Getting Credible Performance Numbers

Performance measurements are done on a large number of invocations of the same routine. Since the first iteration is almost always significantly slower than the subsequent ones, the minimum (or average, geometric mean, etc) value for the execution time is usually used for final projections.

An alternative to calling the kernel many times is to use a single “warm-up” run.

The “warm-up” might be helpful for small/lightweight kernels. Specifically it helps to amortize the following potential (one-time) costs:

NOTE: You need to build your performance conclusions on reproducible data. If “warming” run does not help and/or execution time still varies, you can try running large number of iterations and then average the results (for time values that range too much, consider using geomean).

Consider the following:

Kernels that are very lightweight do not give reliable data, so making them artificially heavier could give you important insights into the hotspots. For example, you can add loop in the kernel, or replicate its heavy pieces.

Please refer to the “OpenCL* Optimizations Tutorial” SDK sample for code examples of performing “warm-up” activities before starting performance measurement. You can download the sample from the Intel® SDK for OpenCL* Applications division of the VCSource webportal.

See Also


Using Tools (suggested next topic)
OpenCL* Optimizations Tutorial SDK sample available for downloads at VCSource webportal
Related Documents: “Working with the -cl-fast-relaxed-math Flag” section of the User's Guide
The OpenCL* 1.1 Specification at http://www.khronos.org portal [PDF]
Overview Presentations of the OpenCL* Standard at http://www.khronos.org portal [Online Article]
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