Program

Tutorials and Workshops

3/24

Time
7:00a-8:30p Breakfast
8:30a-10:00a Third Workshop on Cognitive Architectures (CogArch) 2nd Workshop on Hardware/Software Techniques for Minimizing Data Movement (Min-Move) Learning gem5 Tutorial (Gem5) BigDataBench: Big Data and AI Benchmarks (BigDataBench) Grand Challenges in Computer Systems Research (GrandChallenges)

*open to public

10:00a-10:30a Break
10:30a-12:00p Third Workshop on Cognitive Architectures (CogArch) 2nd Workshop on Hardware/Software Techniques for Minimizing Data Movement (Min-Move) Learning gem5 Tutorial (Gem5) BigDataBench: Big Data and AI Benchmarks (BigDataBench) Grand Challenges in Computer Systems Research (GrandChallenges)

*open to public

12:00p-1:30p Lunch (Provided)
1:30p-3:30p Third Workshop on Cognitive Architectures (CogArch) ReQuEST: Reproducible Quality-Efficient Systems Tournament (ReQuEST) Learning gem5 Tutorial (Gem5) Accelerating Big Data Processing and Associated Deep Learning on Data Centers and HPC Clouds with Modern Architectures (BigData-DeepLearning-HPC) OpenPiton in Action – A Hands-on Tutorial with the Open Source Manycore Processor (OpenPiton) Grand Challenges in Computer Systems Research (GrandChallenges)

*open to public

 3:30p-4:00p Break
4:00p- Third Workshop on Cognitive Architectures (CogArch) ReQuEST: Reproducible Quality-Efficient Systems Tournament (ReQuEST) Learning gem5 Tutorial (Gem5) Accelerating Big Data Processing and Associated Deep Learning on Data Centers and HPC Clouds with Modern Architectures (BigData-DeepLearning-HPC) OpenPiton in Action – A Hands-on Tutorial with the Open Source Manycore Processor (OpenPiton) Grand Challenges in Computer Systems Research (GrandChallenges)

*open to public

 

3/25

Time
7:00a-8:30p Breakfast
8:30a-10:00a The Ninth Workshop on Big Data Benchmark, Performance Optimization, and Emerging Hardware (BPOE-9) Workshop on Approximate Computing Across the Stack (WAX) The Software-Defined Data Computing and Storage (SDDCS) Workshop on Warehouse-scale Memory Systems (WAMS) Grand Challenges in Computer Systems Research
(GrandChallenges)*invitation only
The 14th ACM SIGPLAN/SIGOPS International Conference on Virtual Execution Environments (VEE)
10:00a-10:30a Break
10:30a-12:00p The Ninth Workshop on Big Data Benchmark, Performance Optimization, and Emerging Hardware (BPOE-9) Workshop on Approximate Computing Across the Stack (WAX) The Software-Defined Data Computing and Storage (SDDCS) Workshop on Warehouse-scale Memory Systems (WAMS) Grand Challenges in Computer Systems Research
(GrandChallenges)*invitation only
The 14th ACM SIGPLAN/SIGOPS International Conference on Virtual Execution Environments (VEE)
12:00p-1:30p Lunch (Provided)
1:30p-3:30p The Ninth Workshop on Big Data Benchmark, Performance Optimization, and Emerging Hardware (BPOE-9) Workshop on Approximate Computing Across the Stack (WAX) The Software-Defined Data Computing and Storage (SDDCS) Energy Efficient Machine Learning and Cognitive Computing for Embedded Applications (EMC2) Grand Challenges in Computer Systems Research (GrandChallenges)

* invitation only

The 14th ACM SIGPLAN/SIGOPS International Conference on Virtual Execution Environments (VEE)
 3:30p-4:00p Break
4:00p- The Ninth Workshop on Big Data Benchmark, Performance Optimization, and Emerging Hardware (BPOE-9) Workshop on Approximate Computing Across the Stack (WAX) The Software-Defined Data Computing and Storage (SDDCS) Energy Efficient Machine Learning and Cognitive Computing for Embedded Applications (EMC2) Grand Challenges in Computer Systems Research (GrandChallenges)

* invitation only

The 14th ACM SIGPLAN/SIGOPS International Conference on Virtual Execution Environments (VEE)

Main Program

3/25 (Sunday)

6:00p – 8:30p Reception & SRC Posters

3/26 (Monday)

