
Chongyan Gu - Google 学术搜索 - Google Scholar
Proceedings of the 3rd ACM Workshop on Attacks and Solutions in Hardware …
Department of Computer Science at North Carolina State …
The ACM Symposium on Cloud Computing 2020 (SoCC '20) recently awarded Dr. Xiaohui (Helen) Gu and co-authors, Zhiming Shen (Exotanium, Inc.), Sethuraman Subbiah (Amazon), and John Wilkes (Google), the 10-Year Best Paper Award for their paper “CloudScale: Elastic Resource Scaling for Multi-Tenant Cloud Systems”. This paper focuses on the ...
【论文推荐】SoCC 2023开源代码汇总 - 知乎 - 知乎专栏
ACM Symposium on Cloud Computing (SoCC)是CCF列表计算机体系结构/并行与分布计算/存储系统B类会议。 最近SoCC 2023的论文上线了 ACM Digital Library ,从中整理了提供开源代码的论文,包括14篇论文,希望对相关领域的小伙伴有所帮助。
GitHub Pages - RESEARCH INTERESTS
Yu Gu. 谷峪. Professor, Ph.D. Supervisor. College of Computer Science and Engineering, Northeastern University, Shenyang, China. Email: [email protected] Office: Room B215-1-2, Information Building, Northeastern University, China
37th SoCC 2024: Dresden, Germany - dblp
5 天之前 · 37th IEEE International System-on-Chip Conference, SOCC 2024, Dresden, Germany, September 16-19, 2024. IEEE 2024, ISBN 979-8-3503-7756-9
Song Li
国家重点研发计划项目首席科学家,入选中国科协青年人才托举工程。 博士毕业于美国约翰斯霍普金斯大学计算机科学学院。 主要研究方向为程序分析、漏洞挖掘、应用安全等。 在安全领域四大顶会(CCS、USENIX Security、NDSS,IEEE S&P),软件领域顶会ESEC/FSE等会议发表均有论文发表。 担任安全领域四大顶会IEEE S&P、USENIX Security、ACM CCS等国际顶尖学术会议的学术委员会委员。 主持国家基金委青年项目以及来自华为、阿里的多项项目。 主持开 …
Unsupervised Machine Learning for Responsible and Robust AI …
In this talk, I will present a comprehensive set of AI Observability solutions designed to detect model drift and perform root cause analysis using unsupervised machine learning techniques. These tools are essential for maintaining the health of AI systems, allowing teams to raise advance alerts before problems affect users.
Rui's Homepage - Department of Computer Science, Columbia …
In Proceedings of the ACM Symposium on Cloud Computing 2018(SOCC'18). OWL: Understanding and Detecting Concurrency Attacks Shixiong Zhao, Rui Gu , Haoran Qiu, Tsz On Li, Yuexuan Wang, Heming Cui, and Junfeng Yang
SHOWAR | Proceedings of the ACM Symposium on Cloud …
2021年11月1日 · Our experiments, using a variety of microservice applications and real-world workloads, show that, compared to the state-of-the-art autoscaling and scheduling systems, SHOWAR on average improves the resource allocation by up to 22% while improving the 99th percentile end-to-end user request latency by 20%. April, 01, 2021.
SoCC 论文解读:字节跳动如何在大规模集群中进行统一资源调度
2024年4月19日 · 字节跳动2023年在云计算顶会SoCC上发布的其自研在用的在生产级别离线混部系统Gödel,实践表明Gödel可以实现高达 5000 个 Pod/秒的吞吐量,同时在单个 Gödel 集群上保持约 60% 的总体资源利用率。