- talks - lists.cs.princeton.edu

Mark Browning MSE thesis talk
by Melissa M. Lawson 24 Apr '13

24 Apr '13

Mark Browning will present his MSE thesis talk on Tuesday April 30 at 3PM in Room 302 (note room!). The members of his committee are Adam Finkelstein, advisor and Szymon Rusinkiewicz, reader. Everyone is invited to attend his talk. His abstract follows below. ----- Original Message ----- Stylized Keyframe Animation Using Motion Field Guided Morphs Traditional 2D animation is a challenging task, because each frame must be drawn or synthesized such that it is both temporally and stylistically coherent with neighboring frames. We present a method that makes this process easier when the desired motion of the animation is available. Our method combines stylized keyframes with motion fields describing the transitions between the keyframes to produce inbetweens that: 1) are in the visual style of the keyframes, and 2) follow the given motion fields. By automatically generating the inbetweens, our system reduces the number of frames that must be drawn by up to an order of magnitude and relaxes the animator's burden of ensuring coherence. Our work builds on regenerative morphing/image melding, a recent advance in morphing that generates temporally and stylistically coherent transitions between two images. We extend this method to produce transitions that additionally respect a given motion field, and adapt it to multi-keyframe sequences. We demonstrate that our system can be used to animate fluids, apply single-frame filters to video in a temporally coherent way, and rotoscope video.

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Dan Larkin general exam
by Melissa M. Lawson 24 Apr '13

24 Apr '13

Dan Larkin will present his research seminar/general exam on Tuesday April 30 at 2PM in Room 402. The members of his committee are: Bob Tarjan (advisor), Bob Sedgewick, and Moses Charikar. Everyone is invited to attend his talk, and those faculty wishing to remain for the oral exam following are welcome to do so. His abstract and reading list follow below. ----- Original Message ----- TITLE Experimental Heaps: a Comparative Study of Priority Queues ABSTRACT In many areas the theory-practice gap is neglected. One such divide which has widened in the past decade is that pertaining to priority queue variants. Most implementations in use today are based on classical binary heaps and some slight variations thereof, with a few libraries implementing binomial queues or other quick-melding structures developed in the 1980s. These choices are accompanied by experimentally backed claims that more complicated, and better-in-theory structures simply run slower on real-world workloads. This hasn't seemed to deter the theory community though, as a flurry of results has been published recently establishing new structures which achieve optimal theoretical bounds while claiming in some way to be better than older variants. Whether this claimed improvement is in theoretical elegance, implementational efficiency, or pedagogical convenience, the claims have not been thoroughly tested. Furthermore, previously published experimental work is outdated or suffers from a limited scope. This work seeks to reopen the discussion on narrowing the gap. Implementing both some classic structures and several new, untested variants, we collect a variety of performance metrics across several types of workloads. We include both relatively realistic workloads and purely contrived randomized workloads, which can nevertheless help shed light on practical properties of different structures. We also show that one such contrived workload, a very natural operation sequence found in a benchmark suite, is fundamentally degenerate. We identify trends which may help provide guidance to future practitioners and theoreticians alike. READING LIST Textbook: "Introduction to Algorithms," 2nd ed., T. H. Cormen, C. E. Leiserson, R. L. Rivest, C. Stein. Structures implemented: "Algorithm 232 heapsort," J. W. J. Williams. "A data structure for manipulating priority queues," J. Vuillemin. "Fibonacci heaps and their uses in improved network optimization algorithms," M. L. Fredman, R. E. Tarjan. "The pairing heap: A new form of self-adjusting heap," M. L. Fredman, R. Sedgewick, D. D. Sleator, R. E. Tarjan. "The weak-heap family of priority queues in theory and praxis," S. Edelkamp, A. Elmasry, J. Katajainen. "The violation heap: A relaxed Fibonacci-like heap," A. Elmasry. "Quake heaps: a simple alternative to Fibonacci heaps," T. M. Chan. "Rank-pairing heaps," B. Haeupler, S. Sen, R. E. Tarjan. "Strict fibonacci heaps," G. S. Brodal, G. Lagogiannis, R. E. Tarjan. Some previous experimental studies on heaps: "Pairing heaps: experiments and analysis," J. T. Stasko, J. S. Vitter. "The influence of caches on the performance of heaps," A. LaMarca, R. E. Ladner. "Fast priority queues for cached memory," P. Sanders.

