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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<title>李权熹 (Quanxi Li) - Personal Homepage</title>
</head>
<style>
body {
display: flex;
flex-direction: column;
min-height: 100vh;
margin: 0;
}
main {
flex-grow: 1;
}
footer {
background-color: #f8f9fa;
text-align: center;
padding: 1rem;
border-top: 1px solid #e7e7e7;
}
</style>
<body>
<header>
<h1>李权熹 (Quanxi Li)</h1>
<p>Email: [email protected]</p>
</header>
<nav>
<ul>
<li><a href="#about">About Me</a></li>
<li><a href="#research">Research Interests</a></li>
<li><a href="#publications">Publications</a></li>
</ul>
</nav>
<main>
<section id="about">
<h2>About Me</h2>
<p>
I am a PhD Candidate at
<a href="https://www.ict.ac.cn">
the Institute of Computing Technology, Chinese Academy of Sciences (ICT, CAS)
</a>
co-advised by
<a href="http://www.carch.ac.cn/yjdw/yjy/201906/t20190628_497172.html">Dr. Xiaobing Feng (冯晓兵)</a>
and
<a href="https://wangchenxi7.github.io/home/">Dr. Chenxi Wang (王晨曦)</a>.
I got my Bachelor degree from
<a href="https://www.ustc.edu.cn/">University of Science and Technology of China (USTC)</a>
in 2020.
</p>
</section>
<section id="research">
<h2>Research Interests</h2>
My research focuses on the development of hard-core systems tailored for emerging hardware
platforms, such as resource-disaggregated datacenter.
I am particularly interested in enhancing the performance of applications on these systems through the
design and implementation of advanced programming models and compiler optimizations.
<h3>Runtime for Disaggregated Memory</h3>
As an emerging datacenter architecture, resource-disaggregation aims to reorganize datacenter hardware of
each kind into their dedicated resource servers to improve resource utilization and fault tolerance and
simplify hardware adoption. These servers are connected by advanced network fabrics a such as Infiniband and
Intel Fabrics. As a result, the cloud application running on the resource-disaggregated cluster can get
compute and memory resources from different servers.
<br>
I build a memory-disaggregated framework, Beehive, which improves the remote access throughput by
exploiting the asynchrony within each thread. Beehive is capable of automatically converting applications
into asynchronous execution code, which helps to reduce the microsecond-scale latency associated with remote
memory access. This is achieved while maintaining low CPU overhead and enhancing data locality, leading to
more efficient application performance.
</section>
<section id="publications">
<h2>Publications</h2>
<ul>
<li>
<a href="">
Beehive: A Scalable Disaggregated Memory Runtime Exploiting Asynchrony of Multithreaded Programs
</a>
<br>
by <b>Quanxi Li</b>, Hong Huang, Ying Liu, Yanwen Xia, Jie Zhang, Mosong Zhou, Xiaobing Feng, Huimin
Cui, Quan Chen, Yizhou Shan, Chenxi Wang*
<br>
The 22nd USENIX Symposium on Networked Systems Design and Implementation (NSDI), 2025
</li>
<li>
<a href="https://ieeexplore.ieee.org/abstract/document/9218561">
Codar: A Contextual Duration-Aware Qubit Mapping for Various NISQ Devices
</a>
<br>
by Haowei Deng, Yu Zhang*, <b>Quanxi Li</b>
<br>
The 57th ACM/IEEE Design Automation Conference (DAC), 2020
</li>
<li>
<a href="https://ieeexplore.ieee.org/abstract/document/8914134">
Optimizing quantum programs against decoherence: Delaying qubits into quantum superposition
</a>
<br>
by Yu Zhang*, Haowei Deng, <b>Quanxi Li</b>, Haoze Song and Leihai Nie
<br>
The 2019 International Symposium on Theoretical Aspects of Software Engineering (TASE), 2019
</li>
</ul>
</section>
</main>
<footer>
<p>© 2024 李权熹 (Quanxi Li). All rights reserved.</p>
</footer>
</body>
</html>