Curso de Adobe LiveCycle Designer

Huawei Ascend é uma família de processadores de IA projetados para inferência e treinamento de alta performance.

Esta formação ao vivo (online ou presencial), conduzida por um instrutor, destina-se a engenheiros de IA intermediários e cientistas de dados que desejam desenvolver e otimizar modelos de redes neurais usando a plataforma Ascend da Huawei e o toolkit CANN.

No final desta formação, os participantes serão capazes de:

• Configurar e configurar o ambiente de desenvolvimento do CANN.
• Desenvolver aplicações de IA utilizando MindSpore e fluxos de trabalho CloudMatrix.
• Otimizar desempenho em NPUs Ascend usando operadores personalizados e tiling.
• Implantar modelos em ambientes de borda ou nuvem.

Formato do Curso

• Aula interativa e discussão.
• Uso prático dos processadores Huawei Ascend e toolkit CANN em aplicações de exemplo.
• Exercícios guiados focados na construção, treinamento e implantação do modelo.

Opções de Personalização do Curso

• Para solicitar uma formação personalizada para este curso com base em sua infraestrutura ou conjuntos de dados, entre em contato conosco para agendar.

CANN (Compute Architecture for Neural Networks) is Huawei’s AI compute stack for deploying and optimizing AI models on Ascend AI processors.

This instructor-led, live training (online or onsite) is aimed at intermediate-level AI developers and engineers who wish to deploy trained AI models efficiently to Huawei Ascend hardware using the CANN toolkit and tools such as MindSpore, TensorFlow, or PyTorch.

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

• Understand the CANN architecture and its role in the AI deployment pipeline.
• Convert and adapt models from popular frameworks to Ascend-compatible formats.
• Use tools like ATC, OM model conversion, and MindSpore for edge and cloud inference.
• Diagnose deployment issues and optimize performance on Ascend hardware.

Format of the Course

• Interactive lecture and demonstration.
• Hands-on lab work 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.

Biren AI Accelerators are high-performance GPUs designed for AI and HPC workloads with support for large-scale training and inference.

This instructor-led, live training (online or onsite) is aimed at intermediate-level to advanced-level developers who wish to program and optimize applications using Biren’s proprietary GPU stack, with practical comparisons to CUDA-based environments.

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

• Understand Biren GPU architecture and memory hierarchy.
• Set up the development environment and use Biren’s programming model.
• Translate and optimize CUDA-style code for Biren platforms.
• Apply performance tuning and debugging techniques.

Format of the Course

• Interactive lecture and discussion.
• Hands-on use of Biren SDK in sample GPU workloads.
• Guided exercises focused on porting and performance tuning.

Course Customization Options

• To request a customized training for this course based on your application stack or integration needs, please contact us to arrange.

As unidades MLU da Cambricon (Machine Learning) são chips especializados de IA otimizados para inferência e treinamento em cenários de borda e datacenter.

Este treinamento ao vivo, conduzido por um instrutor (online ou presencial), é direcionado a desenvolvedores intermediários que desejam construir e implantar modelos de IA usando o framework BANGPy e o SDK Neuware na hardware MLU da Cambricon.

No final deste treinamento, os participantes serão capazes de:

• Configurar e configurar os ambientes de desenvolvimento do BANGPy e Neuware.
• Desenvolver e otimizar modelos baseados em Python e C++ para as unidades MLU da Cambricon.
• Implantar modelos em dispositivos de borda e data center que executam o tempo de execução Neuware.
• Integrar fluxos de trabalho de ML com recursos de aceleração específicos do MLU.

Formato do Curso

• Aula interativa e discussão.
• Uso prático do BANGPy e Neuware para desenvolvimento e implantação.
• Exercícios guiados focados em otimização, integração e teste.

Opções de Personalização do Curso

• Para solicitar um treinamento personalizado baseado no modelo do dispositivo Cambricon ou caso de uso específico, entre em contato conosco para agendar.

CANN (Compute Architecture for Neural Networks) is Huawei’s AI computing toolkit used to compile, optimize, and deploy AI models on Ascend AI processors.

This instructor-led, live training (online or onsite) is aimed at beginner-level AI developers who wish to understand how CANN fits into the model lifecycle from training to deployment, and how it works with frameworks like MindSpore, TensorFlow, and PyTorch.

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

• Understand the purpose and architecture of the CANN toolkit.
• Set up a development environment with CANN and MindSpore.
• Convert and deploy a simple AI model to Ascend hardware.
• Gain foundational knowledge for future CANN optimization or integration projects.

Format of the Course

• Interactive lecture and discussion.
• Hands-on labs with simple model deployment.
• Step-by-step walkthrough of the CANN toolchain and integration points.

Course Customization Options

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

Huawei's Ascend CANN toolkit enables powerful AI inference on edge devices such as the Ascend 310. CANN provides essential tools for compiling, optimizing, and deploying models where compute and memory are constrained.

This instructor-led, live training (online or onsite) is aimed at intermediate-level AI developers and integrators who wish 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 Ascend 310 using CANN tools.
• Build lightweight inference pipelines using MindSpore Lite and AscendCL.
• Optimize model performance for limited compute and memory environments.
• Deploy and monitor AI applications in real-world edge use cases.

