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Posts related to the Building a National Finding Aid Network (NAFAN) project. From HangingTogether

Augmenting Amdahl's law with a corollary for multicore hardware makes it relevant to future generations of chips with multiple processor cores. Obtaining optimal multicore performance will require further research in both extracting more parallelism and making sequential cores faster.

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Kernels & AI inference engine for mobile devices

Join other members of the OCLC Research Library Partnership for an informal, small group discussion about the development of bibliometric and research impact (BRI) services.

The diagrams below were prepared by Jenna Hartel , based upon the work of Robert A. Stebbins. These diagrams may be reproduced      without permission, but please acknowledge their source as:...

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As the need for on-device artificial intelligence (AI) has increased in recent years, mobile devices tend to be equipped with multiple heterogeneous processors, including CPU, GPU, and Neural Processing Unit (NPU). While NPUs can offer low-cost and real-time AI processing capabilities for Deep Neural Network (DNN) inference, its limited resources often lead to a trade-off between performance and accuracy, potentially resulting in a non-trivial accuracy drop. To address this problem, we propose a new NPU–GPU Scheduling (NGS) framework for DNN-based video analytics. The main challenge lies in determining when and how to execute inference on the NPU/GPU to satisfy the performance objectives. To make more precise scheduling decisions, we first propose a new image complexity assessment model to replace the existing normalized edge density metric. Then, we formulate the scheduling problem with the objective of maximizing inference accuracy under the given latency constraint, and introduce an adaptive solution based on dynamic programming to determine which frames should be processed on the GPU and when to exit from inference for each of them. Extensive experiments conducted on a real mobile device show that our NGS framework substantially outperforms other solutions, and achieves a close-to-oracle performance.

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Discover how ResNets revolutionize deep learning by solving vanishing gradients, enabling ultradeep networks for image analysis, NLP, and more.

In this webinar, librarians from three research universities describe the services, collaborations, and strategies they are employing to develop research impact services at their institutions.

encodes the proper noun to identify a group of persons closely related by blood or forming a household. This could be a single family unit, or an extended family.... Read the Rest »

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