Session 1 Session 2
7a-8:15a Breakfast
8:15a-8:30a Opening (GC/PC chairs)
8:30a-9:30a

Keynote 1: Hillery Hunter, IBM Fellow and Director, Accelerated Cognitive Infrastructure, IBM Research

Title: “AI productivity: Better hardware doesn’t work without better software”

Abstract:

The journey toward AI has been synergistically fueled by two key factors — availability of lots of data, and availability of lots of compute. Deep learning is one of the hottest areas of AI today and its success has been fueled by use of hardware accelerators, especially GPUs. Despite acceleration, the compute-intensity of deep learning training positions it as one of the few commercial areas of computing today where scientists wait for hours, days, even weeks to realize solutions to their optimization problems. We find in our work that many software packages and system implementations aren’t leveraging the full capability of today’s accelerators. Chip-System-Software co-design and co-optimization can result in dramatic efficiency improvements, and realize productivity gains for data scientists, freeing them up to focus on the fundamental science of deep learning — gaining accuracy, functionality, and generalizability of their models.

Bio:

Hillery Hunter is an IBM Fellow and Director of the Accelerated Cognitive Infrastructure group at IBM’s T.J. Watson Research Center in Yorktown Heights, NY.

She is interested in cross-disciplinary technology topics, spanning silicon to system architecture to achieve new solutions to traditional problems. Her team currently pursues hardware-software co-optimization to take the wait time out of machine and deep learning problems. Her prior work was in the areas of DRAM main memory systems and embedded DRAM, and she gaine development experience serving as IBM’s server and mainframe DDR3-generation end-to-end memory power lead. In 2010, she was selected by the National Academy of Engineering for its Frontiers in Engineering Symposium, a recognition as one of the top young engineers in America.

Dr. Hunter received the Ph.D. degree in Electrical Engineering from the University of Illinois, Urbana-Champaign and is a member of the IBM Academy of Technology. Hillery was appointed as an IBM Fellow in 2017.

9:30a-10:10a Lightning talks (20 talks)
10:10a-10:30a Break
10:30a-11:50a

New architectures
Chair: Josep Torrellas

In-MemoryData Parallel Processor

Daichi Fujiki (University of Michigan); Scott Mahlke (University of Michigan); Reetuparna Das (University of Michigan)

Hardware Multithreaded Transactions

Jordan Fix (Princeton University); Nayana P. Nagendra (Princeton University); Sotiris Apostolakis (Princeton University); Hansen Zhang (Princeton University); Sophie Qiu (Princeton University); David I. August (Princeton University)

Blasting Through The Front-End Bottleneck With Shotgun

Rakesh Kumar (Uppsala University, Sweden); Boris Grot (University of Edinburgh, UK); Vijay Nagarajan (University of Edinburgh, UK)

SlimNoC: A Low-Diameter On-Chip Network Topology for High Energy-Efficiency and Scalability

Maciej Besta (ETH Zurich); Syed Minhaj Hassan (Georgia Tech); Sudhakar Yalamanchili (Georgia Tech); Rachata Ausavarungnirun (CMU); Onur Mutlu (ETH Zurich); Torsten Hoefler (ETH Zurich)

Managed runtimes and dynamic translation
Chair: Lei Liu

Skyway: Connecting Managed Heaps in Distributed Big Data Systems

Khanh Nguyen (University of California, Irvine); Lu Fang (Facebook); Christian Navasca (University of California, Irvine);  Guoqing Harry Xu (University of California, Irvine); Brian Demsky (University of California, Irvine); Shan Lu (University of Chicago)

Espresso: Brewing Java For More Non-Volatility

Mingyu Wu (Shanghai Jiao Tong University); Ziming Zhao (Shanghai Jiao Tong University); Haoyu Li (Shanghai Jiao Tong University); Heting Li (Shanghai Jiao Tong University); Haibo Chen (Shanghai Jiao Tong University); Binyu Zang (Shanghai Jiao Tong University); Haibing Guan (Shanghai Jiao Tong University)

Enhancing Cross-ISA DBT Through Automatically Learned Translation Rules

Wenwen Wang (University of Minnesota at Twin Cities); Pen-Chung Yew (University of Minnesota at Twin Cities); Stephen McCamant (University of Minnesota at Twin Cities); Antonia Zhai (University of Minnesota at Twin Cities)

