March 2016 - talks - lists.cs.princeton.edu

Colloquium Speaker: Mayank Goel Today 12:30pm
by Nicole E. Wagenblast 25 Mar '16

25 Mar '16

Colloquium Speaker Mayank Goel , University of Washington Friday, March 25, 2016 - 12:30pm Computer Science 105 Teaching Old Sensors New Tricks A fundamental issue with any new sensing technology is the deployment burden. The new technology often comes with a rigid and perhaps expensive list of pre-requisites; and it affects the overall cost-effectiveness, deployability, and accessibility of the solution. For example, a user might find it hard to buy and carry a medical device with them everyday. The primary theme of my Ph.D. research has been to reduce the adoption and deployment barriers of new sensing technologies by using the sensors that are already around us. In this talk, I will present my research on extending the capabilities of the on-board sensors on consumer devices for various applications. First, I will discuss how we can leverage the on-device sensors to enable novel human-computer interactions and make the mobile devices more usable. Next, I will discuss my work on using the on-device sensors for building health technologies that work as well as their clinically-approved counterparts and they continue to evolve through deployments in various parts of the world. Finally, I will discuss how my recent work in extending the on-device sensors is shaping my future interests and how I plan to continue to lower the adoption barriers for new sensing technologies. Mayank Goel is a Ph.D. candidate in Computer Science and Engineering in the Ubiquitous Computing (UbiComp) Lab at the University of Washington, advised by Shwetak Patel and Gaetano Borriello. His research focuses on building sensing systems to solve hard problems in diverse application areas, ranging from health sensing, technologies for the developing world to novel user interaction; with an eye toward reducing deployment barriers. His research in the area of health technologies is currently used by hundreds of patients every week, around the world. He was awarded the Microsoft Research Ph.D. Fellowship in 2014, a University of Washington CSE Fellowship, and 7 Best Paper Nominations. He received an M.S. in Computer Science from Georgia Institute of Technology in 2009, where he was advised by Gregory Abowd and specialized in mobile and ubiquitous computing.

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Colloquium Speaker: Joel Tropp, Tuesday, March 29- 12:30pm
by Nicole E. Wagenblast 24 Mar '16

24 Mar '16

Colloquium Speaker Joel Tropp, California Institute of Technology Tuesday, March 29, 12:30pm Computer Science 105 Universality laws for randomized dimension reduction Dimension reduction is the process of embedding high-dimensional data into a lower dimensional space to facilitate its analysis. In the Euclidean setting, one fundamental technique for dimension reduction is to apply a random linear map to the data. The question is how large the embedding dimension must be to ensure that randomized dimension reduction succeeds with high probability. This talk describes a phase transition in the behavior of the dimension reduction map as the embedding dimension increases. The location of this phase transition is universal for a large class of datasets and random dimension reduction maps. Furthermore, the stability properties of randomized dimension reduction are also universal. These results have many applications in numerical analysis, signal processing, and statistics. Joint work with Samet Oymak.

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Colloquium Speaker Stefanie Mueller, Monday March 28th, 12:30pm
by Mitra D. Kelly 24 Mar '16

24 Mar '16

Colloquium Speaker Stefanie Mueller, Human-Computer Interaction Lab at Hasso Plattner Institute Monday March 28th, 12:30pm Computer Science 105 Talk Title: Interacting with Personal Fabrication Machines Abstract: In anticipation of 3D printers reaching millions of users, I am investigating how to allow future users to interact with the new hardware. I present a series of interactive software+hardware systems that I created to answer this question. They are characterized by two main properties. First, they produce physical output quickly, allowing users not only to see their results, but also to touch and test their mechanical properties as users work towards a solution. Second, the systems allow users to interact directly with the workpiece, i.e., rather than using a digital 3D editor, users manipulate the workpiece located inside the 3D printer by pointing at it, causing the machine to then modify the workpiece accordingly. I put my research into perspective by drawing analogies to the evolution of interactive computing from batch processing, to turn taking, to direct manipulation. Bio: Stefanie Mueller is a PhD student working with Patrick Baudisch at the Human-Computer Interaction Lab at Hasso Plattner Institute. In her research, she develops novel hardware and software systems that advance personal fabrication technologies. Stefanie has published 10 papers at the most selective HCI venues CHI and UIST, for which she received a best paper award and two best paper nominees. She is also serving on the CHI and UIST program committees as an associate chair. In addition, Stefanie has been an invited speaker at universities and research labs, such as MIT, Stanford, UC Berkeley, Microsoft Research, Disney Research, and Adobe Research. Mitra Kelly Academic Secretary Princeton University Computer Science Dept 35 Olden Street Princeton NJ 08540 mkelly(a)cs.princeton.edu <mailto:mkelly@cs.princeton.edu> 609-258-4562

