1. OpenCL Introduction A TECHNICAL REVIEW LU OCT. 11 2014

2. 2OPENCL INTRODUCTION | APRIL 11, 2014 CONTENTS 1.OpenCL Architecture 2.OpenCL Programming 3.An Matrix Multiplication Example

3. 1. OPENCL ARCHITECTURE

4. 4OPENCL INTRODUCTION | APRIL 11, 2014 1. OPENCL ARCHITECTURE 1.Four Architectural Models Platform Model Execution Model Memory Model Programming Model 2.OpenCL Framework

5. 5OPENCL INTRODUCTION | APRIL 11, 2014 1.1 FOUR ARCHITECTURAL MODELS  Platform Model  Execution Model  Memory Model  Programming Model

6. 6OPENCL INTRODUCTION | APRIL 11, 2014 1.1.1 PLATFORM MODEL

7. 7OPENCL INTRODUCTION | APRIL 11, 2014 1.1.1 PLATFORM MODEL (CONT.)  One host equipped with OpenCL device(s).  An OpenCL device consists of compute unit(s)/CU(s).  A CU consists of processing element(s), or PE(s). –Computations on a device occur within PEs.

8. 8OPENCL INTRODUCTION | APRIL 11, 2014 1.1.2 EXECUTION MODEL  Kernels –execute on one or more OpenCL devices  Host Program –executes on the host –defines the context for the kernels –manages the execution of kernels

9. 9OPENCL INTRODUCTION | APRIL 11, 2014 1.1.2 EXECUTION MODEL (CONT.)  NDRange –an N-dimensional index space, where N is 1, 2 or 3  WORK-ITEM –an instance of the kernel –identified by a global ID in the NDRange –executes the same code in parallel The specific execution pathway through the code and the data operated upon can vary per work-item.

10. 10OPENCL INTRODUCTION | APRIL 11, 2014 1.1.2 EXECUTION MODEL (CONT.)  WORK-GROUP –Provide a coarse-grained decomposition of NDRange; –Be assigned a unique work-group ID with the same dimensionality as NDRange; –Use a unique local ID to identify each of its work-items. –Its work-items execute concurrently on the PEs of a single CU. –Kernels could use some synchronization controls within a work-group. –The NDRange size should be a multiple of the work-group size.

11. 11OPENCL INTRODUCTION | APRIL 11, 2014 1.1.2 EXECUTION MODEL (CONT.)

12. 12OPENCL INTRODUCTION | APRIL 11, 2014 1.1.2 EXECUTION MODEL (CONT.)  Context –The host defines a context for the execution of the kernels.  Resources in the context: –Devices The collection of OpenCL devices to be used by the host. –Kernels The OpenCL functions that run on OpenCL devices. –Program Objects The program source and executable that implement the kernels. –Memory Objects A set of memory objects visible to the host and the OpenCL devices. Memory objects contain values that can be operated on by instances of a kernel.

13. 13OPENCL INTRODUCTION | APRIL 11, 2014 1.1.2 EXECUTION MODEL (CONT.)  Command-queue –The host creates a data structure called a command-queue to coordinate execution of the kernels on the devices. –The host places commands into the command-queue which are then scheduled onto the devices within the context. –The command-queue schedules commands for execution on a device. –Commands execute asynchronously between the host and the device.

14. 14OPENCL INTRODUCTION | APRIL 11, 2014 1.1.2 EXECUTION MODEL (CONT.)  Commands in command-queue: –Kernel execution commands Execute a kernel on the processing elements of a device. –Memory commands Transfer data to, from, or between memory objects, or map and unmap memory objects from the host address space. –Synchronization commands Constrain the order of execution of commands.

15. 15OPENCL INTRODUCTION | APRIL 11, 2014 1.1.2 EXECUTION MODEL (CONT.)  Commands execute modes: –In-order Execution –Out-of-order Execution Any order constraints are enforced by the programmer through explicit synchronization commands

16. 16OPENCL INTRODUCTION | APRIL 11, 2014 1.1.3 MEMORY MODEL

17. 17OPENCL INTRODUCTION | APRIL 11, 2014 1.1.3 MEMORY MODEL (CONT.)  Private Memory –Per work-item  Local Memory –Shared within a work-group  Global/Constant Memory –Latter is cached  Host Memory –On the CPU  Memory management is explicit –must move data from host -> global -> local and back

18. 18OPENCL INTRODUCTION | APRIL 11, 2014 1.1.3 MEMORY MODEL (CONT.)  Memory Region –Allocation and Memory Access Capabilities

19. 19OPENCL INTRODUCTION | APRIL 11, 2014 1.1.3 MEMORY MODEL (CONT.)  Memory Consistency –OpenCL uses a relaxed consistency memory model; i.e., the state of memory visible to a work-item is not guaranteed to be consistent across the collection of work-items at all times –Within a work-item, memory has load/store consistency –Within a work-group at a barrier, local memory has consistency across work-items –Global memory is consistent within a work-group, at a barrier, but not guaranteed across different work-groups –Consistency of memory shared between commands are enforced through synchronization

20. 20OPENCL INTRODUCTION | APRIL 11, 2014 1.1.4 PROGRAMMING MODEL  Data Parallel Programming Model –All the work-items in NDRange execute in parallel.  Task Parallel Programming Model –Executing a kernel on a compute unit with a work-group containing a single work-item. –Express parallelism by: using vector data types implemented by the device, enqueuing multiple tasks, and/or enqueuing native kernels developed using a programming model orthogonal to OpenCL.

