AWhat changed
Provided a lightweight C-language interface and optimized GPU convolution, pooling and activation primitives with forward/backward variants, reducing framework-specific kernel maintenance.
Scientific scope
Provided a lightweight C-language interface and optimized GPU convolution, pooling and activation primitives with forward/backward variants, reducing framework-specific kernel maintenance. Original2014 library report, not a claim to invent convolution, CUDA or later cuDNN features. Performance/memory gains depend on the measured model, kernel and hardware; portable interface does not imply identical performance across arbitrary devices.
Evidence
The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. Original2014 library report, not a claim to invent convolution, CUDA or later cuDNN features. Performance/memory gains depend on the measured model, kernel and hardware; portable interface does not imply identical performance across arbitrary devices.
Contributors
- Source-listed authors and technical contributors · SCIENCE: Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.
Provisional WRS assessment, edition 2026-10-16.1. Independent expert calibration is pending. This grade does not certify correctness or assign ownership.
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