In-network caching for ICN-based IoT (ICN-IoT): A comprehensive survey

Z Zhang, CH Lung, X Wei, M Chen… - IEEE Internet of …, 2023 - ieeexplore.ieee.org
The Internet of Things (IoT) has already emerged as one of the most popular directions in
today's information and communication technology (ICT) domain. With its advancement over …

H2o: Heavy-hitter oracle for efficient generative inference of large language models

Z Zhang, Y Sheng, T Zhou, T Chen… - Advances in …, 2023 - proceedings.neurips.cc
Abstract Large Language Models (LLMs), despite their recent impressive accomplishments,
are notably cost-prohibitive to deploy, particularly for applications involving long-content …

A survey on sliding window sketch for network measurement

Z Zeng, L Cui, M Qian, Z Zhang, K Wei - Computer Networks, 2023 - Elsevier
As an important basis for network management, effective network measurement is critical for
improving network performance and security. As an efficient tool for network measurement …

A large-scale analysis of hundreds of in-memory key-value cache clusters at twitter

J Yang, Y Yue, KV Rashmi - ACM Transactions on Storage (TOS), 2021 - dl.acm.org
Modern web services use in-memory caching extensively to increase throughput and reduce
latency. There have been several workload analyses of production systems that have fueled …

FaasCache: kee** serverless computing alive with greedy-dual caching

A Fuerst, P Sharma - Proceedings of the 26th ACM International …, 2021 - dl.acm.org
Functions as a Service (also called serverless computing) promises to revolutionize how
applications use cloud resources. However, functions suffer from cold-start problems due to …

High performance cache replacement using re-reference interval prediction (RRIP)

A Jaleel, KB Theobald, SC Steely Jr… - ACM SIGARCH computer …, 2010 - dl.acm.org
Practical cache replacement policies attempt to emulate optimal replacement by predicting
the re-reference interval of a cache block. The commonly used LRU replacement policy …

Distributed hierarchical gpu parameter server for massive scale deep learning ads systems

W Zhao, D **e, R Jia, Y Qian, R Ding… - … of Machine Learning …, 2020 - proceedings.mlsys.org
Neural networks of ads systems usually take input from multiple resources, eg query-ad
relevance, ad features and user portraits. These inputs are encoded into one-hot or multi-hot …

[KNIHA][B] Algorithms to live by: The computer science of human decisions

B Christian, T Griffiths - 2016 - books.google.com
An exploration of how computer algorithms can be applied to our everyday lives to solve
common decision-making problems and illuminate the workings of the human mind. What …

{BGL}:{GPU-Efficient}{GNN} training by optimizing graph data {I/O} and preprocessing

T Liu, Y Chen, D Li, C Wu, Y Zhu, J He, Y Peng… - … USENIX Symposium on …, 2023 - usenix.org
Graph neural networks (GNNs) have extended the success of deep neural networks (DNNs)
to non-Euclidean graph data, achieving ground-breaking performance on various tasks such …

FIFO queues are all you need for cache eviction

J Yang, Y Zhang, Z Qiu, Y Yue, R Vinayak - Proceedings of the 29th …, 2023 - dl.acm.org
As a cache eviction algorithm, FIFO has a lot of attractive properties, such as simplicity,
speed, scalability, and flash-friendliness. The most prominent criticism of FIFO is its low …