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Matvey Arye general exam
by Melissa M. Lawson 23 Apr '13

23 Apr '13

Matvey Arye will present his research seminar/general exam on Monday April 29 at 12:30 PM in Room 401 (note room!). The members of his committee are: Michael Freedman (advisor), Vivek Pai, and Kai Li. Everyone is invited to attend his talk and those faculty wishing to remain for the oral exam following are welcome to do so. His abstract and reading list follow below. ----- Original Message ----- Abstract: Global-scale services generate data that is both widely distributed and big, such as system logs and video feeds. Unfortunately, traditional approaches for backhauling and analyzing this data centrally are slow and expensive, due to the high cost or availability of wide-area network bandwidth. Moreover, they require the analyst to commit to a data-collection policy upfront, making it agnostic to current and future resource conditions. Jetstream is a system that allows adaptive and real-time analysis of large, distributed data sets. It uses dispersed, structured storage to enable data collection without a fixed policy, and adapts the fidelity of collection in response to changes in network conditions. Namely, if a given user query cannot be satisfied within the available bandwidth, Jetstream automatically transforms the query, trading precision for bandwidth. One key ingredient in Jetstream’s architecture is its storage abstraction: a novel adaptation of the data cube from OLAP databases, which we use to represent aggregations and approximations of distributed data. The cube model helps us define a range of data-degradation transforms, all of which can be implemented as standard operators in a user’s query graph. The evaluation is conducted on a system stretching between clusters in Europe and North America and demonstrates the ability to maintain real-time responsiveness, save significant bandwidth through in-place aggregation and approximation, and dynamically adapt the data degradation policies based on changing resource constraints and input data rates. Current Reading List: (9 papers and 1 textbook) Principles of Computer System Design: An Introduction Saltzer and Kaashoek The Design of the Borealis Stream Processing Engine Abadi et al., CIDR 2005 Dryad: Distributed Data-Parallel Programs from Sequential Building Blocks Michael Isard, Mihai Budiu, Yuan Yu, Andrew Birrell, and Dennis Fetterly EuroSys, 2007 TAG: A Tiny Aggregation Service for Ad-Hoc Sensor Networks Madden et al., OSDI, 2002 A Cost-Space Approach to Distributed Query Optimization in Stream Based Overlays Shneidman et al., NetDB 2005 BlinkDB: Queries with Bounded Errors and Bounded Response Times on Very Large Data Sameer Agarwal, Aurojit Panda, Barzan Mozafari, Samuel Madden, Ion Stoica To Appear in ACM EuroSys 2013 DBToaster: Higher-order Delta Processing for Dynamic, Frequently Fresh Views Yanif Ahmad, Oliver Kennedy, Christoph Koch, and Milos Nikolic VLDB 2012 MapReduce: Simplified Data Processing on Large Clusters Jeffrey Dean and Sanjay Ghemawat, OSDI 2004 Data Cube: A Relational Aggregation Operator Generalizing Group-By, Cross-Tab, and Sub-Totals Jim Gray, et al., Data Mining and Knowledge Discover 1997. Discretized Streams: An Efﬁcient and Fault-Tolerant Model for Stream Processing on Large Clusters Matei Zaharia, et al., HotCloud, 2012.

