Computer Graphics Training in Bangkok

This live, instructor-led training in Bangkok (online or onsite) is designed for developers with beginner to intermediate experience who wish to use OpenACC to program heterogeneous devices and maximize their parallel processing capabilities.

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

• Configure an OpenACC development environment.
• Develop and execute a fundamental OpenACC application.
• Annotate code using OpenACC directives and clauses.
• Utilize the OpenACC API and associated libraries.
• Profile, debug, and optimize OpenACC-based applications.

This instructor-led, live training conducted in Bangkok (available online or onsite) is tailored for beginner to intermediate developers looking to master the basics of GPU programming and the essential frameworks for developing GPU applications.

• By the end of this training, participants will be able to:
  Differentiate between CPU and GPU computing, recognizing the specific advantages and complexities of GPU workflows.
• Select the optimal framework and tooling for their GPU application.
• Build a basic GPU program that executes vector addition using one or more of the available frameworks.
• Utilize specific APIs, languages, and libraries to query device details, manage memory allocation, handle host-to-device data copies, launch kernels, and synchronize threads.
• Apply memory spaces such as global, local, constant, and private to enhance data transfer efficiency and memory access.
• Leverage execution models, including work-items, work-groups, threads, blocks, and grids, to control parallel execution.
• Debug and test GPU code using tools like CodeXL, CUDA-GDB, CUDA-MEMCHECK, and NVIDIA Nsight.
• Optimize GPU programs using techniques like coalescing, caching, prefetching, and profiling.

This instructor-led live training, conducted in Bangkok (online or onsite), is designed for developers from beginner to intermediate levels who intend to employ different GPU programming frameworks and assess their features, performance, and compatibility.

Upon completing this training, participants will be able to:

• Establish a development environment that includes the OpenCL SDK, CUDA Toolkit, and ROCm Platform, along with a supporting device and Visual Studio Code.
• Construct a basic GPU program for vector addition using OpenCL, CUDA, and ROCm, comparing the syntax, structure, and execution of each framework.
• Utilize the respective APIs to query device information, manage memory allocation and deallocation, transfer data between host and device, launch kernels, and synchronize threads.
• Write kernels using the respective languages to execute on the device and manipulate data.
• Employ the respective built-in functions, variables, and libraries to perform common tasks and operations.
• Utilize the respective memory spaces, including global, local, constant, and private, to optimize data transfers and memory accesses.
• Apply the respective execution models to control threads, blocks, and grids that define parallelism.
• Debug and test GPU programs using tools such as CodeXL, CUDA-GDB, CUDA-MEMCHECK, and NVIDIA Nsight.
• Optimize GPU programs using techniques like coalescing, caching, prefetching, and profiling.

This instructor-led live training in Bangkok, offered either online or onsite, caters to artists, game developers, and beginners eager to leverage Blender for creating 3D models for interactive applications, video games, and animated films.

By the conclusion of this program, participants will possess the ability to:

• Create animations and visual effects using Blender.
• Integrate curves, surfaces, metaballs, and hair particles to simulate realistic 3D movements.
• Understand the fundamentals of non-destructive modeling and animation.
• Export 3D models and assets for compatibility with game engines, 3D printers, or external software.

This instructor-led live training in Bangkok (available online or on-site) is designed for developers from beginner to intermediate levels who want to install and use ROCm on Windows to program AMD GPUs and leverage their parallelism.

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

• Establish a development environment on Windows featuring the ROCm Platform, an AMD GPU, and Visual Studio Code.
• Create a basic ROCm program that performs vector addition on the GPU and retrieves results from GPU memory.
• Use the ROCm API to query device details, manage device memory, copy data between host and device, launch kernels, and synchronize threads.
• Use the HIP language to write kernels that execute on the GPU and manipulate data.
• Employ HIP built-in functions, variables, and libraries to perform standard tasks and operations.
• Utilize ROCm and HIP memory spaces, such as global, shared, constant, and local, to optimize data transfers and memory access.
• Apply ROCm and HIP execution models to manage the threads, blocks, and grids that define parallelism.
• Debug and test ROCm and HIP programs using tools like the ROCm Debugger and ROCm Profiler.
• Optimize ROCm and HIP programs using techniques including coalescing, caching, prefetching, and profiling.

This instructor-led, live training in Bangkok (available online or onsite) is designed for beginner to intermediate developers looking to program AMD GPUs using ROCm and HIP to maximize parallel processing capabilities.

Upon completion, participants will be able to:

• Establish a development environment comprising the ROCm Platform, an AMD GPU, and Visual Studio Code.
• Build a fundamental ROCm program that performs vector addition on the GPU and extracts results from GPU memory.
• Use the ROCm API to query device details, manage memory allocation, transfer host-device data, launch kernels, and synchronize threads.
• Write GPU-executed kernels using the HIP language to manipulate data.
• Employ HIP built-in functions, variables, and libraries for standard tasks and operations.
• Leverage ROCm and HIP memory spaces, such as global, shared, constant, and local, to streamline data transfers and memory access.
• Utilize ROCm and HIP execution models to control threads, blocks, and grids that structure the parallelism.
• Debug and test ROCm and HIP applications using tools like the ROCm Debugger and ROCm Profiler.
• Optimize ROCm and HIP programs through techniques including coalescing, caching, prefetching, and profiling.

