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Introduction
Coding for the Intel® Processor Graphics
Platform-Level Considerations
Application-Level Optimizations
Optimizing OpenCL™ Usage with Intel® Processor Graphics
Check-list for OpenCL™ Optimizations
Performance Debugging
Using Multiple OpenCL™ Devices
Coding for the Intel® CPU OpenCL™ Device
OpenCL™ Kernel Development for Intel® CPU OpenCL™ device
Mapping Memory Objects
Using Buffers and Images Appropriately
Using Floating Point for Calculations
Using Compiler Options for Optimizations
Using Built-In Functions
Loading and Storing Data in Greatest Chunks
Applying Shared Local Memory
Using Specialization in Branching
Considering native_ and half_ Versions of Math Built-Ins
Using the Restrict Qualifier for Kernel Arguments
Avoiding Handling Edge Conditions in Kernels
Using Shared Context for Multiple OpenCL™ Devices
Sharing Resources Efficiently
Synchronization Caveats
Writing to a Shared Resource
Partitioning the Work
Keeping Kernel Sources the Same
Basic Frequency Considerations
Eliminating Device Starvation
Limitations of Shared Context with Respect to Extensions
Why Optimizing Kernel Code Is Important?
Avoid Spurious Operations in Kernel Code
Perform Initialization in a Separate Task
Use Preprocessor for Constants
Use Signed Integer Data Types
Use Row-Wise Data Accesses
Tips for Auto-Vectorization
Local Memory Usage
Avoid Extracting Vector Components
Task-Parallel Programming Model Hints
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Profiling Operations Using OpenCL™ Profiling Events
The following code snippet measures kernel execution using OpenCL™ profiling events (error handling is omitted):
g_cmd_queue = clCreateCommandQueue(…CL_QUEUE_PROFILING_ENABLE, NULL); clEnqueueNDRangeKernel(g_cmd_queue,…, &perf_event); clWaitForEvents(1, &perf_event); cl_ulong start = 0, end = 0; clGetEventProfilingInfo(perf_event, CL_PROFILING_COMMAND_START, sizeof(cl_ulong), &start, NULL); clGetEventProfilingInfo(perf_event, CL_PROFILING_COMMAND_END, sizeof(cl_ulong), &end, NULL); //END-START gives you hints on kind of “pure HW execution time” //the resolution of the events is 1e-09 sec g_NDRangePureExecTimeMs = (cl_double)(end - start)*(cl_double)(1e-06);
Important caveats:
- The queue should be enabled for profiling (CL_QUEUE_PROFILING_ENABLE property) at the time of creation.
- You need to explicitly synchronize the operation using clFinish() or clWaitForEvents. The reason is that device time counters for the profiled command, are associated with the specified event.
This way you can profile operations on both Memory Objects and Kernels. Refer to the OpenCL™ 1.2 Specification for the detailed description of profiling events.
NOTE:
The host-side wall-clock time might return different results. For the CPU the difference is typically negligible.
See Also
The OpenCL™ 1.2 Specification at http://www.khronos.org/registry/cl/specs/opencl-1.2.pdf
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