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Xin Jin general exam
by Melissa M. Lawson 23 Apr '13

23 Apr '13

Xin Jin will present his research seminar/general exam on Monday April 29 at 2:30PM in Room 401 (note room!). The members of his committee are: Jennifer Rexford (advisor), Michael Freedman, and Kai Li. Everyone is invited to attend his talk, and those faculty wishing to remain for the oral exam following are welcome to do so. His abstract and reading list follow below. ----- Original Message ----- The title is "SoftCell: Taking Control of Cellular Core Networks". Existing cellular networks suffer from inflexible and expensive equipment, and complex control-plane protocols. To address these challenges, we present SoftCell, a scalable architecture for supporting fine-grained policies for mobile devices in cellular core networks. The SoftCell controller realizes high-level service polices by directing traffic over paths that traverse a sequence of middleboxes, optimized to the network conditions and user locations. To ensure scalability, the core switches forward traffic on hierarchical addresses (grouped by base station) and policy tags (identifying paths through middleboxes). This minimizes data-plane state in the core switches, and pushes all fine-grained state to software switches at the base stations. These access switches apply fine-grained rules, specified by the controller, to map all traffic to the appropriate addresses and tags. SoftCell guarantees that packets in the same connection traverse the same sequence of middleboxes in both directions, even in the presence of mobility. Our characterization of real LTE workloads, micro-benchmarks on our prototype controller, and large-scale simulations demonstrate that SoftCell improves the flexibility of cellular core networks, while enabling the use of inexpensive commodity switches and middleboxes. [1] L. L. Peterson and B. S. Davie, Computer networks: a systems approach. Morgan Kaufmann, 2007. [2] J. H. Saltzer, D. P. Reed, and D. D. Clark, “End-to-end arguments in system design,” ACM Transactions on Computer Systems (TOCS), vol. 2, no. 4, 1984. [3] M. Casado, M. J. Freedman, J. Pettit, J. Luo, N. Gude, N. McKeown, and S. Shenker, “Rethinking enterprise network control,” IEEE/ACM Trans. Networking, vol. 17, August 2009 . [4] N. McKeown, T. Anderson, H. Balakrishnan, G. Parulkar, L. Peterson, J. Rexford, S. Shenker, and J. Turner, “OpenFlow: Enabling innovation in campus networks,” SIGCOMM Computer Communications Review, vol. 38, no. 2, 2008. [5] A. R. Curtis, J. C. Mogul, J. Tourrilhes, P. Yalagandula, P. Sharma, and S. Banerjee, “DevoFlow: Scaling flow management for high-performance networks,” in ACM SIGCOMM, August 2011 . [6] A. Greenberg, J. R. Hamilton, N. Jain, S. Kandula, C. Kim, P. Lahiri, D. A. Maltz, P. Patel, and S. Sengupta, “VL2: A scalable and flexible data center network,” in ACM SIGCOMM, August 2009 . [7] R. Niranjan Mysore, A. Pamboris, N. Farrington, N. Huang, P. Miri, S. Radhakrishnan, V. Subramanya, and A. Vahdat, “PortLand: a scalable fault-tolerant layer 2 data center network fabric,” in ACM SIGCOMM, August 2009 . [8] D. Joseph, A. Tavakoli, and I. Stoica, “A policy-aware switching layer for data centers,” in ACM SIGCOMM, August 2008 . [9] Z. Wang, Z. Qian, Q. Xu, Z. Mao, and M. Zhang, “An untold story of middleboxes in cellular networks,” in ACM SIGCOMM, August 2011 . [10] M. Z. Shafiq, L. Ji, A. X. Liu, and J. Wang, “Characterizing and modeling internet traffic dynamics of cellular devices,” in ACM SIGMETRICS, June 2011 . [11] K.-K. Yap, R. Sherwood, M. Kobayashi, T.-Y. Huang, M. Chan, N. Handigol, N. McKeown, and G. Parulkar, “Blueprint for introducing innovation into wireless mobile networks,” in ACM VISA Workshop, August 2010 .

