Jialin Li

lijl at comp.nus.edu.sg

COM2 #03-16
15 Computing Drive
Singapore 117418

I am an Assistant Professor in the School of Computing at the National University of Singapore. Before joining NUS, I received my PhD from the University of Washington, working with Dan Ports, Arvind Krishnamurthy, and Tom Anderson. Before that, I received my bachelor's degree from the University of Michigan where I did some undergraduate research with Valeria Bertacco and Peter Chen.

I am broadly interested in operating systems and distributed systems research. More recently, I have worked on the following research topics: systems design for reconfigurable hardware, co-designing distributed systems with datacenter networks, and system software testing.

Publications

• Pegasus: Tolerating Skewed Workloads in Distributed Storage with In-Network Coherence Directories
  Jialin Li, Jacob Nelson, Ellis Michael, Xin Jin, and Dan R. K. Ports
  Proceedings of the 14th USENIX Symposium on Operating Systems Design and Implementation (OSDI '20) pdf

• Meerkat: Scalable Replicated Transactions Following the Zero-Coordination Principle
  Adriana Szekeres, Michael Whittaker, Naveen Kr. Sharma, Jialin Li, Arvind Krishnamurthy, Irene Zhang, and Dan R. K. Ports
  Proceedings of the 15th ACM SIGOPS EuroSys (EuroSys '20), Heraklion, Crete, Greece, April 2020 pdf

• Harmonia: Near-Linear Scalability for Replicated Storage with In-Network Conflict Detection
  Hang Zhu, Zhihao Bai, Jialin Li, Ellis Michael, Dan R. K. Ports, Ion Stoica, and Xin Jin
  Proceedings of the VLDB Endowment vol. 13 (3) , November 2019 (pp. 376--389) pdf

• Eris: Coordination-Free Consistent Transactions Using In-Network Concurrency Control
  Jialin Li, Ellis Michael, and Dan R. K. Ports
  Proceedings of the 26th Symposium on Operating Systems Principles (SOSP '17) pdf

• Just Say NO to Paxos Overhead: Replacing Consensus Overhead with Network Ordering
  Jialin Li, Ellis Michael, Naveen Kr. Sharma, Adriana Szekeres, and Dan R. K. Ports
  Proceedings of the 12th USENIX Symposium on Operating Systems Design and Implementation (OSDI '16) pdf

• Specifying and Checking File System Crash-consistency Models
  James Bornholt, Antoine Kaufmann, Jialin Li, Arvind Krishnamurthy, Emina Torlak, and Xi Wang
  Proceedings of the 21st International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS'16) pdf

• Arrakis: The Operating System Is the Control Plane
  Simon Peter, Jialin Li, Irene Zhang, Dan R. K. Ports, Doug Woos, Arvind Krishnamurthy, Thomas Anderson, and Timothy Roscoe
  ACM Transactions on Computer Systems vol. 33 (4) pdf

• Designing Distributed Systems Using Approximate Synchrony in Data Center Networks
  Dan R. K. Ports, Jialin Li, Vincent Liu, Naveen Kr. Sharma, and Arvind Krishnamurthy
  Proceedings of the 12th USENIX Symposium on Networked Systems Design and Implementation (NSDI '15) Best Paper Award pdf

• Tales of the Tail: Hardware, OS, and Application-level Sources of Tail Latency
  Jialin Li, Naveen Kr. Sharma, Dan R. K. Ports, and Steven D. Gribble
  Proceedings of the 5th Symposium on Cloud Computing (SOCC '14) pdf

• Arrakis: The Operating System is the Control Plane
  Simon Peter, Jialin Li, Irene Zhang, Dan R. K. Ports, Doug Woos, Arvind Krishnamurthy, Thomas Anderson, and Timothy Roscoe
  Proceedings of the 11th USENIX Symposium on Operating Systems Design and Implementation (OSDI '14) Best Paper Award pdf

• Towards High-Performance Application-Level Storage Management
  Simon Peter, Jialin Li, Doug Woos, Irene Zhang, Dan R. K. Ports, Thomas Anderson, Arvind Krishnamurthy, and Mark Zbikowski
  Proceedings of the 5th Hot Topics in Storage and File Systems (HotStorage '14) pdf

• Bridging Pre- and Post-silicon Debugging with BiPeD
  Andrew DeOrio, Jialin Li, and Valeria Bertacco
  Proceedings of the International Conference on Computer-Aided Design (ICCAD '12) pdf

Projects

• NOPaxos
  NOPaxos takes a new approach to achieving replication in the datacenter without the performance cost of traditional methods, by carefully dividing replication responsibility between the network and protocol layers. The network orders requests but does not ensure reliably delivery, using a new ordered unreliable multicast (OUM) primitive. Our new replication protocol, Network-Ordered Paxos (NOPaxos), exploits network ordering to provide strongly consistent replication without coordination. The resulting system yields throughput within 2% and latency within 16us of an unreplicated system.

• Eris
  Eris takes a different approach to strongly consistent distributed transactions. It moves a core piece of concurrency control functionality into the datacenter network. This network primitive takes on the responsibility for consistently ordering transactions, and a new lightweight transaction protocol ensures atomicity. The resulting system avoids both replication and transaction coordination overhead: it achieves performance within 3% of a non-transactional, unreplicated system on TPC-C.

• Speculative Paxos
  Speculative Paxos explores the co-design of distributed systems with their network layer. We leveraged properties of the datacenter network to build a Mostly-Ordered Multicast primitive which provides a best-effort ordering guarantee. We then co-designed a new replication protocol, Speculative Paxos, that relies on the network to order requests in the normal case. The resulting system provides substantially higher throughput and lower latency than the standard Paxos protocol.

• Arrakis
  Arrakis is a new operating system that eliminates the OS kernel entirely from fast-path I/O operations. The kernel only sets up execution environments and interacts with an application in rare cases where resources need to be reallocated or name conflicts need to be resolved. Applications get the full power of unmediated hardware through an application-specific library, providing significantly better performance, reliability and customizability.

• Predictable Tail-Latency Systems
  Modern datacenter applications struggle with the need to access thousands of servers while still providing a fast response time to the user. In this project, we conducted an extensive measurement study at the operating system level to identify factors that can cause lower-latency application to have orders of magnitude worse latency tail than the median. Using a set of modifications to the kernel scheduler, network stack, and application architecture, we can reduce the tail latency to within a few percent of optimal.