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Course Outline
Introduction
- What is ROCm?
- What is HIP?
- ROCm vs CUDA vs OpenCL
- Overview of ROCm and HIP features and architecture
- Setting up the Development Environment
Getting Started
- Creating a new ROCm project using Visual Studio Code
- Exploring the project structure and files
- Compiling and running the program
- Displaying the output using printf and fprintf
ROCm API
- Understanding the role of the ROCm API in host programs
- Using the ROCm API to query device information and capabilities
- Using the ROCm API to allocate and deallocate device memory
- Using the ROCm API to copy data between host and device
- Using the ROCm API to launch kernels and synchronize threads
- Using the ROCm API to handle errors and exceptions
HIP Language
- Understanding the role of the HIP language in device programs
- Using the HIP language to write kernels that execute on the GPU and manipulate data
- Using HIP data types, qualifiers, operators, and expressions
- Using HIP built-in functions, variables, and libraries for common tasks and operations
ROCm and HIP Memory Model
- Understanding the difference between host and device memory models
- Using ROCm and HIP memory spaces, such as global, shared, constant, and local
- Using ROCm and HIP memory objects, such as pointers, arrays, textures, and surfaces
- Using ROCm and HIP memory access modes, such as read-only, write-only, and read-write
- Understanding ROCm and HIP memory consistency models and synchronization mechanisms
ROCm and HIP Execution Model
- Understanding the difference between host and device execution models
- Using ROCm and HIP threads, blocks, and grids to define parallelism
- Using ROCm and HIP thread functions, such as hipThreadIdx_x, hipBlockIdx_x, hipBlockDim_x, etc.
- Using ROCm and HIP block functions, such as __syncthreads, __threadfence_block, etc.
- Using ROCm and HIP grid functions, such as hipGridDim_x, hipGridSync, cooperative groups, etc.
Debugging
- Understanding common errors and bugs in ROCm and HIP programs
- Using the Visual Studio Code debugger to inspect variables, breakpoints, call stack, etc.
- Using the ROCm Debugger to debug ROCm and HIP programs on AMD devices
- Using the ROCm Profiler to analyze ROCm and HIP programs on AMD devices
Optimization
- Understanding factors that affect the performance of ROCm and HIP programs
- Using ROCm and HIP coalescing techniques to improve memory throughput
- Using ROCm and HIP caching and prefetching techniques to reduce memory latency
- Using ROCm and HIP shared memory and local memory techniques to optimize memory accesses and bandwidth
- Using ROCm and HIP profiling and profiling tools to measure and improve execution time and resource utilization
Summary and Next Steps
Requirements
- Familiarity with C/C++ languages and parallel programming concepts.
- Basic knowledge of computer architecture and memory hierarchy.
- Experience using command-line tools and code editors.
Audience
- Developers aiming to learn how to use ROCm and HIP for programming AMD GPUs and exploiting their parallelism.
- Developers seeking 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.
28 Hours
