Computer Graphics Training in Ho Chi Minh City

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.

Huawei’s AI stack — spanning from the low-level CANN SDK to the high-level MindSpore framework — provides a tightly integrated environment for developing and deploying AI solutions, specifically optimized for Ascend hardware.

This instructor-led, live training (available online or onsite) targets technical professionals at beginner to intermediate levels who want to comprehend how CANN and MindSpore components collaborate to support AI lifecycle management and infrastructure decision-making.

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

• Comprehend the layered architecture of Huawei’s AI compute stack.
• Recognize how CANN facilitates model optimization and hardware-level deployment.
• Assess the MindSpore framework and its toolchain in comparison to industry alternatives.
• Contextualize Huawei's AI stack within enterprise or cloud/on-premises environments.

Course Format

• Interactive lectures and discussions.
• Live system demonstrations and case-based walkthroughs.
• Optional guided labs covering the model flow from MindSpore to CANN.

Course Customization Options

• For requests regarding customized training for this course, please contact us to make arrangements.

This instructor-led live training (online or onsite) is designed for beginner to intermediate developers who intend to use OpenACC to program heterogeneous devices and harness their parallelism.

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

• Set up an OpenACC development environment.
• Write and run a basic OpenACC program.
• Annotate code with OpenACC directives and clauses.
• Use OpenACC API and libraries.
• Profile, debug, and optimize OpenACC programs.

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.

This instructor-led, live training in Ho Chi Minh City (online or onsite) is aimed at beginner-level to intermediate-level developers who wish to learn the basics of GPU programming and the main frameworks and tools for developing GPU applications.

• By the end of this training, participants will be able to:
  Understand the difference between CPU and GPU computing and the benefits and challenges of GPU programming.
• Choose the right framework and tool for their GPU application.
• Create a basic GPU program that performs vector addition using one or more of the frameworks and tools.
• Use the respective APIs, languages, and libraries to query device information, allocate and deallocate device memory, copy data between host and device, launch kernels, and synchronize threads.
• Use the respective memory spaces, such as global, local, constant, and private, to optimize data transfers and memory accesses.
• Use the respective execution models, such as work-items, work-groups, threads, blocks, and grids, to control the parallelism.
• Debug and test GPU programs using tools such as CodeXL, CUDA-GDB, CUDA-MEMCHECK, and NVIDIA Nsight.
• Optimize GPU programs using techniques such as coalescing, caching, prefetching, and profiling.

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.

This instructor-led live training held in Ho Chi Minh City (online or onsite) is designed for beginner to intermediate developers who want to utilize various frameworks for GPU programming and compare their features, performance, and compatibility.

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

• Establish a development environment featuring the OpenCL SDK, CUDA Toolkit, ROCm Platform, compatible hardware (supporting OpenCL, CUDA, or ROCm), and Visual Studio Code.
• Developing fundamental GPU programs that execute vector addition using OpenCL, CUDA, and ROCm, thereby comparing the syntax, structure, and execution models of each framework.
• Utilizing respective APIs to retrieve device information, manage device memory allocation and deallocation, transfer data between host and device, initiate kernels, and synchronize threads.
• Employing specific languages to write kernels that run on the device and process data.
• Leveraging built-in functions, variables, and libraries within each framework to execute common tasks and operations.
• Optimizing data transfers and memory access by utilizing distinct memory spaces such as global, local, constant, and private.
• Controlling parallelism through the management of threads, blocks, and grids using respective execution models.
• Debugging and testing GPU applications using tools like CodeXL, CUDA-GDB, CUDA-MEMCHECK, and NVIDIA Nsight.
• Enhancing GPU program performance through techniques including coalescing, caching, prefetching, and profiling.

CloudMatrix is Huawei's comprehensive AI development and deployment platform engineered to facilitate scalable, production-ready inference pipelines.

This instructor-led live training, available online or onsite, targets beginner to intermediate-level AI professionals aiming to deploy and oversee AI models using the CloudMatrix platform integrated with CANN and MindSpore.

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

• Utilizing CloudMatrix for model packaging, deployment, and serving.
• Converting and optimizing models specifically for Ascend chipsets.
• Configuring pipelines for both real-time and batch inference tasks.
• Monitoring deployments and fine-tuning performance within production environments.

