ROCm for Windows Training Course
ROCm is an open-source GPU programming platform that supports AMD GPUs and offers compatibility with CUDA and OpenCL. It provides developers with direct access to hardware details, allowing complete control over parallelization. However, this requires a solid understanding of device architecture, memory models, execution models, and optimization techniques.
The recent introduction of ROCm for Windows allows users to install and utilize ROCm on the Windows operating system, which is prevalent in both personal and professional settings. This enables users to harness the power of AMD GPUs for applications such as artificial intelligence, gaming, graphics rendering, and scientific computing.
This instructor-led live training (available online or onsite) is designed for beginner to intermediate developers who want to install and use ROCm on Windows to program AMD GPUs and leverage their parallel processing capabilities.
Upon completion of this training, participants will be able to:
- Establish a development environment featuring the ROCm Platform, an AMD GPU, and Visual Studio Code on Windows.
- Develop a fundamental ROCm program that executes vector addition on the GPU and retrieves results from GPU memory.
- Utilize the ROCm API to query device information, allocate and deallocate device memory, transfer data between host and device, launch kernels, and synchronize threads.
- Write GPU-executing kernels and manipulate data using the HIP language.
- Employ HIP built-in functions, variables, and libraries for common tasks and operations.
- Leverage ROCm and HIP memory spaces—such as global, shared, constant, and local—to optimize data transfers and memory access.
- Control the threads, blocks, and grids that define parallelism using ROCm and HIP execution models.
- Debug and test ROCm and HIP programs using tools like ROCm Debugger and ROCm Profiler.
- Optimize ROCm and HIP programs through techniques such as coalescing, caching, prefetching, and profiling.
Course Format
- Interactive lectures and discussions.
- Extensive exercises and practice opportunities.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request customized training for this course, please contact us to arrange.
Course Outline
Introduction
- What is ROCm?
- What is HIP?
- ROCm vs CUDA vs OpenCL
- Overview of ROCm and HIP features and architecture
- ROCm for Windows vs ROCm for Linux
Installation
- Installing ROCm on Windows
- Verifying the installation and checking device compatibility
- Updating or uninstalling ROCm on Windows
- Troubleshooting common installation issues
Getting Started
- Creating a new ROCm project using Visual Studio Code on Windows
- Exploring the project structure and files
- Compiling and running the program
- Displaying the output using printf and fprintf
ROCm API
- Using ROCm API in the host program
- Querying device information and capabilities
- Allocating and deallocating device memory
- Copying data between host and device
- Launching kernels and synchronizing threads
- Handling errors and exceptions
HIP Language
- Using HIP language in the device program
- Writing kernels that execute on the GPU and manipulate data
- Using data types, qualifiers, operators, and expressions
- Using built-in functions, variables, and libraries
ROCm and HIP Memory Model
- Using different memory spaces, such as global, shared, constant, and local
- Using different memory objects, such as pointers, arrays, textures, and surfaces
- Using different memory access modes, such as read-only, write-only, read-write, etc.
- Using memory consistency models and synchronization mechanisms
ROCm and HIP Execution Model
- Using different execution models, such as threads, blocks, and grids
- Using thread functions, such as hipThreadIdx_x, hipBlockIdx_x, hipBlockDim_x, etc.
- Using block functions, such as __syncthreads, __threadfence_block, etc.
- Using grid functions, such as hipGridDim_x, hipGridSync, cooperative groups, etc.
Debugging
- Debugging ROCm and HIP programs on Windows
- Using Visual Studio Code debugger to inspect variables, breakpoints, call stack, etc.
- Using ROCm Debugger to debug ROCm and HIP programs on AMD devices
- Using ROCm Profiler to analyze ROCm and HIP programs on AMD devices
Optimization
- Optimizing ROCm and HIP programs on Windows
- Using coalescing techniques to improve memory throughput
- Using caching and prefetching techniques to reduce memory latency
- Using shared memory and local memory techniques to optimize memory accesses and bandwidth
- Using profiling and profiling tools to measure and improve execution time and resource utilization
Summary and Next Steps
Requirements
- Understanding of the C/C++ language and parallel programming concepts.
- Basic knowledge of computer architecture and memory hierarchy.
- Experience with command-line tools and code editors.
- Familiarity with the Windows operating system and PowerShell.
Audience
- Developers looking to learn how to install and use ROCm on Windows to program AMD GPUs and exploit their parallelism.
- Developers aiming to write high-performance, scalable code that runs across various AMD devices.
- Programmers interested in exploring the low-level aspects of GPU programming and optimizing code performance.
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