Notice

• Time : Jan. 14(Mon), 14:00~
• Location : 104 E101

Speaker : Seo Jin Park
Abstract
Since the advent of the Internet, applications have started using millions of people’s data which is beyond the capacity of a single machine. In response to the need for large-scale systems, the systems community focused on largely-scalable distributed systems, such as NoSQL storage. Unfortunately, the proposed solutions for scalability introduced two new challenges for applications: higher latency to access data (which limits the form of computation) and weak consistency (which makes systems harder to use).
In this talk, I will present my work on improving the latency and consistency of large-scale systems with the goal of enabling a new class of complex applications that operate on big data in real-time, such as social graph queries, online analytics, and machine learning. In pursuit of the goal, I fixed a widespread consistency problem in Remote Procedure Calls (RPC) by guaranteeing exactly-once execution (SOSP’15). In addition, my recent work, Consistent Unordered Replication Protocol (CURP), removed the overheads of strongly-consistent replication, which is another basic building block of distributed systems (NSDI’19).
 
Short-Bio
Seo Jin Park is a final year PhD student at Stanford University, advised with John Ousterhout. His research focus has been improving latency and consistency of large-scale distributed systems. He previously worked on a fast in-memory storage system (RAMCloud), and on a nanosecond-scale fast logging system (NanoLog). Before coming to Stanford for PhD, he previously received M.Eng. in EECS and B.S. in Computer Science and Mathematics from MIT in 2013.
 
Time : Jan. 14(Mon), 14:00~
Location : 104 E101