First day
Introduction to OpenCL
- History
- OpenCL 1.0
- OpenCL 1.1
- OpenCL 1.2
- OpenCP/EP (Embedded Profile)
- Design goals of OpenCL
- CPUs, GPUs and GPGPUs
- Data-parallel and Task-parallel
- Hardware related and portable
- Terminology
- Host / Device
- Memory model
- Execution Model
The OpenCL Architecture
- The OpenCL Architecture
- Platform Model
- Execution Model
- Memory Model
- Programming Model
- The OpenCL Software Stack
- Example
| Exercise: |
Installation and test of the OpenCL SDK |
The OpenCL Host API
- Platform layer
- Querying and selecting devices
- Managing compute devices
- Managing computing contexts and queues
- The host objects: program, kernel, buffer, image
| Exercise: |
Write a platform discovery and analysis program (displaying CPUs, GPUs, versions...) |
- Runtime
- Managing resources
- Managing memory domains
- Executing compute kernels
| Exercise: |
Write an image loader program, transferring image to/from compute devices |
- Compiler
- The OpenCL C programming language
- Online compilation
- Offline compilation
Second day
The Basic OpenCL Execution Model
- How code is executed on hardware
- Compute kernel
- Compute program
- Application queues
- OpenCL Data-parallel execution
- N-dimensional computation domains
- Work-items and work-groups
- Synchronization and communication in a work-group
- Mapping global work size to work-groups
- Parallel execution of work-groups
| Exercise: |
Compile and execute a program to square an array on the platform computing nodes |
The OpenCL Programming Language
- Restrictions from C99
- Data types
- Scalar
- Vector
- Structs and pointers
- Type-conversion functions
- Image types
| Exercise: |
Rewrite the square program to use vector operations |
- Required built-in functions
- Work-item functions
- Math and relational
- Input/output
- Geometric functions
- Synchronization
- Optional features
| Exercise: |
Write and execute an image manipulation program (Blur filter) |
Third day
Advanced OpenCL Execution modes
| Exercise: |
Enhance the image manipulation program to measure kernel computation time |
- The OpenCL Memory Model
- Global Memory
- Local Memory
- Private Memory
- OpenCL Task-parallel execution
- Optional OpenCL feature
- Native work-items
| Exercise: |
Simulate the N-Body problem, displaying data using OpenGL |
Efficient OpenCL
- When (not) to use OpenCL
- Code design guidelines
- Explicit vectorization
| Exercise: |
Explore vectorisation on an image rotation kernel |
- Memory latency and access patterns
- ALU latency
- Using local memory
| Exercise: |
Enhance the Blur filter program to investigate memory optimisations |
- Synchronizing threads
- Warps/Wavefronts, work groups, and GPU cores
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