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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 ROCm API in the host program
- Using ROCm API to query device information and capabilities
- Using ROCm API to allocate and deallocate device memory
- Using ROCm API to copy data between host and device
- Using ROCm API to launch kernels and synchronize threads
- Using ROCm API to handle errors and exceptions
HIP Language
- Understanding the role of HIP language in the device program
- Using 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 to perform 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, read-write, etc.
- Using ROCm and HIP memory consistency model 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 the 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 the common errors and bugs in ROCm and HIP programs
- 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
- Understanding the 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 the execution time and resource utilization
Summary and Next Steps
Requirements
- An 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
Audience
- Developers who wish to learn how to use ROCm and HIP to program AMD GPUs and exploit their parallelism
- Developers who wish to write high-performance and scalable code that can run on different AMD devices
- Programmers who wish to explore the low-level aspects of GPU programming and optimize their code performance
28 Hours
Testimonials (5)
Podejście prowadzącego. Bardzo sympatyczny i z poczuciem humoru, jednocześnie z zachowaniem należytego profesjonalizmu. W razie pytań, odpowiedzi były zawsze wyczerpujące. Dla mnie jako osoby mało obeznaną z tematem programowania niskopoziomowego, otwartośc prowadzącego dużo pomoga.
Michał Kwiatek - Nokia Solutions and Networks Sp. z o.o.
Course - NVIDIA GPU Programming - Extended
zainteresowanie osobami ,które były na szkoleniu, tłumaczenie każdemu z osobna
agata miernik-dukielska - BANK SPÓŁDZIELCZY W OŁAWIE
Course - Raster and Vector Graphics (Adobe Photoshop, Corel Draw)
wszystko ok
Mariusz Orłowski - Narodowy Bank Polski
Course - Adobe LiveCycle Designer
praca na przykładach
Kacper Gardziała - Exacto Sp. z o.o.
Course - Adobe Illustrator
Very interactive with various examples, with a good progression in complexity between the start and the end of the training.