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D Shue preFPO
by Melissa M. Lawson 18 Apr '13

18 Apr '13

David Shue will present his preFPO on Thursday April 25 at 9AM in Room 402. The members of his committee are: Michael Freedman, advisor; Jennifer Rexford and Anees Shaikh (IBM Research), readers; Vivek Pai and Margaret Martonosi, nonreaders. Everyone is invited to attend his talk. His abstract follows below. -------------------------------------------- Title: Performance Isolation and Fairness for Multi-Tenant Cloud Storage Abstract: Shared storage services enjoy wide adoption in commercial clouds. But most systems today provide weak performance isolation and fairness between tenants, if at all. Misbehaving or high-demand tenants can overload the shared service and disrupt other well-behaved tenants, leading to unpredictable performance and violating SLAs. In this thesis, we present Pisces, a system for achieving datacenter-wide per-tenant performance isolation and fairness in shared key-value storage. Today’s approaches for multi-tenant resource allocation are based either on per-VM allocations or hard rate limits that assume uniform workloads to achieve high utilization. Pisces provides per-tenant weighted fair shares (or minimal rates) of the aggregate resources over the entire service, even when different tenants’ partitions are co-located and when demand for different partitions is skewed, time-varying, or bottlenecked by different server resources. Our key insight was to decompose the system-wide fair sharing problem into a combination of four complementary mechanisms—partition placement, weight allocation, replica selection, and weighted fair queuing—that operate on different time-scales and combine to achieve per-tenant max-min fairness. While Pisces provides fairness for key-value storage systems that leverage asynchronous writes for performance, many storage systems require stronger durability guarantees and often provide rich data models that can support arbitrary computation in the form of UDF's or map/reduce functionality. Achieving predictable performance in these systems requires fine-grained per-tenant resource allocation over multiple resources (e.g network, disk, and CPU). In the second part of this thesis, w e generalize and extend the PIsces per-node scheduling model with Libra, a multi-resource allocation library for building predictable shared services.

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lunchtime Tue Apr 23 talk on automated formal analysis of Internet routing systems
by Jennifer Rexford 17 Apr '13

17 Apr '13

Speaker: Anduo Wang, U. Penn, http://www.cis.upenn.edu/~anduo/ Title: Automated Formal Analysis of Internet Routing Systems Date/time: 12:30-1:20pm Tue Apr 23 (lunch served 12-12:30) Location: 402 in CS building Abstract: The past twenty years have witnessed significant advances in formal modeling, system verification and testing of network protocols. However a long-standing challenge in these approaches is the decoupling of formal reasoning process and the actual distributed implementation. This talk presents my thesis work on bridging formal reasoning and actual implementation in the context of today’s Internet routing. I will present the Formally Safe Routing (FSR) toolkit, that combines the use of declarative networking, routing algebra, and SMT solver techniques, in order to synthesize faithful distributed routing implementations from verified network models. Next, I will describe our work on scaling up formal analysis of lnternet-scale configurations. Our core technique uses a configuration rewriting calculus for transforming large network configurations into smaller instances, while preserving routing behaviors. Finally, I conclude with a discussion of my ongoing and future work, on synthesizing provably correct network configurations for the emerging Software Defined Networking (SDN) platforms.

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CITP Event Brad Smith – Immigration, Education, and the Future of Computer Science in America Friday, April 19, 12:30pm
by Nicole E. Wagenblast 17 Apr '13

17 Apr '13

Brad Smith – Immigration, Education, and the Future of Computer Science in America Date: Friday, April 19, 2013 Time: 12:30 PM Location: 3rd Floor Open Space, Sherrerd Hall Streaming Live: https://www.youtube.com/user/citpprinceton Brad Smith is Microsoft’s General Counsel and leads the company’s Department of Legal and Corporate Affairs (LCA). He is responsible for the company’s legal work, its intellectual property portfolio and patent licensing business, and its government affairs and philanthropic work. Since becoming general counsel in 2002, Smith has overseen numerous negotiations leading to competition law and intellectual property agreements with governments around the world and with companies across the IT sector. He has led the launch of global campaigns to bring enforcement actions against those engaged in software piracy and counterfeiting, malware, consumer fraud, and other digital crimes. Before joining Microsoft in 1993, Smith was a partner at Covington & Burling, having worked in the firm’s Washington, D.C., and London offices. He graduated summa cum laude from Princeton University and received his law degree at Columbia University.

