[fuzz] Handle statistical error in normalization of CPU times Since the normalization values are experimentally determined they have potential for error. Previous experience suggests to me that this error might be significant, so adding support for quantifying and propagating it in the calculations. Specifically multiple iterations of normalization microbenchmarking are now run to produce a mean and error which is then propagated through to later calculations. Since normalization is now considered an experimental value, it is no longer used as a substitute for burn-in, so the overall experimental harness is reworked to be more readable/sequential. If there are any normalization or experimental tasks to be run, then burn-in (if enabled) is run before hand, so that thermal throttling/etc is minimized. The terminology around normalization has been, well normalized, since it was confusingly referred to as perf score and benchmarking in different parts of the code. Also re-shuffled members in structs and documentation to be better grouped together, since the burn-in values and normalization ones were interleaved in places. Bug: 524444910 Change-Id: Ic7b31173b2aaa5950f46fd789284ec38ab16f7b9 Reviewed-on: https://dawn-review.googlesource.com/c/dawn/+/339415 Reviewed-by: dan sinclair <dsinclair@chromium.org> Commit-Queue: Ryan Harrison <rharrison@chromium.org>
Dawn is an open-source and cross-platform implementation of the WebGPU standard. More precisely it implements webgpu.h that is a one-to-one mapping with the WebGPU IDL. Dawn is meant to be integrated as part of a larger system and is the underlying implementation of WebGPU in Chromium.
Dawn provides several WebGPU building blocks:
webgpu.h version that Dawn implements.webgpu.h.Helpful links:
Developer documentation:
User documentation: (TODO, figure out what overlaps with the webgpu.h docs)
BSD 3-Clause License, please see LICENSE.
This is not an officially supported Google product.