Computer Graphics Training in BRICS Corporate Offsite Training Venues

This instructor-led, live training in BRICS Corporate Offsite Training Venues (online or onsite) targets beginner to intermediate developers who wish to utilize OpenACC to program heterogeneous devices and exploit 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.

This instructor-led live training in BRICS Corporate Offsite Training Venues (online or onsite) targets beginner to intermediate developers keen on learning the fundamentals of GPU programming and the key frameworks and tools for developing GPU applications.

• Upon completing this training, participants will be able to:
  Understand the differences between CPU and GPU computing, including 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.

This instructor-led, live training in BRICS Corporate Offsite Training Venues (online or onsite) targets beginner to intermediate developers who want to utilise diverse frameworks for GPU programming and compare their features, performance, and compatibility.

Upon completing this training, participants will be able to:

• Set up a development environment featuring the OpenCL SDK, CUDA Toolkit, ROCm Platform, a device supporting OpenCL, CUDA, or ROCm, and Visual Studio Code.
• Develop a basic GPU program performing vector addition using OpenCL, CUDA, and ROCm, and compare the syntax, structure, and execution of each framework.
• Employ the respective APIs to query device information, allocate and deallocate device memory, copy data between host and device, launch kernels, and synchronize threads.
• Utilise the respective languages to write kernels that execute on the device and manipulate data.
• Use the respective built-in functions, variables, and libraries to carry out common tasks and operations.
• Leverage the respective memory spaces, such as global, local, constant, and private, to optimise data transfers and memory accesses.
• Apply the respective execution models to manage the threads, blocks, and grids that define parallelism.
• Debug and test GPU programs using tools like CodeXL, CUDA-GDB, CUDA-MEMCHECK, and NVIDIA Nsight.
• Optimise GPU programs employing techniques such as coalescing, caching, prefetching, and profiling.

This instructor-led live training in BRICS Corporate Offsite Training Venues (online or on-site) is designed for artists, game developers, and complete beginners who wish to utilise Blender to create 3D models for interactive applications, video games, animated films, and more.

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

• Learn how to create animations and visual effects using Blender.
• Add curves, surfaces, metaballs, and hair particles to simulate realistic 3D movements.
• Understand the principles of non-destructive modelling and animation.
• Export 3D models and assets to game engines, 3D printers, or other software.

This instructor-led, live training in BRICS Corporate Offsite Training Venues (online or onsite) is aimed at beginner-level to intermediate-level developers who wish to install and use ROCm on Windows 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, a AMD GPU, and Visual Studio Code on Windows.
• 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 BRICS Corporate Offsite Training Venues (online or onsite) is aimed at beginner-level 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 BRICS Corporate Offsite Training Venues (online or onsite) is intended 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 projects.

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, as well as rendering.

This instructor-led, live training session in BRICS Corporate Offsite Training Venues (available online or on-site) targets beginner to intermediate-level graphic designers and animators who wish to learn how to create stunning animations, interactive media, and engaging web content using Adobe Animate.

By the end 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.

This instructor-led, live training in BRICS Corporate Offsite Training Venues (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.

97% of clients are satisfied.

This instructor-led live training in BRICS Corporate Offsite Training Venues (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.

This instructor-led, live training in BRICS Corporate Offsite Training Venues (online or onsite) is designed for beginner-level system administrators and IT professionals who wish to install, configure, manage, and troubleshoot CUDA environments.

Upon completing this training, participants will be able to:

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

This instructor-led, live training in BRICS Corporate Offsite Training Venues (online or onsite) is designed for beginner to intermediate-level developers who want to use OpenCL to program heterogeneous devices and leverage their parallelism.

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

• Set up a development environment comprising the OpenCL SDK, an OpenCL-compatible device, and Visual Studio Code.
• Develop a fundamental OpenCL program that performs vector addition on the device and retrieves results from device memory.
• Utilize the OpenCL API to query device information, and create contexts, command queues, buffers, kernels, and events.
• Write kernels using the OpenCL C language to execute on the device and manipulate data.
• Employ OpenCL built-in functions, extensions, and libraries to carry out common tasks and operations.
• Leverage OpenCL host and device memory models to optimize data transfers and memory access.
• Use the OpenCL execution model to manage work-items, work-groups, and ND-ranges.
• Debug and test OpenCL programs using tools like CodeXL, Intel VTune, and NVIDIA Nsight.
• Optimize OpenCL programs through techniques such as vectorization, loop unrolling, local memory usage, and profiling.

This instructor-led, live training in BRICS Corporate Offsite Training Venues (online or onsite) targets 3D design and 3D printing enthusiasts from beginner to advanced levels 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 BRICS Corporate Offsite Training Venues (online or onsite) is designed for C++ developers who intend to use CUDA to expedite applications, develop high-performance GPU kernels, and exploit parallel algorithm libraries for scientific computing, data processing, and machine learning tasks.

This instructor-led, live training in BRICS Corporate Offsite Training Venues (online or onsite) is designed for C/C++ developers who wish to utilize CUDA to accelerate compute-intensive applications, including data processing, scientific simulations, machine learning workloads, and image processing pipelines.

This instructor-led, live training in BRICS Corporate Offsite Training Venues (online or onsite) targets software developers, data analysts, and technical professionals who want to use TensorFlow 2.x and Keras to build, train, and deploy deep learning models for computer vision, natural language processing, and multimodal applications.

This instructor-led, live training programme conducted in BRICS Corporate Offsite Training Venues explores GPU programming for parallel computing, the use of various platforms, hands-on work with CUDA features, and optimization strategies using CUDA. Relevant applications include deep learning, analytics, image processing, and engineering use cases.