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Colloquium Speaker Ranjitha Kumar, Mon April 15, 4:30pm
by Nicole E. Wagenblast 12 Apr '13

12 Apr '13

Design Mining the Web Ranjitha Kumar , Stanford University Monday, April 15th, 4:30pm Computer Science 105 The Web has transformed the nature of creative work. For the first time, millions of people have a direct outlet for sharing their creations with the world. As a result, the Web has become the largest repository of design knowledge in human history, and the ensuing "democratization of design" has created a critical feedback loop, engendering a new culture of reuse and remixing. The means and methods designers employ to draw on prior work, however, remain mostly informal and ad hoc. How can content producers find relevant examples amongst hundreds of millions of possibilities and leverage existing design practice to inform and improve their creations? My research explores data-driven techniques for working with examples at scale during the design process, automating search and curation, enabling rapid retargeting, and learning generative probabilistic models to support new design interactions. Knowledge discovery and data mining have revolutionized informatics; in this talk, I'll discuss what we can learn from mining design. Ranjitha Kumar is a PhD candidate in the Computer Science Department at Stanford University, where she builds principled, data-driven tools for amplifying human creativity in design. Her work has received best paper awards or nominations at both of the premiere HCI conferences (CHI and UIST), and been recognized by the machine learning community through invited papers at IJCAI and ICML. She is the recipient of the 2011 Google PhD Fellowship in Design Development, and holds a BS in Computer Science from Stanford.

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4:30pm Wed Apr 10 talk on NetFPGA platform in room CS 402
by Jennifer Rexford 10 Apr '13

10 Apr '13

Speaker: Andrew Moore (University of Cambridge) Title: NetFPGA: The Flexible Open-Source Networking Platform Time: 4:30pm Wednesday April 10 Place: CS 402 Abstract: The NetFPGA is an open platform enabling researchers and instructors to build high-speed, hardware-accelerated networking systems. The NetFPGA is the de-facto experimental platform for line-rate implementations of network research and it continues with a new generation platform capable of 4x10Gbps. The target audience is not restricted to hardware researchers: the NetFPGA provides the ideal platform for research across a wide range of networking topics from architecture to algorithms and from energy-efficient design to routing and forwarding. The most prominent NetFPGA success is OpenFlow, which in turn has reignited the Software Defined Networking movement. NetFPGA enabled OpenFlow by providing a widely available open-source development platform capable of line-rate and was, until its commercial uptake, the reference platform for OpenFlow. NetFPGA enables high-impact network research. This seminar will combine presentation and demonstration; no knowledge of hardware programming languages (eg Verilog/VHDL) is required. A NetFPGA 10G card will be awarded as a door-prize amongst the seminar attendees.

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Colloquium Speaker Matei Zaharia Thurs April 11, 4:30pm
by Nicole E. Wagenblast 09 Apr '13

09 Apr '13

Making Big Data Analytics Interactive and Real-Time Matei Zaharia , University of California, Berkeley Thursday, April 11, 2013, 4:30pm Computer Science 105 The rapid growth in data volumes requires new computer systems that scale out across hundreds of machines. While early frameworks, such as MapReduce, handled large-scale batch processing, the demands on these systems have also grown. Users quickly needed to run (1) more interactive ad-hoc queries, (2) more complex multi-pass algorithms (e.g. machine learning and graph processing), and (3) real-time processing on large data streams. In this talk, we present a single abstraction, resilient distributed datasets (RDDs), that supports all of these emerging workloads by providing efficient and fault-tolerant in-memory data sharing. We have used RDDs to build a stack of computing systems including the Spark parallel engine, Shark SQL processor, and Spark Streaming engine. Spark and Shark can run machine learning algorithms and interactive queries up to 100x faster than Hadoop MapReduce, while Spark Streaming enables fault-tolerant stream processing at significantly higher scales than were possible before. These systems, along with several resource allocation and scheduling algorithms we have developed along the way, have been used in multiple industry and research applications, and have a growing open source community with 14 companies contributing in the past year. Matei Zaharia is a PhD student at UC Berkeley, working with Scott Shenker and Ion Stoica on topics in systems, cloud computing and networking. He is also a committer on Apache Mesos and Apache Hadoop. His work is supported by a Google PhD fellowship. Matei got his undergraduate degree at the University of Waterloo in Canada.

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