ROCm for Windows Training Course
ROCm is an open-source GPU programming platform designed for AMD graphics cards, offering compatibility with CUDA and OpenCL. It provides developers with direct access to hardware specifications, granting complete control over parallel processing tasks. However, effective utilization demands a solid grasp of device architecture, memory management, execution models, and optimization strategies.
ROCm for Windows is a recent advancement enabling the installation and operation of ROCm on the Windows OS, a platform prevalent in both personal and professional settings. This integration allows users to harness AMD GPU capabilities for diverse applications, including artificial intelligence, gaming, graphics rendering, and scientific computations.
This instructor-led live training, available online or onsite, targets beginner to intermediate developers interested in installing and utilizing ROCm on Windows to program AMD GPUs and leverage their parallel processing power.
Upon completion of this training, participants will be able to:
- Configure a development environment featuring 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 for GPU execution and data manipulation.
- Leverage HIP built-in functions, variables, and libraries for common tasks and operations.
- Optimize data transfers and memory access using ROCm and HIP memory spaces, including global, shared, constant, and local.
- Control threads, blocks, and grids to define parallelism using ROCm and HIP execution models.
- Debug and test ROCm and HIP applications using tools like the ROCm Debugger and ROCm Profiler.
- Enhance ROCm and HIP programs through techniques such as coalescing, caching, prefetching, and profiling.
Course Format
- Interactive lectures and discussions.
- Extensive exercises and practice sessions.
- Practical implementation in a live laboratory environment.
Customization Options
- To arrange customized training for this course, please contact us.
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 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 project structure and files
- Compiling and running the program
- Displaying output using printf and fprintf
ROCm API
- Using ROCm API in host programs
- 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 device programs
- Writing kernels for GPU execution and data manipulation
- Using data types, qualifiers, operators, and expressions
- Using built-in functions, variables, and libraries
ROCm and HIP Memory Model
- Using different memory spaces: global, shared, constant, and local
- Using various memory objects: pointers, arrays, textures, and surfaces
- Using memory access modes: read-only, write-only, read-write, etc.
- Understanding memory consistency models and synchronization mechanisms
ROCm and HIP Execution Model
- Utilizing execution models: threads, blocks, and grids
- Using thread functions like hipThreadIdx_x, hipBlockIdx_x, hipBlockDim_x, etc.
- Using block functions like __syncthreads, __threadfence_block, etc.
- Using grid functions like hipGridDim_x, hipGridSync, cooperative groups, etc.
Debugging
- Debugging ROCm and HIP programs on Windows
- Using Visual Studio Code debugger to inspect variables, breakpoints, and call stacks
- Using the ROCm Debugger for debugging ROCm and HIP programs on AMD devices
- Using the ROCm Profiler to analyze ROCm and HIP programs on AMD devices
Optimization
- Optimizing ROCm and HIP programs on Windows
- Improving memory throughput through coalescing techniques
- Reducing memory latency using caching and prefetching techniques
- Optimizing memory access and bandwidth using shared and local memory techniques
- Measuring and improving execution time and resource utilization using profiling tools
Summary and Next Steps
Requirements
- Understanding of 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 seeking to install and use ROCm on Windows to program AMD GPUs and exploit parallelism.
- Developers aiming to write high-performance, scalable code compatible with various AMD devices.
- Programmers interested in exploring low-level GPU programming aspects and optimizing code performance.
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