Adobe LiveCycle Designer Training Course

The Huawei Ascend series is a collection of AI processors tailored for efficient inference and training tasks.

This instructor-led live training (delivered online or at your location) targets intermediate-level AI engineers and data scientists aiming to create and refine neural network models with the Huawei Ascend platform and CANN toolkit.

Upon completion, participants will be able to:

• Establish and configure the CANN development environment.
• Create AI applications using MindSpore and CloudMatrix workflows.
• Tune performance on Ascend NPUs with custom operators and tiling techniques.
• Deploy models in both edge and cloud settings.

Course Format

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

Customization Options for the Course

• If you wish to tailor this course based on your specific infrastructure or datasets, please contact us to arrange a customized session.

CANN (Compute Architecture for Neural Networks) is Huawei’s AI compute 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 efficiently deploy trained AI models to Huawei Ascend hardware using the CANN toolkit, along with tools such as MindSpore, TensorFlow, or PyTorch.

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

• Gain a comprehensive understanding of the CANN architecture and its significance in the AI deployment pipeline.
• Convert and adapt models from popular frameworks into formats compatible with Ascend processors.
• Utilize tools like ATC, OM model conversion, and MindSpore for inference at the edge and in the cloud.
• Identify and resolve deployment issues while optimizing performance on Ascend hardware.

Format of the Course

• Interactive lectures and demonstrations.
• Hands-on lab sessions 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.

CloudMatrix is Huawei’s comprehensive AI development and deployment platform tailored to support scalable, production-ready inference pipelines.

This instructor-led live training (online or in-person) targets beginner to intermediate-level AI professionals aiming to deploy and monitor AI models using the CloudMatrix platform, integrated with CANN and MindSpore.

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

• Utilize CloudMatrix for model packaging, deployment, and serving.
• Convert and optimize models for Ascend chipsets.
• Establish pipelines for real-time and batch inference tasks.
• Monitor deployments and fine-tune performance in production environments.

Course Format

• Interactive lecture and discussion sessions.
• Hands-on experience with CloudMatrix using practical deployment scenarios.
• Guided exercises focused on conversion, optimization, and scaling techniques.

Customization Options for the Course

• To request a customized training based on your AI infrastructure or cloud environment, please contact us to arrange.

Biren AI Accelerators are advanced GPUs tailored for artificial intelligence and high-performance computing tasks, supporting extensive training and inference processes.

This instructor-led live training (online or at your site) is targeted at intermediate to advanced developers looking to develop and fine-tune applications using Biren’s proprietary GPU technology. Practical comparisons will be made with CUDA-based environments.

By the conclusion of this course, attendees will be able to:

• Grasp the architecture and memory structure of Biren GPUs.
• Configure the development environment and utilize Biren’s programming framework.
• Convert and enhance CUDA-style code for use with Biren platforms.
• Implement performance optimization and debugging strategies.

Course Format

• Engaging lectures and discussions.
• Practical application of the Biren SDK in sample GPU tasks.
• Guided exercises centered on porting and optimizing performance.

Customization Options for the Course

• To request a customized training session based on your specific application stack or integration requirements, please contact us to arrange.

Cambricon MLUs (Machine Learning Units) are specialized AI chips designed to enhance performance in both inference and training tasks within edge computing and data center environments.

This instructor-led live training session (conducted either online or at your location) is tailored for intermediate developers looking to create and deploy AI models using the BANGPy framework alongside Neuware SDK on Cambricon MLU hardware.

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

• Establish and configure development environments for BANGPy and Neuware.
• Create and refine Python- and C++-based models specifically for Cambricon MLUs.
• Deploy these models onto edge devices and data centers that utilize Neuware runtime.
• Incorporate ML workflows with features optimized for MLU acceleration.

Course Format

• Engaging lectures combined with interactive discussions.
• Practical hands-on experience using BANGPy and Neuware for both development and deployment tasks.
• Guided exercises centered on optimization, integration, and testing processes.

Customization Options

• If you require a customized training session based on your specific Cambricon device model or use case, please reach out to us for further arrangements.

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

This instructor-led, live training, available either online or on-site, is tailored for beginner-level AI developers seeking to understand how CANN integrates into the model lifecycle from training through deployment, as well as how it collaborates with frameworks such as MindSpore, TensorFlow, and PyTorch.

Upon completing this training, participants will be equipped to:

• Grasp the core purpose and architectural design of the CANN toolkit.
• Establish a development environment utilizing CANN and MindSpore.
• Convert and successfully deploy a basic AI model onto Ascend hardware.
• Acquire the foundational knowledge necessary for future CANN optimization or integration initiatives.

Course Format

• Interactive lectures complemented by group discussions.
• Practical laboratories focused on straightforward model deployment.
• A step-by-step walkthrough of the CANN toolchain and its key integration points.

Customization Options

• To arrange a customized training session for this course, please contact us to discuss your specific requirements.

Huawei's Ascend CANN toolkit empowers robust AI inference on edge devices like the Ascend 310, offering indispensable utilities for compiling, optimizing, and deploying models within environments where computational power and memory are limited.

Designed for intermediate-level AI developers and integrators, this instructor-led live training—available either online or on-site—focuses on leveraging the CANN toolchain to successfully deploy and refine models on Ascend edge hardware.