Gloss: Seamless Live Reconfiguration and Reoptimization of Stream Programs

Sumanaruban Rajadurai (National University of Singapore); Jeffrey Bosboom (MIT CSAIL); Weng-Fai Wong (National University of Singapore); Saman Amarasinghe (MIT CSAIL)

11:50a-1:00p Lunch
1:00p-2:00p

GPUs 1
Chair:Christopher J. Rossbach

Filtering Translation Bandwidth with Virtual Caching

Hongil Yoon (University of Wisconsin-Madison); Jason Lowe-Power (University of California, Davis); Gurindar S. Sohi (University of Wisconsin-Madison)

Automatic Hierarchical Parallelization of Linear Recurrences

Sepideh Maleki (Texas State University); Martin Burtscher (Texas State University)

Automatic matching of legacy code to heterogeneous APIs: An idiomatic approach

Philip Ginsbach (The University of Edinburgh); Toomas Remmelg (The University of Edinburgh); Michel Steuwer (University of Glasgow); Bruno Bodin (The University of Edinburgh); Christophe Dubach (The University of Edinburgh); Michael F. P. O’Boyle (The University of Edinburgh)

Performance management
Chair: James Larus

Understanding and Auto-Adjusting Performance-Sensitive Configurations

Shu Wang (University of Chicago); Chi Li (University of Chicago); William Sentosa (Bandung Institute of Technology); Henry Hoffmann (University of Chicago); Shan Lu (University of Chicago); Achmad Imam Kistijantoro (Bandung Institute of Technology)

SPECTR: Formal Supervisory Control and Coordination for Many-core Systems Resource Management

Amir M. Rahmani (University of California, Irvine and TU Wien); Bryan Donyanavard (University of California, Irvine); Tiago Mück (University of California, Irvine); Kasra Moazzemi (University of California, Irvine); Axel Jantsch (TU Wien); Onur Mutlu (ETH Zürich); Nikil Dutt (University of California, Irvine)

CALOREE: Learning Control for Predictable Latency and Low Energy
Nikita Mishra (University of Chicago); Connor Imes (University of Chicago); John D Lafferty (Yale); Henry Hoffmann (University of Chicago)

2:00p-2:20p Break
2:20p-3:20p

Programmable devices and co-processors
Chair: Satish Narayanasamy

Darwin: A Genomics Co-processor provides up to 15,000X acceleration on long read assembly

Yatish Turakhia (Stanford University); Gill Bejerano (Stanford University); William J. Dally (Stanford University)

Liquid Silicon: A Reconfigurable Memory-Oriented Computing Fabric with Scalable Multi-Context Support

Yue Zha (University of Wisconsin Madison); Jing Li (University of Wisconsin Madison)

Time Dilation and Contraction for Programmable Analog Devices with Jaunt

Sara Achour (MIT); Martin Rinard (MIT)

Mobile applications
Chair: Dongyoon Lee

Exploiting Dynamical Thermal Energy Harvesting for Reusing in Smartphone with Mobile Applications

Yuting Dai (College of Computer Science & Technology, Guizhou University); Tao Li (University of Florida); Benyong Liu (Guizhou University); Mingcong Song (University of Florida)

Static Detection of Event-based Races in Android Apps

Yongjian Hu (University of California, Riverside); Iulian Neamtiu (New Jersey Institute of Technology)

 
Potluck: Cross-application Approximate Deduplication for Computation-Intensive Mobile Applications

Peizhen Guo (Yale university); Wenjun Hu (Yale university)

3:20p-3:40p Break
3:40p-5:30p Posters SRC talks (until 4:40pm)
5:30p-7:00p Wild and crazy ideas
7:00p-8:00p Business meeting
8:00p- End of day

3/27  (Tuesday)

Session 1 Session 2
7a-8:15a Breakfast
8:15a-8:30a Opening (GC/PC chairs)
8:30a-9:30a

Keynote 2: Fred Chong, Seymour Goodman Professor of Computer Architecture,
University of Chicago

Title: “Quantum Computing is Getting Real: Architecture, PL, and OS roles in Closing the Gap between Quantum Algorithms and Machines”

Abstract:

Quantum computing is at an inflection point, where 50-qubit (quantum bit) machines have been built, 100-qubit machines are just around the corner, and even 1000-qubit machines are perhaps only a few years away.  These machines have the potential to fundamentally change our concept of what is computable and demonstrate practical applications in areas such as quantum chemistry, optimization, and quantum simulation.