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Colloquium Speaker: Mayank Goel Friday, March 25- 12:30pm
by Nicole E. Wagenblast 24 Mar '16

24 Mar '16

Colloquium Speaker Mayank Goel , University of Washington Friday, March 25, 2016 - 12:30pm Computer Science 105 Teaching Old Sensors New Tricks A fundamental issue with any new sensing technology is the deployment burden. The new technology often comes with a rigid and perhaps expensive list of pre-requisites; and it affects the overall cost-effectiveness, deployability, and accessibility of the solution. For example, a user might find it hard to buy and carry a medical device with them everyday. The primary theme of my Ph.D. research has been to reduce the adoption and deployment barriers of new sensing technologies by using the sensors that are already around us. In this talk, I will present my research on extending the capabilities of the on-board sensors on consumer devices for various applications. First, I will discuss how we can leverage the on-device sensors to enable novel human-computer interactions and make the mobile devices more usable. Next, I will discuss my work on using the on-device sensors for building health technologies that work as well as their clinically-approved counterparts and they continue to evolve through deployments in various parts of the world. Finally, I will discuss how my recent work in extending the on-device sensors is shaping my future interests and how I plan to continue to lower the adoption barriers for new sensing technologies. Mayank Goel is a Ph.D. candidate in Computer Science and Engineering in the Ubiquitous Computing (UbiComp) Lab at the University of Washington, advised by Shwetak Patel and Gaetano Borriello. His research focuses on building sensing systems to solve hard problems in diverse application areas, ranging from health sensing, technologies for the developing world to novel user interaction; with an eye toward reducing deployment barriers. His research in the area of health technologies is currently used by hundreds of patients every week, around the world. He was awarded the Microsoft Research Ph.D. Fellowship in 2014, a University of Washington CSE Fellowship, and 7 Best Paper Nominations. He received an M.S. in Computer Science from Georgia Institute of Technology in 2009, where he was advised by Gregory Abowd and specialized in mobile and ubiquitous computing.

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Colloquium Speaker: Adam Belay, Today- 12:30pm
by Nicole E. Wagenblast 24 Mar '16

24 Mar '16

Colloquium Speaker Adam Belay, Stanford University Thursday, March 24, 12:30pm Computer Science 105 Unleashing Hardware Potential through Better OS Abstractions Datacenter workloads have demanding performance requirements, including the simultaneous need for high throughput, low tail latency, and high server utilization. While modern hardware is compatible with these goals, modern operating systems remain a bottleneck. Better OS abstractions could significantly improve performance, yet deploying these abstractions has become intractable given the size and complexity of today's systems. I will first discuss Dune, a kernel extension that allows OS developers to sidestep software and hardware complexity by running an OS within an ordinary Linux process. With Dune, developers can both access the capabilities of raw hardware and fall back on the functionality of a full Linux environment where convenient. I will then discuss IX and Shinjuku, two generations of new datacenter-focused operating systems that were enabled by Dune. IX provides a novel system call interface that greatly improves network throughput without sacrificing latency. For example, IX improves Memcached's TCP throughput by 5x over Linux. Shinjuku, an ongoing research effort, aims to significantly increase CPU utilization through a centralized approach to intra-server load balancing. Adam Belay is a Ph.D. candidate in Computer Science at Stanford University, where he is a member of the Secure Computer Systems Group and the Multiscale Architecture and Systems Team. Previously, he worked on storage virtualization at VMware Inc. and contributed substantial power management code to the Linux Kernel project. Adam's research area is operating systems and networking. Much of his work has focused on restructuring computer systems so that developers can more easily reach the full performance potential of hardware. Adam has received a Stanford Graduate Fellowship, a VMware Graduate Fellowship, and an OSDI Jay Lepreau Best Paper Award.

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Jude Nelson will present his Pre-FPO on Wednesday, March 30, 2016 at 2pm in CS 402.
by Nicki Gotsis 23 Mar '16