Format of the Course

• Interactive lecture and demonstration.
• Hands-on lab work with 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.

Huawei’s AI stack — from the low-level CANN SDK to the high-level MindSpore framework — offers a tightly integrated AI development and deployment environment optimized for Ascend hardware.

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level technical professionals who wish to understand how the CANN and MindSpore components work together to support AI lifecycle management and infrastructure decisions.

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

• Understand the layered architecture of Huawei’s AI compute stack.
• Identify how CANN supports model optimization and hardware-level deployment.
• Evaluate the MindSpore framework and toolchain in relation to industry alternatives.
• Position Huawei's AI stack within enterprise or cloud/on-prem environments.

Format of the Course

• Interactive lecture and discussion.
• Live system demos and case-based walkthroughs.
• Optional guided labs on model flow from MindSpore to CANN.

Course Customization Options

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

CANN SDK (Compute Architecture for Neural Networks) is Huawei’s AI compute foundation that allows developers to fine-tune and optimize the performance of deployed neural networks on Ascend AI processors.

This instructor-led, live training (online or onsite) is aimed at advanced-level AI developers and system engineers who wish to optimize inference performance using CANN’s advanced toolset, including the Graph Engine, TIK, and custom operator development.

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

• Understand CANN's runtime architecture and performance lifecycle.
• Use profiling tools and Graph Engine for performance analysis and optimization.
• Create and optimize custom operators using TIK and TVM.
• Resolve memory bottlenecks and improve model throughput.

Format of the Course

• Interactive lecture and discussion.
• Hands-on labs with real-time profiling and operator tuning.
• Optimization exercises using edge-case deployment examples.

Course Customization Options

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

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

This instructor-led, live training (online or onsite) is aimed at intermediate-level AI practitioners who wish to build, deploy, and optimize vision and language models using the CANN SDK for production use cases.

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

• Deploy and optimize CV and NLP models using CANN and AscendCL.
• Use CANN tools to convert models and integrate them into live pipelines.
• Optimize inference performance for tasks like detection, classification, and sentiment analysis.
• Build real-time CV/NLP pipelines for edge or cloud-based deployment scenarios.

Format of the Course

• Interactive lecture and demonstration.
• Hands-on lab with model deployment and performance profiling.
• Live pipeline design using real CV and NLP use cases.

Course Customization Options

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

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

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

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

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

Format of the Course

• Interactive lecture and demonstration.
• Hands-on coding of operators using TIK and TVM pipelines.
• Testing and tuning on Ascend hardware or simulators.

Course Customization Options

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

Arquiteturas chinesas GPU como Huawei Ascend, Biren e Cambricon MLUs oferecem alternativas ao CUDA, adaptadas para os mercados de IA e HPC locais.

Esta formação presencial ou online, ministrada por instrutores, destina-se a programadores avançados GPU e especialistas em infraestrutura que desejam migrar e otimizar aplicativos CUDA existentes para plataformas de hardware chinesas.

Ao final deste treinamento, os participantes serão capazes de:

• Avaliar a compatibilidade dos trabalhos do CUDA existente com as alternativas de chips chineses.
• Portar bases de código CUDA para ambientes Huawei CANN, Biren SDK e Cambricon BANGPy.
• Comparar o desempenho e identificar pontos de otimização em diferentes plataformas.
• Enfrentar desafios práticos no suporte a arquiteturas cruzadas e na implantação.

Formato do Curso

• Aula interativa e discussão.
• Laboratórios de tradução prática de código e comparação de desempenho.
• Exercícios guiados focados em estratégias de adaptação multi-GPU.

Opções de Personalização do Curso

• Para solicitar uma formação personalizada baseada no seu plataforma ou projeto CUDA, entre em contato conosco para agendar.

Ascend, Biren e Cambricon são plataformas de hardware de IA líderes na China, cada uma oferecendo ferramentas únicas de aceleração e perfilamento para cargas de trabalho de IA em escala de produção.

Esta formação ao vivo (online ou presencial), ministrada por um instrutor, é direcionada a engenheiros avançados de infraestrutura e desempenho de IA que desejam otimizar fluxos de trabalho de inferência e treinamento de modelos em múltiplas plataformas de chips de IA chineses.

No final desta formação, os participantes serão capazes de:

• Benchmarkear modelos nas plataformas Ascend, Biren e Cambricon.
• Identificar gargalos do sistema e ineficiências de memória/cálculo.
• Aplique otimizações em nível de gráfico, núcleo e operador.
• Ajustar pipelines de implantação para melhorar a taxa de transferência e a latência.

Formato do Curso

• Aula interativa e discussão.
• Uso prático das ferramentas de perfilamento e otimização em cada plataforma.
• Exercícios guiados focados em cenários práticos de ajuste.

Opções de Customização do Curso

• Para solicitar uma formação personalizada com base no seu ambiente de desempenho ou tipo de modelo, entre em contato conosco para agendar.