Course Format

• Interactive lectures and discussions.
• Practical application of CloudMatrix through real-world deployment scenarios.
• Guided exercises focusing on conversion, optimization, and scaling techniques.

Customization Options for the Course

• To request customized training tailored to your specific AI infrastructure or cloud environment, please contact us for arrangements.

This instructor-led live training in Ho Chi Minh City (available online or onsite) is designed for artists, game developers, or complete beginners who wish to utilize Blender to create 3D models for interactive applications, video games, animated films, and more.

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

• Learn how to produce animations and visual effects with Blender.
• Incorporate curves, surfaces, metaballs, and hair particles to simulate realistic 3D movements.
• Understand the basics of non-destructive modeling and animation.
• Export 3D models and assets to game engines, 3D printers, or other software.

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.

This instructor-led live training session Ho Chi Minh City (online or onsite) is designed for beginner to intermediate-level developers who want to install and use ROCm on Windows to program AMD GPUs and exploit their parallel capabilities.

Upon completing this training, participants will be equipped to:

• Establish a development environment comprising the ROCm Platform, an AMD GPU, and Visual Studio Code on Windows.
• Develop a fundamental ROCm application that executes vector addition on the GPU and retrieves results from GPU memory.
• Utilize the ROCm API to query device details, manage device memory allocation and deallocation, transfer data between host and device, launch kernels, and synchronize threads.
• Employ the HIP language to write kernels that run on the GPU and manipulate data.
• Leverage HIP built-in functions, variables, and libraries to carry out common tasks and operations.
• Optimize data transfers and memory access by utilizing ROCm and HIP memory spaces, including global, shared, constant, and local regions.
• Control threads, blocks, and grids that define parallelism through ROCm and HIP execution models.
• Debug and test ROCm and HIP applications using tools like ROCm Debugger and ROCm Profiler.
• Enhance ROCm and HIP programs using optimization techniques such as coalescing, caching, prefetching, and profiling.

This instructor-led, live training in Ho Chi Minh City (online or onsite) is aimed at beginner to intermediate-level developers who wish to use ROCm and HIP to program AMD GPUs and exploit their parallelism.

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

• Set up a development environment that includes ROCm Platform, an AMD GPU, and Visual Studio Code.
• Create a basic ROCm program that performs vector addition on the GPU and retrieves the results from the GPU memory.
• Use ROCm API to query device information, allocate and deallocate device memory, copy data between host and device, launch kernels, and synchronize threads.
• Use HIP language to write kernels that execute on the GPU and manipulate data.
• Use HIP built-in functions, variables, and libraries to perform common tasks and operations.
• Use ROCm and HIP memory spaces, such as global, shared, constant, and local, to optimize data transfers and memory accesses.
• Use ROCm and HIP execution models to control the threads, blocks, and grids that define the parallelism.
• Debug and test ROCm and HIP programs using tools such as ROCm Debugger and ROCm Profiler.
• Optimize ROCm and HIP programs using techniques such as coalescing, caching, prefetching, and profiling.

This instructor-led live training in Ho Chi Minh City (online or on-site) is designed for artists, game developers, and complete beginners who wish to use Blender to create 3D models for interactive applications, video games, animated films, and other media.

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

• Understand the principles and core concepts of 3D modeling.
• Explore a variety of modes and tools for modeling and editing 3D meshes.
• Use the tools for UV mapping/unwrapping, sculpting, and painting 3D models rendering.

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.

Ascend, Biren, and Cambricon stand out as premier AI hardware platforms in China, each providing distinct acceleration and profiling capabilities designed for large-scale AI workloads in production environments.

This instructor-led training session, available either online or onsite, targets advanced AI infrastructure and performance engineers looking to enhance model inference and training workflows across various Chinese AI chip architectures.

Upon completing this course, participants will gain the ability to:

• Evaluate model performance on Ascend, Biren, and Cambricon systems.
• Diagnose system bottlenecks and identify inefficiencies in memory or compute resources.
• Implement optimizations at the graph, kernel, and operator levels.
• Configure deployment pipelines to maximize throughput and minimize latency.

Course Format

• Engaging lectures combined with interactive discussions.
• Practical application of profiling and optimization tools across different platforms.
• Structured exercises centered on real-world tuning scenarios.