23 Mar '16

Jude Nelson will present his Pre-FPO on Wednesday, March 30, 2016 at 2pm in CS 402. The members of his committee are: Larry Peterson (adviser), John Hartman (reader; University of Arizona), Jen Rexford (reader), Brian Kernighan (non-reader), Kai Li (non-reader) Everyone is invited to attend his talk. The talk title and abstract follow below: "Syndicate: Software-defined Storage for Wide-area Networks" Abstract The proliferation of commodity cloud services presents a golden opportunity for hosting data for wide-area applications. Instead of writing a new storage system from scratch, developers can integrate existing component services into a coherent storage solution. This is highly desirable in theory, because it reduces the amount of code they must deploy while helping them achieve their desired storage cost/performance trade-offs. However, in practice this poses interesting distributed systems challenges, since each component can independently fail, become a performance bottleneck, become too costly to utilize, or change its API and behaviors. Without careful design, built-from-parts wide-area storage can result in brittle, hard-to-modify, and expensive-to-operate applications. In this thesis, we explore the challenges of integrating existing systems to create coherent wide-area storage. Our solution is Syndicate, a scalable software-defined storage system for wide-area networks. Unlike conventional built-from-parts storage, Syndicate lets developers explicitly control end-to-end data consistency, data flow processing, and administrative and trust boundaries across the wide-area. With Syndicate, an application accesses data via a stable storage interface (such as a filesystem), while developers control at runtime how data moves through an ever-changing set of underlying existing systems. In this manner, applications remain resilient to service changes--developers can "hot-swap" services for a better cost/performance trade-off, and tolerate service API changes and failures without taking the application offline. We validate Syndicate's design by using it to construct three non-trivial wide-area applications, and show that Syndicate imposes minimal runtime overhead while significantly reducing the amount of storage code a developer must write. Syndicate is open-source software comprising of approximately 30,000 lines of C++ and 13,000 lines of Python. It is available at https://github.com/syndicate-storage.

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EE Seminar - March 28, 2016, 4:30 pm, E-Quad B205 - Prof. Christopher Batten
by Nicole E. Wagenblast 23 Mar '16

23 Mar '16

Speaker: Prof. Christopher Batten Cornell University Title: Architectural Specialization for Inter-Iteration Loop Dependence Patterns Date: Monday, March 28, 2016 Time: 4:30 p.m. Room: E-Quad, Room B205 Host: Prof. David Wentzlaff Abstract: Hardware specialization is an increasingly common technique to enable improved performance and energy efficiency in spite of the diminished benefits of technology scaling. Exploring hardware specialization requires a vertically integrated research approach spanning applications, compilers, run-times, instruction set design, microarchitectures, and VLSI implementation. In the first part of the talk, I will describe our work on a new architectural design pattern called explicit loop specialization (XLOOPS) based on the idea of elegantly encoding inter-iteration loop dependence patterns in the instruction set. The XLOOPS hardware/software abstraction requires only lightweight changes to a general-purpose compiler to generate XLOOPS binaries and enables executing these binaries on: (1) traditional microarchitectures with minimal performance impact, (2) specialized microarchitectures to improve performance and/or energy efficiency, and (3) adaptive microarchitectures that can seamlessly migrate loops between traditional and specialized execution to dynamically trade-off performance vs. energy efficiency. Our initial results show promising performance improvements compared to simple in-order processors and energy efficiency improvements compared to complex out-of-order processors. In the second part of the talk, I will describe PyMTL and Pydgin, two new Python-based frameworks designed to improve the productivity of vertically integrated computer architecture research. PyMTL leverages the Python programming language to create a highly productive domain-specific embedded language for concurrent-structural modeling and hardware design. The PyMTL framework encourages a philosophy of "modeling towards layout" in which a microarchitecture is incrementally refined from a high-level functional-level model, to a timing-approximate cycle-level model, to a bit-accurate RTL implementation. Pydgin is a framework for rapidly developing very fast instruction-set simulators (ISSs) from a Python-based architecture description language. Both frameworks were critical in exploring the XLOOPS architectural design pattern, and we are continuing to leverage these frameworks in our research and teaching. Biography: Christopher Batten is an Assistant Professor in the School of Electrical and Computer Engineering at Cornell University, where he leads a research group focusing on energy-efficient parallel computer architecture for both high-performance and embedded applications. His work has been recognized with several awards including an AFOSR Young Investigator Program award (2015), Intel Early Career Faculty Honor Program award (2013), an NSF CAREER award (2012), a DARPA Young Faculty Award (2012), and an IEEE Micro Top Picks selection (2004). His teaching has been recognized with a Michael Tien '72 Excellence in Teaching Award (2013) and a James M. and Marsha D. McCormick Award for Outstanding Advising of First-Year Engineering Students (2013). Prior to his appointment at Cornell, Batten received his Ph.D. in electrical engineering and computer science from the Massachusetts Institute of Technology in 2010. He received an M.Phil. in engineering as a Churchill Scholar at the University of Cambridge in 2000, and received a B.S. in electrical engineering as a Jefferson Scholar at the University of Virginia in 1999.

