Computer Science Seminar

Friday, February 8, 2019 at 10:00am to 10:50am

Computer Science Building, 209
500 W. 15th St., Rolla, MO 65409

Efficient Algorithms for Modern and Future Architecture
Yan Gu, Department of Computer Science, Carnegie Mellon University

In today’s data-driven world with rapidly increasing data sizes, many new hardware technologies have been designed to store, process, and discover knowledge from ever-growing large-scale data. As a result, practically efficient algorithms on recent and future platforms must address the architectural concerns brought up by new hardware technologies. In this talk, I will introduce my research on two specific topics.
The first part focuses on future platforms for non-volatile main memories (NVMs) that have the special property that writes are more expensive than reads. This proposes the need for write-efficient algorithms that uses writes significantly fewer than classic approaches. In this talk, I will show how this challenge can be theoretically modeled, the new algorithms we proposed, and better experimental results.
The second part of this talk discusses the challenges in recent parallel algorithm design in the shared-memory setting. I will then introduce the new simple parallel algorithms that are efficient both theoretically and practically.
I will conclude the talk by sketching future image of computing and directions for algorithm design to accommodate such trends.
Bio: Yan Gu is a postdoctoral associate at MIT CSAIL. Prior to that, he received his PhD from Carnegie Mellon University in 2018 advised by Guy Blelloch, and Bachelor’s degree from Tsinghua University in 2012, both in Computer Science. His research designs theoretically-efficient algorithms with good performance in practice, with an emphasis on parallelism and future non-volatile main memories.

Event Type

Meetings, Lectures and Conferences

Departments

College of Engineering and Computing, Computer Science

Website

https://cs.mst.edu/studentopportuniti...

Contact Name

Dawn Davis

Contact Phone

5733416642

Contact Email

dawnd@mst.edu

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