Customization Options

• If you require a tailored training program aligned with your specific performance environment or model type, please contact us to make arrangements.

This instructor-led, live training in Ho Chi Minh City (online or on-site) is intended for graphic designers and animators at beginner to intermediate levels who wish to learn how to produce impressive animations, interactive media, and engaging web content using Adobe Animate.

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

• Navigate the Adobe Animate interface and tools.
• Create and edit animations using keyframes, motion tweens, and shape tweens.
• Design interactive animations and applications with ActionScript and JavaScript.
• Incorporate audio and video elements into projects.
• Export animations for web, video, and mobile platforms.

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.

Chinese GPU architectures, including Huawei Ascend, Biren, and Cambricon MLUs, provide CUDA alternatives specifically designed for local AI and high-performance computing (HPC) markets.

This instructor-led live training, available online or onsite, targets advanced-level GPU programmers and infrastructure specialists looking to migrate and optimize existing CUDA applications for deployment on Chinese hardware platforms.

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

• Evaluate the compatibility of existing CUDA workloads with alternative Chinese chipsets.
• Port CUDA codebases into Huawei CANN, Biren SDK, and Cambricon BANGPy environments.
• Compare performance metrics and identify optimization opportunities across different platforms.
• Address practical challenges related to 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 customized training based on your specific platform or CUDA project, please contact us to arrange a session.

This instructor-led, live training in Ho Chi Minh City (online or onsite) is aimed at beginner-level to intermediate-level developers who wish to use CUDA to program NVIDIA GPUs and exploit their parallelism.

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

• Set up a development environment that includes CUDA Toolkit, an NVIDIA GPU, and Visual Studio Code.
• Create a basic CUDA program that performs vector addition on the GPU and retrieves the results from the GPU memory.
• Use the CUDA API to query device information, allocate and deallocate device memory, copy data between host and device, launch kernels, and synchronize threads.
• Use the CUDA C/C++ language to write kernels that execute on the GPU and manipulate data.
• Use CUDA built-in functions, variables, and libraries to perform common tasks and operations.
• Use CUDA memory spaces, such as global, shared, constant, and local, to optimize data transfers and memory accesses.
• Use the CUDA execution model to control the threads, blocks, and grids that define the parallelism.
• Debug and test CUDA programs using tools such as CUDA-GDB, CUDA-MEMCHECK, and NVIDIA Nsight.
• Optimize CUDA programs using techniques such as coalescing, caching, prefetching, and profiling.

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Psdto3D101 is a specialized software tool designed for creating lenticular files with 3D effects, flip, morph, and motion designs. This course provides participants with the knowledge and practical skills to manage and apply Psdto3D101 for producing professional lenticular outputs, covering both management and creative aspects of the software.

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level graphic and print professionals who wish to create, manage, and optimize lenticular files using Psdto3D101 software.

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

• Understand the fundamentals of lenticular printing and design.
• Navigate and configure Psdto3D101 for different project types.
• Create 3D, flip, and motion effects using layers and sequences.
• Export and prepare lenticular files for professional printing.

Format of the Course

• Interactive lecture and discussion.
• Practical exercises using Psdto3D101 software.
• Hands-on implementation in a live-lab environment.

Course Customization Options

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

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.

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:

• Grasp the architecture and memory hierarchy of Biren GPUs.
• Configure the development environment and utilize Biren’s programming model.
• Translate and optimize CUDA-style code for Biren platforms.
• Implement 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.

This instructor-led live training in Ho Chi Minh City (online or onsite) is aimed at artists, game developers, or complete beginners who wish to use Blender to create 3D models for interactive applications, video games, animated films, etc.

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

• Understand the principles and core concepts of 3D modeling.
• Explore a variety of modes and tools for modeling and editing 3D meshes.
• Learn how to create animations and visual effects with Blender.
• Add curves, surfaces, metaballs, and hair particles to simulate realistic 3D motions.
• Use the tools for UV mapping/unwrapping, sculpting, and painting 3D models.
• Export 3D models and assets to a game engine, 3D printer, or other software. 

Cambricon MLUs (Machine Learning Units) are specialized AI chips designed for high-performance inference and training in both edge computing and data center environments.

