opencl introduction an example for opencl lu oct.11 2014
TRANSCRIPT
OpenCL Introduction
AN EXAMPLE FOR OPENCLLU LU
OCT.11 2014
2OPENCL INTRODUCTION | APRIL 11, 2014
CONTENTS
1. Environment Configuration
2. Case Analyzing
1. ENVIRONMENT CONFIGURATION
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1. ENVIRONMENT CONFIGURATION
IDE– Any IDE for C/C++ could use OpenCL.– We use Microsoft Visual Studio 2010.
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.
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1. ENVIRONMENT CONFIGURATION
Include Directory
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1. ENVIRONMENT CONFIGURATION
Lib Directory
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1. ENVIRONMENT CONFIGURATION
OpenCL Lib
2. CASE ANALYZING
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2. CASE ANALYZING
1. Problem Description
2. Algorithm
3. Calculation Features
4. Parallelizing
5. Programming1. Kernel2. Host
6. Tools1. AMD Profiler2. gDEBugger
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2.1 PROBLEM DESCRIPTION
Input an image, the rotation center and angle;
Output the rotated image with the same size of the input (original) image.
Original Rotated
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2.2 ALGORITHM
Let be the rotation center, be the rotation angle;
A point in original image will be move into the new position after rotating clockwise as per following formula:
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2.3 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.
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2.4 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.
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2.5 PROGRAMMING
1. Kernel– which run in GPU.
2. Host– which run in CPU.
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2.5.1 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 < W)) && (((int)ypos >= 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. }
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2.5.1 KERNEL
This kernel will rotate the image with rotation angle anticlockwise.
OpenCL defined some native function, such as sin and cos, but here calculate these value in host and pass them as parameters to the kernel because they are the same for every work-item.
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2.5.1 KERNEL
KernelAnalyzer
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2.5.1 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.
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2.5.2 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
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2.5.2 HOST
Query Platformcl_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 Platform
Query Devices
Create Context
Create Command Queue
Compile Program
Create Kernel
Create Buffers
Write buffers
Set Kernel Arguments
Run Kernel
Read buffers
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2.5.2 HOST
Query Devicescl_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
Query Devices
Create Context
Create Command Queue
Compile Program
Create Kernel
Create Buffers
Write buffers
Set Kernel Arguments
Run Kernel
Read buffers
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2.5.2 HOST Query Platform
Query Devices
Create Context
Create Command Queue
Compile Program
Create Kernel
Create Buffers
Write buffers
Set Kernel Arguments
Run Kernel
Read buffers
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2.5.2 HOST
Create Contextcl_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 Queuecl_command_queue clCreateCommandQueue (
cl_context context,cl_device_id device,cl_command_queue_properties properties,cl_int *errcode_ret)
Query Platform
Query Devices
Create Context
Create Command Queue
Compile Program
Create Kernel
Create Buffers
Write buffers
Set Kernel Arguments
Run Kernel
Read buffers
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2.5.2 HOST Query Platform
Query Devices
Create Context
Create Command Queue
Compile Program
Create Kernel
Create Buffers
Write buffers
Set Kernel Arguments
Run Kernel
Read buffers
Compile Programcl_program clCreateProgramWithSource(
cl_context context,cl_uint count,const char **strings,const size_t *lengths,cl_int *errcode_ret)
Create Kernelcl_kernel clCreateKernel (
cl_program program,const char *kernel_name,cl_int *errcode_ret)
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2.5.2 HOST Query Platform
Query Devices
Create Context
Create Command Queue
Compile Program
Create Kernel
Create Buffers
Write buffers
Set Kernel Arguments
Run Kernel
Read buffers
Create Bufferscl_mem clCreateBuffer (cl_context context,
cl_mem_flags flags,size_t size,void *host_ptr,cl_int *errcode_ret)
Write Bufferscl_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)
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2.5.2 HOST Query Platform
Query Devices
Create Context
Create Command Queue
Compile Program
Create Kernel
Create Buffers
Write buffers
Set Kernel Arguments
Run Kernel
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 Kernelcl_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)
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2.5.2 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
Run Kernel
Read buffers
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2.5.2 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
Run Kernel
Read buffers
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2.5.2 HOST
Read Bufferscl_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
Read buffers
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2.5.2 HOST
Release– clReleaseKernel– clReleaseProgram– clReleaseMemObject– clReleaseCommandQueue– clReleaseContext– clReleaseDevice
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2.6 TOOLS
1. AMD Profiler
2. gDEBugger
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2.6.1 AMD PROFILER
Counters
We can see the running information of any kernel.
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2.6.1 AMD PROFILER
Trace
Trace the OpenCL Runtime.
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2.6.2 GDEBUGGER
Debug into kernel
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THANK YOU!
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