This live, instructor-guided training, delivered in Bangkok (online or onsite), caters to artists, game developers, or beginners seeking to use Blender for creating 3D models for interactive applications, video games, animated films, and more.

By the end of this program, participants will be capable of:

• Comprehending the essential principles and key concepts of 3D modeling.
• Discovering various modes and utilities for constructing and modifying 3D meshes.
• Leveraging tools for UV mapping/unwrapping, sculpting, painting, and rendering 3D models.

This live, instructor-led training in Bangkok (available online or on-site) is designed for graphic designers and animators ranging from beginner to intermediate levels who seek to master the creation of stunning animations, interactive media, and engaging web content using Adobe Animate.

Upon completing this course, participants will be equipped to:

• Confidently navigate the Adobe Animate interface and utilize its diverse toolset.
• Develop and refine animations through the use of keyframes, motion tweens, and shape tweens.
• Build interactive animations and applications by leveraging ActionScript and JavaScript.
• Integrate audio and video components seamlessly into creative projects.
• Prepare and export animations optimized for web, video, and mobile environments.

This live, instructor-led training session, conducted in Bangkok (either online or on-site), is tailored for developers from beginner to intermediate levels who wish to utilize CUDA for programming NVIDIA GPUs and leverage their parallel capabilities.

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

• Configure a development environment that includes the 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 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 CUDA C/C++ language to write kernels that execute on the GPU and manipulate data.
• Utilize CUDA built-in functions, variables, and libraries to perform common tasks and operations.
• Leverage CUDA memory spaces, such as global, shared, constant, and local, to optimize data transfers and memory accesses.
• Use the CUDA execution model to control threads, blocks, and grids that define 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.

97% client satisfaction rate.

This instructor-led, live training in Bangkok (online or onsite) is designed for artists, game developers, and complete beginners seeking to use Blender to create 3D models for interactive applications, video games, and animated films.

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.

This instructor-led live training in Bangkok (delivered online or on-site) is tailored for beginner-level system administrators and IT professionals looking to install, configure, manage, and troubleshoot CUDA environments.

By the end of the program, participants will be able to:

• Comprehend the architecture, components, and capabilities of CUDA.
• Install and configure CUDA environments efficiently.
• Manage and optimize CUDA resources effectively.
• Debug and resolve common CUDA issues.

This instructor-led live training, delivered in Bangkok (online or onsite), is designed for developers at beginner to intermediate levels who aim to utilize OpenCL for programming heterogeneous devices and maximizing their parallel capabilities.

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

• ​ ​​​​Set up a development environment featuring the OpenCL SDK, a compatible device, and Visual Studio Code.
• ​ ​​​​Develop a basic OpenCL program that performs vector addition on the device and fetches results from device memory.
• ​ ​​​​Use the OpenCL API to query device details and create contexts, command queues, buffers, kernels, and events.
• ​ ​​​​Write kernels in OpenCL C that execute on the device and manipulate data.
• ​ ​​​​Apply OpenCL built-in functions, extensions, and libraries for common tasks and operations.
• ​ ​​​​Utilize OpenCL host and device memory models to optimize data transfers and memory access.
• ​ ​​​​Control work-items, work-groups, and ND-ranges using the OpenCL execution model.
• ​ ​​​​Debug and test OpenCL programs with tools such as CodeXL, Intel VTune, and NVIDIA Nsight.
• ​ ​​​​Optimize OpenCL programs using methods like vectorization, loop unrolling, local memory, and profiling.

This instructor-led live training, available in Bangkok (online or on-site), is designed for 3D design and printing enthusiasts of all skill levels. It focuses on using Fusion 360 to design, simulate, and prepare models for 3D printing.

By the end of the session, 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 Bangkok (offered online or on-site) is tailored for C++ developers who intend to use CUDA to accelerate applications, develop high-performance GPU kernels, and apply parallel algorithm libraries to scientific computing, data processing, and machine learning workflows.

This live, instructor-led training in Bangkok (available online or onsite) is designed for C/C++ developers seeking to leverage CUDA to boost the performance of compute-intensive applications, covering areas such as data processing, scientific simulations, machine learning operations, and image processing pipelines.

This live training in Bangkok, available online or onsite, targets software developers, data analysts, and technical professionals aiming to utilize TensorFlow 2.x and Keras to build, train, and deploy deep learning models for computer vision, natural language processing, and multimodal applications.

Join this Bangkok instructor-led live session to delve into GPU programming for parallel computing. You will learn to utilize diverse platforms, harness the capabilities of the CUDA platform, and implement effective optimization strategies. The course highlights practical applications in deep learning, analytics, image processing, and engineering.