Upon completing this training, participants will be equipped to:

• Prepare and convert AI models for the Ascend 310 platform utilizing CANN utilities.
• Construct streamlined inference pipelines employing MindSpore Lite and AscendCL.
• Enhance model efficiency to suit constraints in compute and memory availability.
• Deploy and oversee AI applications within practical, real-world edge scenarios.

Course Format

• Engaging lectures complemented by live demonstrations.
• Practical laboratory exercises focused on edge-specific models and use cases.
• Real-time deployment examples executed on virtual or physical edge hardware.

Customization Options

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

Huawei's AI ecosystem, spanning from the foundational CANN SDK to the high-level MindSpore framework, delivers a seamlessly integrated environment for AI development and deployment, specifically optimized for Ascend hardware.

This live, instructor-led training, available both online and on-site, is designed for technical professionals ranging from beginner to intermediate levels who seek to grasp how CANN and MindSpore components collaborate to streamline AI lifecycle management and inform infrastructure strategy.

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

• Comprehend the layered architecture underpinning Huawei's AI compute stack.
• Recognize the role of CANN in enabling model optimization and hardware-level deployment.
• Assess the MindSpore framework and its toolchain against industry alternatives.
• Strategically position Huawei's AI stack within enterprise, cloud, or on-premises environments.

Course Format

• Interactive lectures followed by open discussion.
• Real-time system demonstrations and scenario-based walkthroughs.
• Optional guided labs exploring the model workflow from MindSpore to CANN.

Customization Options

• To request a tailored version of this course, please contact us to make arrangements.

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

This instructor-led live training, available either online or on-site, is designed for advanced AI developers and system engineers seeking to optimize inference performance. Participants will leverage CANN's sophisticated toolset, including the Graph Engine, TIK, and capabilities for custom operator development.

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

• Comprehend CANN's runtime architecture and its performance lifecycle.
• Utilize profiling tools and the Graph Engine for in-depth performance analysis and optimization.
• Develop and refine custom operators using TIK and TVM.
• Address memory bottlenecks and enhance overall model throughput.

Course Format

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

Course Customization Options

• To request a tailored version of this training, please contact us to make arrangements.

The CANN SDK (Compute Architecture for Neural Networks) delivers robust deployment and optimization capabilities for real-time AI applications in computer vision and NLP, with particular strength on Huawei Ascend hardware.

This instructor-led, live training (available online or on-site) is designed for intermediate-level AI professionals seeking to build, deploy, and optimize vision and language models using the CANN SDK for production environments.

Upon completing this training, participants will be able to:

• Deploy and refine CV and NLP models using CANN and AscendCL.
• Leverage CANN utilities to convert models and seamlessly integrate them into live processing pipelines.
• Enhance inference performance for critical tasks such as object detection, classification, and sentiment analysis.
• Construct real-time CV and NLP pipelines tailored for edge or cloud-based deployment scenarios.

Course Format

• Engaging lectures complemented by live demonstrations.
• Practical laboratory sessions focused on model deployment and performance profiling.
• Live pipeline design exercises using authentic computer vision and NLP use cases.

Customization Options

• To arrange a customized version of this training, please contact us to discuss your specific requirements.

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

This instructor-led, live training (available online or on-site) is designed for senior system developers seeking to build, deploy, and fine-tune custom operators for AI models by leveraging CANN's TIK programming model and its integration with the TVM compiler.

Upon completing this training, participants will be equipped to:

• Develop and validate custom AI operators using the TIK DSL tailored for Ascend processors.
• Seamlessly integrate custom operations into the CANN runtime and execution graph.
• Leverage TVM for operator scheduling, automatic tuning, and performance benchmarking.
• Debug and refine instruction-level performance for bespoke computational patterns.

Course Format

• Engaging lectures paired with live demonstrations.
• Practical coding sessions focused on building operators using TIK and TVM pipelines.
• Rigorous testing and performance tuning on Ascend hardware or dedicated simulators.

Customization Options

• To arrange a tailored version of this training, please contact us for further discussion.

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

This instructor-led training (online or at your location) is targeted at advanced 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 course, participants will be able to:

• Determine the compatibility of current CUDA workloads with Chinese chip alternatives.
• Migrate CUDA codebases to environments such as Huawei CANN, Biren SDK, and Cambricon BANGPy.
• Analyze performance differences and pinpoint optimization opportunities across various platforms.
• Overcome practical challenges in cross-architecture support and deployment.

Course Format

• Interactive lectures and discussions.
• Hands-on labs for code translation and performance comparison.
• Guided exercises focusing on multi-GPU adaptation strategies.

Customization Options

• To request a customized training based on your platform or CUDA project, please contact us to arrange the details.

The leading AI hardware platforms in China—Ascend, Biren, and Cambricon—provide distinctive acceleration and profiling tools tailored for large-scale AI workloads.

This instructor-led training session (conducted either online or on-site) is designed for advanced-level engineers specializing in AI infrastructure and performance. The goal is to enhance their ability to optimize model inference and training processes across various Chinese AI chip platforms.

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

• Evaluate models using the Ascend, Biren, and Cambricon platforms.
• Detect system limitations and inefficiencies in memory and compute resources.
• Implement optimizations at the graph level, kernel level, and operator level.
• Refine deployment pipelines to boost throughput and reduce latency.

Course Format

• An interactive lecture combined with discussions.
• Practical use of profiling and optimization tools on each platform.
• Guided exercises centered around real-world tuning scenarios.

Customization Options for the Course

• If you require a customized training session based on your specific performance environment or model type, please contact us to arrange this.