21. 21OPENCL INTRODUCTION | APRIL 11, 2014 1.1.4 PROGRAMMING MODEL (CONT.)  Synchronization –Work-items in a single work-group Work-group barrier –Commands enqueued to command-queue(s) in a single context Command-queue barrier Waiting on an event.

22. 22OPENCL INTRODUCTION | APRIL 11, 2014 1.1.4 PROGRAMMING MODEL (CONT.)  Events Synchronization

23. 23OPENCL INTRODUCTION | APRIL 11, 2014 1.2 OPENCL FRAMEWORK  OpenCL Platform layer –This layer allows a host program to discover OpenCL devices and their capabilities and to create contexts.  OpenCL Runtime –The runtime allows the host program to manipulate created contexts.  OpenCL Compiler –The compiler creates executable program containing OpenCL kernels. The OpenCL programming language implemented by the compiler supports a subset of the ISO C99 language with parallelism extensions.

24. 2. OPENCL PROGRAMMING

25. 25OPENCL INTRODUCTION | APRIL 11, 2014 2.2 BASIC STEPS  Step 1: Discover and initialize the platforms  Step 2: Discover and initialize the devices  Step 3: Create the context  Step 4: Create a command queue  Step 5: Create device buffers  Step 6: Write the host data to device buffers

26. 26OPENCL INTRODUCTION | APRIL 11, 2014 2.2 BASIC STEPS (CONT.)  Step 7: Create and compile the program  Step 8: Create the kernel  Step 9: Set the kernel arguments  Step 10: Configure the work-item structure  Step 11: Enqueue the kernel for execution  Step 12: Read the output buffer back to the host  Step 13: Release the OpenCL resources

27. 27OPENCL INTRODUCTION | APRIL 11, 2014 2.3 BASIC STRUCTURE  Host program –Query compute devices –Create the context and command-queue –Create memory objects associated to the context –Compile and create kernel objects –Issue commands to command-queue –Synchronization of commands –Release OpenCL resources  Kernels –C code with come restrictions and extensions Platform Layer Runtime Language

28. 3. AN EXAMPLE

29. 29OPENCL INTRODUCTION | APRIL 11, 2014 3.1 DESCRIPTION OF THE PROBLEM

30. 30OPENCL INTRODUCTION | APRIL 11, 2014 3.2 SERIAL IMPLEMENTATION

31. 31OPENCL INTRODUCTION | APRIL 11, 2014 3.3 CALCULATION PROCEDURE DIAGRAM A A B B C C

32. 32OPENCL INTRODUCTION | APRIL 11, 2014 3.4 CHARACTERS OF THE CALCULATION

33. 33OPENCL INTRODUCTION | APRIL 11, 2014 3.5 OPENCL IMPLEMENTATION

34. 34OPENCL INTRODUCTION | APRIL 11, 2014 3.6 OPENCL MATRIX-MULTIPLY CODE  kernel

35. 35OPENCL INTRODUCTION | APRIL 11, 2014 3.7 OPENCL IMPLEMENTATION Platform layer Runtime layer Compiler Query platform Query devices Command queue Create kernel Compile program Create buffers Set arguments Execute kernel

36. 36OPENCL INTRODUCTION | APRIL 11, 2014 THANK YOU!

37. 37OPENCL INTRODUCTION | APRIL 11, 2014 DISCLAIMER & ATTRIBUTION The information presented in this document is for informational purposes only and may contain technical inaccuracies, omissions and typographical errors. The information contained herein is subject to change and may be rendered inaccurate for many reasons, including but not limited to product and roadmap changes, component and motherboard version changes, new model and/or product releases, product differences between differing manufacturers, software changes, BIOS flashes, firmware upgrades, or the like. AMD assumes no obligation to update or otherwise correct or revise this information. However, AMD reserves the right to revise this information and to make changes from time to time to the content hereof without obligation of AMD to notify any person of such revisions or changes. AMD MAKES NO REPRESENTATIONS OR WARRANTIES WITH RESPECT TO THE CONTENTS HEREOF AND ASSUMES NO RESPONSIBILITY FOR ANY INACCURACIES, ERRORS OR OMISSIONS THAT MAY APPEAR IN THIS INFORMATION. AMD SPECIFICALLY DISCLAIMS ANY IMPLIED WARRANTIES OF MERCHANTABILITY OR FITNESS FOR ANY PARTICULAR PURPOSE. IN NO EVENT WILL AMD BE LIABLE TO ANY PERSON FOR ANY DIRECT, INDIRECT, SPECIAL OR OTHER CONSEQUENTIAL DAMAGES ARISING FROM THE USE OF ANY INFORMATION CONTAINED HEREIN, EVEN IF AMD IS EXPRESSLY ADVISED OF THE POSSIBILITY OF SUCH DAMAGES. ATTRIBUTION © 2013 Advanced Micro Devices, Inc. All rights reserved. AMD, the AMD Arrow logo and combinations thereof are trademarks of Advanced Micro Devices, Inc. in the United States and/or other jurisdictions. SPEC is a registered trademark of the Standard Performance Evaluation Corporation (SPEC). Other names are for informational purposes only and may be trademarks of their respective owners.