OpenCL Introduction AN EXAMPLE FOR OPENCL LU OCT

2OPENCL INTRODUCTION | APRIL 11, 2014 CONTENTS 1.Environment Configuration 2.Case Analyzing

1. ENVIRONMENT CONFIGURATION

4OPENCL INTRODUCTION | APRIL 11, ENVIRONMENT CONFIGURATION  IDE –Any IDE for C/C++ could use OpenCL. –We use Microsoft Visual Studio  Setting for the requiring projects: –Add include path of the SDK to Additional include directories. –Add library path of the SDK to Additional library directories.

5OPENCL INTRODUCTION | APRIL 11, ENVIRONMENT CONFIGURATION  Include Directory

6OPENCL INTRODUCTION | APRIL 11, ENVIRONMENT CONFIGURATION  Lib Directory

7OPENCL INTRODUCTION | APRIL 11, ENVIRONMENT CONFIGURATION  OpenCL Lib

2. CASE ANALYZING

9OPENCL INTRODUCTION | APRIL 11, CASE ANALYZING 1.Problem Description 2.Algorithm 3.Calculation Features 4.Parallelizing 5.Programming 1.Kernel 2.Host 6.Tools 1.AMD Profiler 2.gDEBugger

10OPENCL INTRODUCTION | APRIL 11, PROBLEM DESCRIPTION  Input an image, the rotation center and angle;  Output the rotated image with the same size of the input (original) image. OriginalRotated

11OPENCL INTRODUCTION | APRIL 11, ALGORITHM

12OPENCL INTRODUCTION | APRIL 11, CALCULATION FEATURES  The calculation for each point is the same and independent;  A large amount of points.  So it is fit for parallel computing with GPU.

13OPENCL INTRODUCTION | APRIL 11, PARALLELIZING  With OpenCL framework, assign one work-item for the calculation for each point.  There are two methods to implement the algorithm: –Assign work-items as per original image; For each point, calculate the new position and copy it to the output image; Write-memory conflict. –Assign work-items as per output image. For each point, calculate the source position and copy it from the original image; Read-memory conflict.

14OPENCL INTRODUCTION | APRIL 11, PROGRAMMING 1.Kernel –which run in GPU. 1.Host –which run in CPU.

15OPENCL INTRODUCTION | APRIL 11, KERNEL 1.__kernel void image_rotate( 2.__global float * src_data, __global float * dest_data,//Data in global memory 3.int W, int H,//Image Dimensions 4.float sinTheta, float cosTheta )//Rotation Parameters 5.{ 6.//Thread gets its index within index space 7.const int ix = get_global_id(0); 8.const int iy = get_global_id(1); 9.//Calculate location of data to move into ix and iy– Output decomposition as mentioned 10.float xpos = (((float)ix) * cosTheta + ((float)iy) * sinTheta); 11.float ypos = (((float)iy) * cosTheta - ((float)ix) * sinTheta); 12.//Bound Checking 13. if ((((int)xpos >= 0) && ((int)xpos = 0) && ((int)ypos < H))) 14.{ 15.//Read (xpos,ypos) src_data and store at (ix,iy) in dest_data 16.dest_data[iy * W + ix] = src_data[(int)(floor(ypos * W + xpos))]; 17. } 18.}

16OPENCL INTRODUCTION | APRIL 11, KERNEL

17OPENCL INTRODUCTION | APRIL 11, KERNEL  KernelAnalyzer

18OPENCL INTRODUCTION | APRIL 11, KERNEL  KernelAnalyzer –We can see the bottlenecks are ALU ops. –It means that the main work of kernel is calculation, but not the data transfer. –This kernel has high performance.

19OPENCL INTRODUCTION | APRIL 11, HOST Platform Query Platform Query Devices Create Context Create Command Queue Compiler Compile Program Create Kernel Runtime Create Buffers Write buffers Set Kernel Arguments Run Kernel Read buffers

20OPENCL INTRODUCTION | APRIL 11, HOST  Query Platform cl_int clGetPlatformIDs (cl_uint num_entries, cl_platform_id *platforms, cl_uint *num_platforms) –This function is usually called twice; first calling is for getting the number of platform, and second calling is for getting the platforms. –First calling: clGetPlatformIDs(NULL, NULL, num) –Second calling: clGetPlatformIDs(num, platforms, NULL) Query Devices Create Context Create Command Queue Compile Program Create Kernel Create Buffers Write buffers Set Kernel Arguments Run Kernel Read buffers

21OPENCL INTRODUCTION | APRIL 11, HOST  Query Devices cl_int clGetDeviceIDs (cl_platform_id platform, cl_device_type device_type, cl_uint num_entries, cl_device_id *devices, cl_uint *num_devices) –This function is also usually called twice just like clGetPlatformIDs. –device_type: CL_DEVICE_TYPE_ALL CL_DEVICE_TYPE_CPU CL_DEVICE_TYPE_GPU Query Platform Create Context Create Command Queue Compile Program Create Kernel Create Buffers Write buffers Set Kernel Arguments Run Kernel Read buffers

