Cornell Systems Lunch

CS 7490 Spring 2015
Friday 12PM, Gates 114

Emin Gun Sirer and Robbert van Renesse


Sponsored by Microsoft

The Systems Lunch is a seminar for discussing recent, interesting papers in the systems area, broadly defined to span operating systems, distributed systems, networking, architecture, databases, and programming languages. The goal is to foster technical discussions among the Cornell systems research community. We meet once a week on Fridays at noon in Gates 114.

The systems lunch is open to all Cornell Ph.D. students interested in systems. First-year graduate students are especially welcome. Non-Ph.D. students have to obtain permission from the instructor. Student participants are expected to sign up for CS 7490, Systems Research Seminar, for one credit.

To join the systems lunch mailing list please send an empty message to cs-systems-lunch-l-request@cornell.edu with the subject line "join". More detailed instructions can be found here.

Links to papers and abstracts below are unlikely to work outside the Cornell CS firewall. If you have trouble viewing them, this is the likely cause.

Other semesters:

fall 19 spring 20
fall 18 spring 19
fall 17 spring 18
fall 16 spring 17
fall 15 spring 16
fall 14 spring 15
fall 13 spring 14
fall 12 spring 13
fall 11 spring 12
fall 10 spring 11
fall 09 spring 10
fall 08 spring 09
fall 07 spring 08
fall 06 spring 07
fall 05 spring 06
fall 04 spring 05
fall 03 spring 04
fall 02 spring 03
fall 01 spring 02
Date Paper Presenter
January 23 Scalable Error Isolation for Distributed Systems
Marco Serafini
NSDI 2015 		Marco Serafini (QCRI)
January 30 A Self-Configurable Geo-Replicated Cloud Storage System
Ardekani and Terry
OSDI 2014 		Tom Magrino
February 6 Targeted Resource Management in Multi-Tenant Distributed Systems
Rodrigo Fonseca
Host: Hakim Weatherspoon 		Rodrigo Fonseca (Brown)
February 13 Bitcoin, Ethereum and Beyond: An introduction to the workings and unsolved problems of cryptocurrency

Host: Ittay Eyal 		Vitalik Buterin (Ethereum)
February 20 Jitk: A Trustworthy In-Kernel Interpreter Infrastructure
Xi Wang, David Lazar, Nickolai Zeldovich, Adam Chlipala, Zachary Tatlock
OSDI 2014 		Laure Thompson
February 27

Host: Nate Foster 		Andreas Haeberlean (UPENN)
March 6 CosTLO: Cost-Effective Redundancy for Lower Latency Variance on CloudStorage Services
Zhe Wu, Curtis Yu, and Harsha V. Madhyastha
NSDI 2015 		Qin Jia
March 13 Warranties for Faster Strong Consistency
Jed Liu. Tom Magrino. Owen Arden. Michael D. George. Andrew C. Myers
NSDI 2014 		Jed Liu
March 20 Willow: A User-Programmable SSD
Sudharsan Seshadri, Mark Gahagan, Sundaram Bhaskaran, Trevor Bunker, Arup De, Yanqin Jin, Yang Liu, and Steven Swanson, University of California, San Diego
OSDI 2014 		Kai Mast
March 27 Understanding Optimal Caching and Opportunistic Caching at The Edge of Information-Centric Networks

ICN 2014 		Colin Ponce
Networking Named Content

SIGCOMM 2009 		Colin Ponce
April 3 Spring Break, no meeting.
April 10 ACSU Luncheon—no systems lunch, no meeting.
April 17 Advanced Sports Monitoring

Host: Fred Schneider 		Dag Johansen (Univ. of Tromso and Forzasys)
April 24 Physical Disentanglement in a Container-Based File System
Lanyue Lu, Yupu Zhang, Thanh Do, Samer Al-Kiswany, Andrea C. Arpaci-Dusseau, Remzi H. Arpaci-Dusseau
OSDI 2014 		Jiyong Shin
May 1 Operating System Support for High-throughput Accelerators

Future applications will need to use programmable parallel accelerators like GPUs to achieve their performance and power goals. However building efficient systems that use accelerators today is incredibly difficult.

In this talk I will argue that the root cause for this complexity is the lack of adequate operating system support for programs running on accelerators. I will describe our experience in building native file system (GPUfs) and networking (GPUnet) layers for GPUs. These layers expose well-understood standard I/O abstractions like files and sockets to programs running on GPUs, and are designed to accommodate massive parallelism, extreme NUMA and weak memory consistency of the underlying hardware.

GPUfs and GPUnet break the constrained GPU-as-coprocessor model and streamline the development of high-performance, distributed applications like in-GPU-memory MapReduce and a new class of low-latency, high-throughput GPU-native network services such as a face verification server.

Joint work with Emmett Witchel, Bryan Ford, Idit Keidar, and UT Austin and Technion students.

Mark Silberstein (Technion)