Yet a significant resource gap remains between practical quantum algorithms and real machines.  There is an urgent shortage of the necessary computer scientists to work on software and architectures to close this gap.

I will outline several grand research challenges in closing this gap, including programming language design, software and hardware verification, defining and perforating abstraction boundaries, cross-layer optimization, managing parallelism and communication, mapping and scheduling computations, reducing control complexity, machine-specific optimizations, learning error patterns, and many more. I will also describe the resources and infrastructure available for starting research in quantum computing and for tackling these challenges.

Bio:

Fred Chong is the Seymour Goodman Professor in the Department of Computer Science at the University of Chicago. Chong received his Ph.D. from MIT in 1996 and was a faculty member and Chancellor’s fellow at UC Davis from 1997-2005. He was also a Professor of Computer Science, Director of Computer Engineering, and Director of the Greenscale Center for Energy-Efficient Computing at UCSB from 2005-2015. He is a recipient of the NSF CAREER award and 6 best paper awards. His research interests include emerging technologies for computing, quantum computing, multicore and embedded architectures, computer security, and sustainable computing.

9:30a-10:10a Lightning talks (20 talks)
10:10a-10:30a Break
10:30a-11:50a

Memory 1
Chair: Dan Tsafrir

SOFRITAS: Serializable Ordering-Free Regions for Increasing Thread Atomicity Scalably

Christian DeLozier (University of Pennsylvania); Ariel Eizenberg (University of Pennsylvania); Brandon Lucia (Carnegie Mellon University); Joseph Devietti (University of Pennsylvania)

DAMN: Overhead-Free IOMMU Protection for Networking

Alex Markuze (Technion); Igor Smolyar (Technion); Adam Morrison (Tel Aviv University); Dan Tsafrir (Technion & VMware Research)

Processing In-Memory for Google Consumer Workloads

Amirali Boroumand (Carnegie Mellon University); Saughata Ghose (Carnegie Mellon University); Youngsok Kim (Seoul National University); Rachata Ausavarungnirun (Carnegie Mellon University); Rahul Thakur (Google); Eric Shiu (Google); Allan Knies (Google); Aki Kuusela (Google); Daehyun Kim (Google); Parthasarathy Ranganathan (Google); Onur Mutlu (ETH Zurich, Carnegie Mellon University)

Watching for Software Inefficiencies with WITCH

Shasha Wen (College of William and Mary); Xu Liu (College of William and Mary); John Byrne (Hewlett Packard Labs); Milind Chabbi (Hewlett Packard Labs)

Program analysis
Chair: Shan Lu

Fast, Sound Dynamic Analysis through Predicated Static Analysis and Speculative Execution

David Devecsery (University of Michigan); Peter M. Chen (University of Michigan); Satish Narayanasamy (University of Michigan); Jason Flinn (University of Michigan)

Statistical Reconstruction of Class Hierarchies in Binaries

Omer Katz (Technion); Noam Rinetzky (Tel Aviv University); Eran Yahav (Technion)

Sulong, and Thanks For All the Bugs: Finding Errors in C Programs by Abstracting from the Native Execution Model

Manuel Rigger (Johannes Kepler University Linz, Austria) ; Roland Schatz (Oracle Labs, Austria); Rene Mayrhofer (Johannes Kepler University Linz, Austria); Matthias Grimmer (Oracle Labs, Austria); Hanspeter Mössenböck (Johannes Kepler University Linz, Austria)

FirmUp: Precise Static Detection of Common Vulnerabilities in Firmware

Yaniv David (Technion); Nimrod Partush (Technion); Eran Yahav (Technion)

11:50a-1:00p Lunch
1:00p-2:00p

Concurrency and parallelism
Chair: Hank Hoffmann

Frightening small children and disconcerting grown-ups: Concurrency in the Linux kernel

Jade Alglave (University College London); Luc Maranget (INRIA); Paul E. McKenney (IBM Corporation); Andrea Parri (Scuola Superiore Sant’Anna); Alan Stern (Harvard University)

FCatch: Automatically detecting time-of-fault bugs in cloud systems

Haopeng Liu (University of Chicago); Xu Wang (Beihang University); Guangpu Li (University of Chicago); Shan Lu (University of Chicago); Feng Ye (Huawei US R&D Center); Chen Tian (Huawei US R&D Center)