22OPENCL INTRODUCTION | APRIL 11, HOST Query Platform Create Context Create Command Queue Compile Program Create Kernel Create Buffers Write buffers Set Kernel Arguments Run Kernel Read buffers

23OPENCL INTRODUCTION | APRIL 11, HOST  Create Context cl_context clCreateContext ( const cl_context_properties *properties, cl_uint num_devices, const cl_device_id *devices, void (CL_CALLBACK *pfn_notify)(const char *errinfo, const void *private_info, size_t cb, void *user_data), void *user_data, cl_int *errcode_ret)  Create Command Queue cl_command_queue clCreateCommandQueue ( cl_context context, cl_device_id device, cl_command_queue_properties properties, cl_int *errcode_ret) Query Platform Query Devices Compile Program Create Kernel Create Buffers Write buffers Set Kernel Arguments Run Kernel Read buffers

24OPENCL INTRODUCTION | APRIL 11, HOST Query Platform Query Devices Create Context Create Command Queue Create Buffers Write buffers Set Kernel Arguments Run Kernel Read buffers  Compile Program cl_program clCreateProgramWithSource( cl_context context, cl_uint count, const char **strings, const size_t *lengths, cl_int *errcode_ret)  Create Kernel cl_kernel clCreateKernel ( cl_program program, const char *kernel_name, cl_int *errcode_ret)

25OPENCL INTRODUCTION | APRIL 11, HOST Query Platform Query Devices Create Context Create Command Queue Compile Program Create Kernel Set Kernel Arguments Run Kernel Read buffers  Create Buffers cl_mem clCreateBuffer (cl_context context, cl_mem_flags flags, size_t size, void *host_ptr, cl_int *errcode_ret)  Write Buffers cl_int clEnqueueWriteBuffer (cl_command_queue command_queue, cl_mem buffer, cl_bool blocking_write, size_t offset, size_t size, const void *ptr, cl_uint num_events_in_wait_list, const cl_event *event_wait_list, cl_event *event)

26OPENCL INTRODUCTION | APRIL 11, HOST Query Platform Query Devices Create Context Create Command Queue Compile Program Create Kernel Create Buffers Write buffers Read buffers  Set Kernel Arguments (for each one) cl_int clSetKernelArg (cl_kernel kernel, cl_uint arg_index, size_t arg_size, const void *arg_value)  Run Kernel cl_int clEnqueueNDRangeKernel (cl_command_queue command_queue, cl_kernel kernel, cl_uint work_dim, const size_t *global_work_offset, const size_t *global_work_size, const size_t *local_work_size, cl_uint num_events_in_wait_list, const cl_event *event_wait_list, cl_event *event)

27OPENCL INTRODUCTION | APRIL 11, HOST  Parameters of clEnqueueNDRangeKernel –work_dim is the number of dimensions used to specify the global work-items and work-items in the work-group. –global_work_offset can be used to specify an array of work_dim unsigned values that describe the offset used to calculate the global ID of a work-item. –If global_work_offset is NULL, the global IDs start at offset (0, 0, … 0). –local_work_size points to an array of work_dim unsigned values that describe the number of work- items that make up a work-group (also referred to as the size of the work-group) that will execute the kernel specified by kernel. Query Platform Query Devices Create Context Create Command Queue Compile Program Create Kernel Create Buffers Write buffers Set Kernel Arguments Read buffers

28OPENCL INTRODUCTION | APRIL 11, HOST  Parameters of clEnqueueNDRangeKernel –global_work_size into appropriate work-group instances. If local_work_size is specified, global_work_size must be evenly divisible by local_work_size. –event_wait_list and num_events_in_wait_list specify events that need to complete before this particular command can be executed. –event returns an event object that identifies this particular kernel execution instance. Query Platform Query Devices Create Context Create Command Queue Compile Program Create Kernel Create Buffers Write buffers Set Kernel Arguments Read buffers

29OPENCL INTRODUCTION | APRIL 11, HOST  Read Buffers cl_int clEnqueueReadBuffer ( cl_command_queue command_queue, cl_mem buffer, cl_bool blocking_read, size_t offset, size_t size, void *ptr, cl_uint num_events_in_wait_list, const cl_event *event_wait_list, cl_event *event) Query Platform Query Devices Create Context Create Command Queue Compile Program Create Kernel Create Buffers Write buffers Set Kernel Arguments Run Kernel

30OPENCL INTRODUCTION | APRIL 11, HOST  Release –clReleaseKernel –clReleaseProgram –clReleaseMemObject –clReleaseCommandQueue –clReleaseContext –clReleaseDevice

31OPENCL INTRODUCTION | APRIL 11, TOOLS 1.AMD Profiler 2.gDEBugger

32OPENCL INTRODUCTION | APRIL 11, AMD PROFILER  Counters We can see the running information of any kernel.

33OPENCL INTRODUCTION | APRIL 11, AMD PROFILER  Trace Trace the OpenCL Runtime.

34OPENCL INTRODUCTION | APRIL 11, GDEBUGGER  Debug into kernel

35OPENCL INTRODUCTION | APRIL 11, 2014 THANK YOU!

36OPENCL 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.