (available online or on-site) is designed for senior AI developers and systems engineers seeking to refine inference capabilities through CANN’s advanced toolset, including the Graph Engine, TIK, and custom operator creation.

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

• Comprehend the CANN runtime structure and its performance lifecycle.
• Employ profiling instruments and the Graph Engine for performance evaluation and refinement.
• Develop and optimize proprietary operators utilizing TIK and TVM.
• Address memory constraints and augment model throughput for government applications.

Instructional Methodology

• Interactive presentations and facilitated discussions.
• Practical laboratories incorporating real-time profiling and operator calibration.
• Refinement exercises utilizing edge-case deployment scenarios for government sectors.

Instructional Adaptation Options

• To request a customized training curriculum for this module, please contact the provider for coordination.

The Compute Architecture for Neural Networks (CANN) Software Development Kit offers robust mechanisms for the deployment and optimization of real-time artificial intelligence applications in computer vision and natural language processing, particularly on Huawei Ascend infrastructure.

This instructor-led, live training course, available in online or on-site formats, is designed for intermediate-level AI practitioners seeking to build, deploy, and optimize vision and language models using the CANN SDK for production use cases for government.

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

• Deploy and optimize CV and NLP models using CANN and AscendCL.
• Leverage CANN tools to convert models and integrate them into live operational 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 for government.

Course Format

• Interactive lectures and technical demonstrations.
• Practical laboratory exercises focused on model deployment and performance profiling.
• Design of live pipelines utilizing authentic CV and NLP use cases.

Customization Options

• To request tailored training aligned with specific operational needs for government, please contact the program office to arrange.

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

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

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

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

Format of the Course

• Interactive instruction and practical demonstration.
• Hands-on coding of operators using TIK and TVM pipelines.
• Testing and tuning on Ascend hardware or simulation environments.

Course Customization Options

• To request a customized training for government, please contact us to arrange details.