Unconventional Parallelization of Nondeterministic Applications

Enrico Armenio Deiana (Northwestern University); Vincent St-Amour (Northwestern University); Peter Dinda (Northwestern University); Nikos Hardavellas (Northwestern University); Simone Campanoni (Northwestern University)

 

Neural networks
Chair: Adrian Sampson

Bridging the Gap Between Neural Networks and Neuromorphic Hardware with A Neural Network Compiler

Yu Ji (Tsinghua University); YouHui Zhang (Tsinghua University); WenGuang Chen (Tsinghua University); Yuan Xie (UCSB)

MAERI: Enabling Flexible Dataflow Mapping over DNN Accelerators via Reconfigurable Interconnects

Hyoukjun Kwon (Georgia Institute of Technology); Ananda Samajdar (Georgia Institute of Technology); Tushar Krishna (Georgia Institute of Technology)

VIBNN: Hardware Acceleration of Bayesian Neural Networks

Ruizhe Cai (Syracuse University); Ao Ren (Syracuse University); Ning Liu (Syracuse University); Caiwen Ding (Syracuse University); Luhao Wang (University of Southern California); Xuehai Qian (University of Southern California); Massoud Pedram (University of Southern California); Yanzhi Wang (Syracuse University)

2:00p-3:00p

GPU 2
Chair: Jayneel Gandhi

LTRF: A Latency Tolerant Register File Architecture for GPUs

Mohammad Sadrosadati (ETH Zurich, Sharif University of Technology); Amirhossein Mirhosseini (University of Michigan); Borna Ehsani (Karlsruhe Institute of Technology, Sharif University of Technology); Hamid Sarbazi-Azad (Sharif University of Technology, IPM); Mario Paulo Drumond (EPFL); Babak Falsafi (EPFL); Rachata Ausavarungnirun (CMU); Onur Mutlu (ETH Zurich, CMU)

Redesigning the GPU Memory Hierarchy to Support Multi-Application Concurrency

Rachata Ausavarungnirun (Carnegie Mellon University); Vance Miller (UT Austin); Joshua Landgraf (UT Austin); Saugata Ghose (Carnegie Mellon University); Jayneel Gandhi (VMware Research Group); Adwait Jog (College of William and Mary); Chris Rossbach (UT Austin and VMware Research Group); Onur Mutlu (ETH Zurich and Carnegie Mellon University)

Sugar: Secure GPU Acceleration in Web Browsers

Zhihao Yao (UC Irvine); Zongheng Ma (UC Irvine); Ardalan Amiri Sani (UC Irvine); Aparna Chandramowlishwaran (UC Irvine)

Datacenters
Chair: John Carter

SmoothOperator: Combating Power Fragmentation and Improving Power Utilization in Large-scale Datacenters

Chang-Hong Hsu (University of Michigan, Ann Arbor); Qingyuan Deng (Facebook, Inc.); Jason Mars (University of Michigan, Ann Arbor); Lingjia Tang (University of Michigan, Ann Arbor)

WSMeter: A Performance Evaluation Methodology for Google’s Production Warehouse-Scale Computers

Jaewon Lee (Seoul National University)
Changkyu Kim (Google)
Kun Lin (Google)
Liqun Cheng (Google)
Rama Govindaraju (Google)
Jangwoo Kim (Seoul National University)

DAC: Data-Aware Auto-Tuning High Dimensional Configurations of In-memory Cluster Computing

Zhibin Yu (Shenzhen Institute of Advanced Technology, Chinese Academy of Science); Zhendong Bei (Shenzhen Institute of Advanced Technology, Chinese Academy of Science); Xuehai Qian (University of Southern California)

3:00p-7:00p Excursion
7:00p-9:00p Banquet with Dean Shostak’s Crystal Concert
9:00p- End of day

3/28 (Wednesday)

Session 1 Session 2
7a-8:30a Breakfast
8:30a-9:00a Lightning talks (16 talks)
9:00a-10:20a

Irregular apps and graphs
Chair: Martha Kim

An Event-Triggered Programmable Prefetcher for Irregular Workloads

Sam Ainsworth (University of Cambridge); Timothy M. Jones (University of Cambridge)

Minnow: Slipstreaming General-Purpose Cores on Parallel Worklist-based Irregular Applications

Dan Zhang (The University of Texas at Austin); Xiaoyu Ma (Google); Michael Thomson (The University of Texas at Austin); Derek Chiou (Microsoft)