This instructor-led, live training session (available online or onsite) is tailored for intermediate-level developers looking to build and deploy AI models using the BANGPy framework and Neuware SDK on Cambricon MLU hardware.

Upon completing this training, participants will be able to:

• Set up and configure development environments for BANGPy and Neuware.
• Develop and optimize models written in Python and C++ for Cambricon MLUs.
• Deploy models to edge devices and data centers running the Neuware runtime.
• Integrate machine learning workflows with specific MLU acceleration features.

Course Format

• Interactive lectures and discussions.
• Hands-on exercises using BANGPy and Neuware for development and deployment.
• Guided practice focusing on optimization, integration, and testing.

Customization Options

• To request a customized version of this course tailored to your specific Cambricon device model or use case, please contact us to arrange.

This instructor-led, live training in Ho Chi Minh City (online or onsite) is designed for beginner-level system administrators and IT professionals who want to install, configure, manage, and troubleshoot CUDA environments.

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

• Understand the architecture, components, and capabilities of CUDA.
• Install and set up CUDA environments.
• Manage and optimize CUDA resources.
• Debug and resolve common CUDA issues.

This instructor-led live training in Ho Chi Minh City (online or onsite) is designed for beginner to intermediate developers who wish to utilize OpenCL to program heterogeneous devices and exploit their parallelism.

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

• Set up a development environment that includes OpenCL SDK, a device that supports OpenCL, and Visual Studio Code.
• Create a basic OpenCL program that performs vector addition on the device and retrieves the results from the device memory.
• Use OpenCL API to query device information, create contexts, command queues, buffers, kernels, and events.
• Use OpenCL C language to write kernels that execute on the device and manipulate data.
• Use OpenCL built-in functions, extensions, and libraries to perform common tasks and operations.
• Use OpenCL host and device memory models to optimize data transfers and memory accesses.
• Use OpenCL execution model to control the work-items, work-groups, and ND-ranges.
• Debug and test OpenCL programs using tools such as CodeXL, Intel VTune, and NVIDIA Nsight.
• Optimize OpenCL programs using techniques such as vectorization, loop unrolling, local memory, and profiling.

This instructor-led, live training in Ho Chi Minh City (online or onsite) is aimed at beginner-level to advanced-level 3D design and 3D printing enthusiasts who wish to use Fusion 360 to design, simulate, and prepare models for 3D printing.

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

• Install and configure Fusion 360 for optimal performance.
• Design, model, and simulate 3D objects in a unified environment.
• Optimize and prepare designs for the 3D printing process.
• Collaborate and share their designs using Fusion 360's cloud capabilities.

This instructor-led, live training in Ho Chi Minh City (online or onsite) is aimed at C++ developers who wish to use CUDA to accelerate applications, write high-performance GPU kernels, and leverage parallel algorithm libraries for scientific computing, data processing, and machine learning workloads.

This instructor-led live training in Ho Chi Minh City (online or onsite) is designed for C/C++ developers who want to use CUDA to accelerate compute-intensive applications, such as data processing, scientific simulations, machine learning workloads, and image processing pipelines.

This instructor-led, live training in Ho Chi Minh City (online or onsite) is aimed at software developers, data analysts, and technical professionals who wish to use TensorFlow 2.x and Keras to build, train, and deploy deep learning models for computer vision, natural language processing, and multimodal applications.

FreeCAD is a customizable, multi-platform, scriptable, and extensible open-source parametric 3D modeler designed for creating real-world objects.

In this instructor-led live training, participants will learn how to create models intended for future construction or 3D printing.

Upon completing this training, participants will be able to:

• Utilize FreeCAD's tools and workflows as an alternative to commercial CAD or BIM modeling software
• Export designs to various formats including STEP, IGES, STL, SVG, DXF, OBJ, IFC, DAE, and others
• Leverage Python to expand FreeCAD's capabilities
• Automate FreeCAD, develop modules, and embed FreeCAD into existing applications

Audience

• Designers
• Developers
• Mechanical engineers

Course Format

• A blend of lectures, discussions, exercises, and extensive hands-on practice

This instructor-led, live training course in Ho Chi Minh City explores how to program GPUs for parallel computing, utilize diverse platforms, work with the CUDA platform and its features, and apply various optimization techniques using CUDA. Key application areas include deep learning, analytics, image processing, and engineering solutions.