- talks - lists.cs.princeton.edu

Distinguished Lecturer Jeff Dean, April 24 at 4:30
by Emily C. Lawrence 10 Apr '18

10 Apr '18

Jeff Dean from Google Research Tuesday, April 24, 2018 - 4:30pm Friend Center - Room 101 Host: Kai Li Event page: http://www.cs.princeton.edu/events/25679 "Deep Learning to Solve Challenging Problems" For the past six years, the Google Brain team has conducted research on difficult problems in artificial intelligence, on building large-scale computer systems for machine learning research, and, in collaboration with many teams at Google, on applying our research and systems to dozens of Google products. We have made significant progress in computer vision, speech recognition, language understanding, machine translation, healthcare, robotic control, and other areas. Our group has open-sourced the TensorFlow system, a widely popular system designed to easily express machine learning ideas, and to quickly train, evaluate and deploy machine learning systems. In this talk, I'll highlight some of the research and computer systems work we've done with an eye towards how it can be used to solve challenging problems. This talk describes joint work with many people at Google. Bio: Jeff Dean joined Google in 1999 and is currently a Google Senior Fellow in Google's Research Group, where he co-founded and leads the Google Brain team, Google's deep learning and artificial intelligence research team. He and his collaborators are working on systems for speech recognition, computer vision, language understanding, and various other machine learning tasks. He has co-designed/implemented many generations of Google's crawling, indexing, and query serving systems, and co-designed/implemented major pieces of Google's initial advertising and AdSense for Content systems. He is also a co-designer and co- implementor of Google's distributed computing infrastructure, including the MapReduce , BigTable and Spanner systems, protocol buffers, the open-source TensorFlow system for machine learning, and a variety of internal and external libraries and developer tools. Jeff received a Ph.D. in Computer Science from the University of Washington in 1996, working with Craig Chambers on whole-program optimization techniques for object-oriented languages. He received a B.S. in computer science & economics from the University of Minnesota in 1990. He is a member of the National Academy of Engineering, and of the American Academy of Arts and Sciences, a Fellow of the Association for Computing Machinery (ACM), a Fellow of the American Association for the Advancement of Sciences (AAAS), and a winner of the ACM Prize in Computing and the Mark Weiser Award. **A reception in the Friend Center Upper Atrium will follow immediately after the talk.

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CORRECTION - Yinda Zhang PreFPO tomorrow April 10, 2018 at 2:00 pm CS402
by Barbara A. Mooring 09 Apr '18

09 Apr '18

Yinda Zhang will present PreFPO on Tuesday, April 10, 2018 at 2:00 in room CS402 Committee Member: Thomas Funkhouser, Adviser Olga Russakovsky Szymon Rusinkiewicz Ryan Adams James Hays (Georgia Institute of Technology) All are welcomed to attend. Title and abstract are below. Title: “From Pixels to Scenes: Recovering 3D Geometry and Semantics for Indoor Environments” Abstract: Understanding 3D geometry and semantics of the surrounding environment is in critically high demand for many applications, such as autonomous driving, robotics, augmented reality, etc. However, it is extremely challenging due to the low quality depth measurements due to failures and noisy measurements from sensors, limited access to ground truth data, and cluttered scenes with heavy occlusions and intervening objects. In this presentation, I will introduces a full spectrum of 3D scene understanding works to handle these challenging issues. Starting from estimating a depth map, which is one of the most important immediate measurements of the 3D geometry of the scene, we introduce a learning based active stereo system that learns self-supervisely and reduces the disparity error to 1/10th of other canonical stereo systems. To further handle the missing depth caused by sensor failures, we propose a method to effectively complete the depth map using information from an aligned color image. Beyond per pixel depth, we then attempt to predict other high-level semantics on each pixel, such as surface normals and object boundaries. However, realizing the lack of large scale supervision, we design a synthetic data generation framework, which creates photo-realistic color rendering and various of accurate pixel-wise ground truths to facilitate the learning process and improve the performance on real data. In the end, we pursue holistic scene understanding by estimating a 3D representation of the scene, in which objects and room layout are represented using 3D bounding box and planar surface respectively. We propose methods to produce such representation from either a single color panorama or depth image leveraging scene context. On the whole, these proposed methods produce understanding of both 3D geometry and semantics from the most fine-grained pixel level to the holistic scene scale, which build foundations and could possibly inspire future works for 3D scene understanding. Barbara A. Mooring Interim Graduate Coordinator Computer Science Department Princeton University

