Improve runtime feature detection (and performance) #21
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
The Problem
By relying heavily on compile-time feature detection, rather than runtime feature detection, the library was more fragile (leading to bugs like #14) and unable to gracefully degrade across CPU architecture variants with a single build.
The Solution
Rely on runtime feature detection (out of the hot path) to determine which hardware acceleration target to use, enabling graceful degradation across CPU types with a single build, and minimizing the risk of a
SIGILLor similar bug sneaking in.As a side benefit, AWS Graviton targets are ~36% faster and peak at ~53GiB/s (Graviton4).
Changes
checksumutility to enable easier benchmarking using a single binary, rather than a source checkout, across platforms.Planned version bump
MINORLinks