[HTML][HTML] AI augmented Edge and Fog computing: Trends and challenges
In recent years, the landscape of computing paradigms has witnessed a gradual yet
remarkable shift from monolithic computing to distributed and decentralized paradigms such …
remarkable shift from monolithic computing to distributed and decentralized paradigms such …
DCNetBench: Scaleable Data Center Network Benchmarking
Data center networking is the central infrastructure of the modern information society.
However, benchmarking them is very challenging as the real-world network traffic is difficult …
However, benchmarking them is very challenging as the real-world network traffic is difficult …
SAIBench: A Structural Interpretation of AI for Science Through Benchmarks
Y Li, J Zhan - arXiv preprint arXiv:2311.17869, 2023 - arxiv.org
Artificial Intelligence for Science (AI4S) is an emerging research field that utilizes machine
learning advancements to tackle complex scientific computational issues, aiming to enhance …
learning advancements to tackle complex scientific computational issues, aiming to enhance …
Does AI for science need another ImageNet Or totally different benchmarks? A case study of machine learning force fields
Abstract AI for science (AI4S) is an emerging research field that aims to enhance the
accuracy and speed of scientific computing tasks using machine learning methods …
accuracy and speed of scientific computing tasks using machine learning methods …
Preliminary Scaling Characterization of TPCx-AI
A Raina - Performance Evaluation and Benchmarking: 14th TPC …, 2023 - books.google.com
TPCx-AI is the latest TPC benchmark addressing some of the numerous challenges in AI
benchmarking. It has the ability to scale datasets, to emulate machine learning and deep …
benchmarking. It has the ability to scale datasets, to emulate machine learning and deep …