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Course Outline
Introduction
- What is ROCm?
- What is HIP?
- Comparison of ROCm, CUDA, and OpenCL for government applications
- Overview of ROCm and HIP features and architecture
- Setting up the Development Environment for government use
Getting Started
- Creating a new ROCm project using Visual Studio Code for government projects
- Exploring the project structure and files in a government context
- Compiling and running the program for government systems
- Displaying the output using printf and fprintf for government reporting
ROCm API
- Understanding the role of ROCm API in the host program for government operations
- Using ROCm API to query device information and capabilities for government systems
- Using ROCm API to allocate and deallocate device memory for government applications
- Using ROCm API to copy data between host and device for government data management
- Using ROCm API to launch kernels and synchronize threads for government computations
- Using ROCm API to handle errors and exceptions in government software
HIP Language
- Understanding the role of HIP language in the device program for government tasks
- Using HIP language to write kernels that execute on the GPU and manipulate data for government processes
- Using HIP data types, qualifiers, operators, and expressions for government programming
- Using HIP built-in functions, variables, and libraries to perform common tasks and operations in government applications
ROCm and HIP Memory Model
- Understanding the difference between host and device memory models for government systems
- Using ROCm and HIP memory spaces, such as global, shared, constant, and local, for government data storage
- Using ROCm and HIP memory objects, such as pointers, arrays, textures, and surfaces, for government data handling
- Using ROCm and HIP memory access modes, such as read-only, write-only, read-write, etc., for government data operations
- Using ROCm and HIP memory consistency model and synchronization mechanisms for government applications
ROCm and HIP Execution Model
- Understanding the difference between host and device execution models for government processes
- Using ROCm and HIP threads, blocks, and grids to define parallelism in government computations
- Using ROCm and HIP thread functions, such as hipThreadIdx_x, hipBlockIdx_x, hipBlockDim_x, etc., for government programming
- Using ROCm and HIP block functions, such as __syncthreads, __threadfence_block, etc., for government synchronization
- Using ROCm and HIP grid functions, such as hipGridDim_x, hipGridSync, cooperative groups, etc., for government parallel processing
Debugging
- Understanding the common errors and bugs in ROCm and HIP programs for government applications
- Using Visual Studio Code debugger to inspect variables, breakpoints, call stack, etc., in government software
- Using ROCm Debugger to debug ROCm and HIP programs on AMD devices for government systems
- Using ROCm Profiler to analyze ROCm and HIP programs on AMD devices for government performance monitoring
Optimization
- Understanding the factors that affect the performance of ROCm and HIP programs for government operations
- Using ROCm and HIP coalescing techniques to improve memory throughput in government applications
- Using ROCm and HIP caching and prefetching techniques to reduce memory latency in government systems
- Using ROCm and HIP shared memory and local memory techniques to optimize memory accesses and bandwidth for government data processing
- Using ROCm and HIP profiling and profiling tools to measure and improve the execution time and resource utilization for government tasks
Summary and Next Steps
Requirements
- An 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
Audience
- Developers who seek to learn how to use ROCm and HIP for programming AMD GPUs and leveraging their parallel capabilities
- Developers aiming to write high-performance, scalable code that can operate across various AMD devices
- Programmers interested in delving into the low-level aspects of GPU programming and optimizing code performance for government applications
28 Hours