Wonderland: A Novel Abstraction-Based Out-Of-Core Graph Processing System

Mingxing Zhang (Tsinghua University); Yongwei Wu (Tsinghua University); Youwei Zhuo (University of Southern California); Xuehai Qian (University of Southern California); Chenyin Huan (Tsinghua University); Kang Chen (Tsinghua University)

Transforming Irregular Graphs for GPU-Friendly Graph Processing

Amir Sabet (University of California, Riverside); Junqiao Qiu (University of California, Riverside); Zhijia Zhao (University of California, Riverside)

 

Memory 2
Chair: Steve Blackburn

Devirtualizing virtual memory for heterogeneous systems

Swapnil Haria (University of Wisconsin-Madison); Mark D. Hill (University of Wisconsin-Madison); Mike M. Swift (University of Wisconsin-Madison)

LATR: Lazy Translation Coherence

Mohan Kumar (Georgia Institute of Technology); Steffen Maass (Georgia Institute of Technology); Sanidhya Kashyap (Georgia Institute of Technology); Jan Vesely (Rutgers University); Zi Yan (Rutgers University); Taesoo Kim (Georgia Institute of Technology); Abhishek Bhattacharjee (Rutgers University); Tushar Krishna (Georgia Institute of Technology)

Reducing Paging Overheads in SGX with Efficient Integrity Verification Structures

Meysam Taassori (University of Utah); Ali shafiee (University of Utah); Rajeev Balasubramonian (University of Utah)

Making Huge Pages Actually Useful

Ashish Panwar (Indian Institute of Science); Aravinda Prasad (Indian Institute of Science); K Gopinath (Indian Institute of Science)

 

10:20a-10:40a Break
10:40a-12:00p

Security and protection
Chair: John Criswell

BranchScope: A New Side-Channel Attack on Directional Branch Predictor

Dmitry Evtyushkin (College of William and Mary); Ryan Riley (CMU Qatar); Nael Abu-Ghazaleh (UC Riverside); Dmitry Ponomarev (Binghamton University)

StrongBox: Confidentiality, Integrity, and Performance using Stream Ciphers for Full Drive Encryption

Bernard Dickens III (University of Chicago); Haryadi S. Gunawi (University of Chicago); Ariel J. Feldman (University of Chicago); Henry Hoffmann (University of Chicago)

DATS – Refactoring Access Control Out of Web Applications

Lluis Vilanova (Technion); Casen Hunger (UT Austin); Charalampos Papamanthou (UMD); Yoav Etsion (Technion); Mohit Tiwari (UT Austin)

DLibOS: Performance and Protection with a Network-on-Chip

Stephen Mallon (University of Sydney); Vincent Gramoli (University of Sydney/Data61-CSIRO); Guillaume Jourjon (Data61-CSIRO)

 

Potpourri
Chair: Yan Solihin

The Architectural Implications of Autonomous Driving: Constraints and Acceleration

Shih-Chieh Lin (University of Michigan, Ann Arbor); Yunqi Zhang (University of Michigan, Ann Arbor); Chang-Hong Hsu (University of Michigan, Ann Arbor); Matt Skach (University of Michigan, Ann Arbor); Md E. Haque (University of Michigan, Ann Arbor); Lingjia Tang (University of Michigan, Ann Arbor); Jason Mars (University of Michigan, Ann Arbor)

A Reconfigurable Energy Storage Architecture for Energy-harvesting Devices

Alexei Colin (Carnegie Mellon University); Emily Ruppel (Carnegie Mellon University); Brandon Lucia (Carnegie Mellon University)

NEOFog: Nonvolatility-Exploiting Optimizations for Fog Computing

Kaisheng Ma (Penn State); Jinyang Li (Tsinghua University); Tongda Wu (Tsinghua University); Zhibo Wang (Tsinghua University); Xueqing Li (Penn State); Yongpan Liu (Tsinghua University); Yuan Xie (UCSB); Mahmut Taylan Kandemir (Penn State); Jack Sampson (Penn State); Vijaykrishnan Narayanan (Penn State)

vbench: Benchmarking Video Transcoding in the Cloud

Andrea Lottarini (Columbia University); Alex Ramirez (Google Inc.); Joel Coburn (Google Inc.); Martha A. Kim (Columbia University); Parthasarathy Ranganathan (Google Inc.); Daniel Stodolsky (Google Inc.); Mark Wachsler (Google Inc.)

12:00p-12:10p Closing remarks
12:10p- End of conference