GPU Programming with OpenCL Training Course

Introduction

• What is OpenCL?
• Comparing OpenCL, CUDA, and SYCL
• Overview of OpenCL features and architecture
• Configuring the Development Environment

Getting Started

• Creating a new OpenCL project in Visual Studio Code
• Exploring the project structure and key files
• Compiling and executing the program
• Displaying output using printf and fprintf

OpenCL API

• Understanding the role of the OpenCL API in host programs
• Using the OpenCL API to query device information and capabilities
• Creating contexts, command queues, buffers, kernels, and events via the OpenCL API
• Enqueuing commands such as read, write, copy, map, unmap, execute, and wait using the OpenCL API
• Handling errors and exceptions with the OpenCL API

OpenCL C

• Understanding the role of OpenCL C in device programs
• Writing kernels that execute on the device and manipulate data using OpenCL C
• Utilizing OpenCL C data types, qualifiers, operators, and expressions
• Using OpenCL C built-in functions for math, geometry, and relations
• Leveraging OpenCL C extensions and libraries, including atomic, image, and cl_khr_fp16

OpenCL Memory Model

• Distinguishing between host and device memory models
• Working with OpenCL memory spaces such as global, local, constant, and private
• Managing OpenCL memory objects like buffers, images, and pipes
• Applying OpenCL memory access modes including read-only, write-only, and read-write
• Implementing the OpenCL memory consistency model and synchronization mechanisms

OpenCL Execution Model

• Distinguishing between host and device execution models
• Defining parallelism using OpenCL work-items, work-groups, and ND-ranges
• Using OpenCL work-item functions such as get_global_id, get_local_id, and get_group_id
• Applying OpenCL work-group functions including barrier, work_group_reduce, and work_group_scan
• Utilizing OpenCL device functions such as get_num_groups, get_global_size, and get_local_size

Debugging

• Identifying common errors and bugs in OpenCL programs
• Inspecting variables, breakpoints, and call stacks using the Visual Studio Code debugger
• Debugging and analyzing OpenCL programs on AMD devices using CodeXL
• Debugging and analyzing OpenCL programs on Intel devices using Intel VTune
• Debugging and analyzing OpenCL programs on NVIDIA devices using NVIDIA Nsight

Optimization

• Understanding factors that influence OpenCL program performance
• Improving arithmetic throughput using OpenCL vector data types and vectorization techniques
• Reducing control overhead and increasing locality through OpenCL loop unrolling and loop tiling
• Optimizing memory access and bandwidth using OpenCL local memory and related functions
• Measuring and improving execution time and resource utilization using OpenCL profiling tools