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Colloquium Speaker: Adam Belay, Thursday, March 24- 12:30pm- reminder
by Nicole E. Wagenblast 23 Mar '16

23 Mar '16

Colloquium Speaker Adam Belay, Stanford University Thursday, March 24, 12:30pm Computer Science 105 Unleashing Hardware Potential through Better OS Abstractions Datacenter workloads have demanding performance requirements, including the simultaneous need for high throughput, low tail latency, and high server utilization. While modern hardware is compatible with these goals, modern operating systems remain a bottleneck. Better OS abstractions could significantly improve performance, yet deploying these abstractions has become intractable given the size and complexity of today's systems. I will first discuss Dune, a kernel extension that allows OS developers to sidestep software and hardware complexity by running an OS within an ordinary Linux process. With Dune, developers can both access the capabilities of raw hardware and fall back on the functionality of a full Linux environment where convenient. I will then discuss IX and Shinjuku, two generations of new datacenter-focused operating systems that were enabled by Dune. IX provides a novel system call interface that greatly improves network throughput without sacrificing latency. For example, IX improves Memcached's TCP throughput by 5x over Linux. Shinjuku, an ongoing research effort, aims to significantly increase CPU utilization through a centralized approach to intra-server load balancing. Adam Belay is a Ph.D. candidate in Computer Science at Stanford University, where he is a member of the Secure Computer Systems Group and the Multiscale Architecture and Systems Team. Previously, he worked on storage virtualization at VMware Inc. and contributed substantial power management code to the Linux Kernel project. Adam's research area is operating systems and networking. Much of his work has focused on restructuring computer systems so that developers can more easily reach the full performance potential of hardware. Adam has received a Stanford Graduate Fellowship, a VMware Graduate Fellowship, and an OSDI Jay Lepreau Best Paper Award.

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Colloquium Speaker: Igor Mordatch, Today, 4:30pm
by Nicole E. Wagenblast 23 Mar '16

23 Mar '16

Colloquium Speaker Igor Mordatch, University of California, Berkeley Wednesday, March 23, 4:30pm Computer Science 105 Automated Discovery and Learning of Complex Movement Behaviours In order to create truly autonomous physical robots, understand the underlying principles behind human movement, or tell narratives in animated films and interactive games, it is necessary to synthesize movement behaviours with the same wide variety, richness and complexity observed in humans and other animals. Moreover, these behaviours should be discovered automatically from only a few core principles, and not be a result of extensive manual engineering or a mimicking of demonstrations. In this talk at the intersection of robotics, computer graphics and biomechanics, I will show work on novel trajectory and policy optimization methods that give rise to a range of behaviours such getting up, climbing, moving objects, hand manipulation, acrobatics, and various cooperative actions involving multiple characters all in a single system. The resulting movements can be used to successfully control a physical bipedal robot and coupled with detailed models of human physiology, motions that match real human motion can be produced de novo, giving the predictive power to conduct virtual biomechanics experiments. The approach is fully automatic, based on general neural network policy representations and does not require domain knowledge specific to each behaviour, pre-existing examples or motion capture data. Although discovery and learning are computationally-expensive and rely on cloud and GPU computing, the interactive animation can run in real-time on any hardware once the controllers are learned. Igor Mordatch is a post-doctoral fellow working with professor Pieter Abbeel at University of California, Berkeley. He received his PhD at University of Washington under supervision of Emanuel Todorov and Zoran Popovic and undergraduate degree in Computer Science and Mathematics at University of Toronto. He worked as a visiting researcher at Stanford University and Pixar Research. His research interests lie in the development and use of optimal control and machine learning techniques for robotics, computer graphics, and biomechanics.

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Colloquium Speaker: Igor Mordatch, Wednesday, March 23, 4:30pm
by Nicole E. Wagenblast 22 Mar '16

22 Mar '16

Colloquium Speaker Igor Mordatch, University of California, Berkeley Wednesday, March 23, 4:30pm Computer Science 105 Automated Discovery and Learning of Complex Movement Behaviours In order to create truly autonomous physical robots, understand the underlying principles behind human movement, or tell narratives in animated films and interactive games, it is necessary to synthesize movement behaviours with the same wide variety, richness and complexity observed in humans and other animals. Moreover, these behaviours should be discovered automatically from only a few core principles, and not be a result of extensive manual engineering or a mimicking of demonstrations. In this talk at the intersection of robotics, computer graphics and biomechanics, I will show work on novel trajectory and policy optimization methods that give rise to a range of behaviours such getting up, climbing, moving objects, hand manipulation, acrobatics, and various cooperative actions involving multiple characters all in a single system. The resulting movements can be used to successfully control a physical bipedal robot and coupled with detailed models of human physiology, motions that match real human motion can be produced de novo, giving the predictive power to conduct virtual biomechanics experiments. The approach is fully automatic, based on general neural network policy representations and does not require domain knowledge specific to each behaviour, pre-existing examples or motion capture data. Although discovery and learning are computationally-expensive and rely on cloud and GPU computing, the interactive animation can run in real-time on any hardware once the controllers are learned. Igor Mordatch is a post-doctoral fellow working with professor Pieter Abbeel at University of California, Berkeley. He received his PhD at University of Washington under supervision of Emanuel Todorov and Zoran Popovic and undergraduate degree in Computer Science and Mathematics at University of Toronto. He worked as a visiting researcher at Stanford University and Pixar Research. His research interests lie in the development and use of optimal control and machine learning techniques for robotics, computer graphics, and biomechanics.

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