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Yinda Zhang - PreFPO - April 10, 2018 at 2:00 pm CS402
by Barbara A. Mooring 09 Apr '18

09 Apr '18

Yinda Zhang will present PreFPO on Tuesday, April 20, 2018 at 2:00 in room CS402 Committee Member: Thomas Funkhouser, Adviser Olga Russakovsky Szymon Rusinkiewicz Ryan Adams James Hays (Georgia Institute of Technology) All are welcomed to attend. Title and abstract are below. Title: “From Pixels to Scenes: Recovering 3D Geometry and Semantics for Indoor Environments” Abstract: Understanding 3D geometry and semantics of the surrounding environment is in critically high demand for many applications, such as autonomous driving, robotics, augmented reality, etc. However, it is extremely challenging due to the low quality depth measurements due to failures and noisy measurements from sensors, limited access to ground truth data, and cluttered scenes with heavy occlusions and intervening objects. In this presentation, I will introduces a full spectrum of 3D scene understanding works to handle these challenging issues. Starting from estimating a depth map, which is one of the most important immediate measurements of the 3D geometry of the scene, we introduce a learning based active stereo system that learns self-supervisely and reduces the disparity error to 1/10th of other canonical stereo systems. To further handle the missing depth caused by sensor failures, we propose a method to effectively complete the depth map using information from an aligned color image. Beyond per pixel depth, we then attempt to predict other high-level semantics on each pixel, such as surface normals and object boundaries. However, realizing the lack of large scale supervision, we design a synthetic data generation framework, which creates photo-realistic color rendering and various of accurate pixel-wise ground truths to facilitate the learning process and improve the performance on real data. In the end, we pursue holistic scene understanding by estimating a 3D representation of the scene, in which objects and room layout are represented using 3D bounding box and planar surface respectively. We propose methods to produce such representation from either a single color panorama or depth image leveraging scene context. On the whole, these proposed methods produce understanding of both 3D geometry and semantics from the most fine-grained pixel level to the holistic scene scale, which build foundations and could possibly inspire future works for 3D scene understanding. Barbara A. Mooring Interim Graduate Coordinator Computer Science Department Princeton University

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Reminder: Colloquium Speaker-Amit Levy, tomorrow at 12:30pm
by Emily C. Lawrence 09 Apr '18

09 Apr '18

Amit Levy from Stanford University Tuesday, April 10, 2018 - 12:30pm Computer Science - Room 105 Host: Mike Freedman "Closing the Loop on Secure System Design" Abstract: Despite decades of research building secure operating systems, many deployed systems must still choose between flexible application APIs and security. As a result, the vast majority of programmers are unable to improve these systems. This is not merely a result of poor system building. It is hard to design highly extensible systems that are both secure and useful. Moreover, evaluating novel designs with actual developers is critical in order to make sure system builders can adopt research systems in practice. Fortunately, in emerging application domains, such as the Internet of Things, there are no entrenched operating systems and application portability is less important. This makes it possible evaluate research techniques for building more secure and extensible systems with developers who are willing to adopt them. I'll describe Tock, an operating system for microcontrollers that enables third-party developers to extend the system. Tock uses the Rust type-system to isolate kernel extensions and the hardware to isolate applications. I'll discuss how we continuously evaluate Tock by engaging with practitioners, and how lessons from practitioners have fed back into the system's design. Bio: Amit Levy is a PhD candidate in Computer Science at Stanford University. He builds secure operating system kernels, web platforms, and network systems that help make computers more programmable by third-party application developers.

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Colloquium Speaker-Jose Faleiro, TODAY at 12:30
by Emily C. Lawrence 09 Apr '18

09 Apr '18

CS Department Colloquium Speaker Jose Faleiro from Yale University Monday, April 9, 2018 - 12:30pm Computer Science - Room 105 Host: Wyatt Lloyd "High Performance Serializable Transactions via Deterministic Execution" Abstract: Concurrency, the processing of multiple requests simultaneously, is one of the most challenging problems large-scale server applications face in practice. Accordingly, database systems research has long made the case for automatically handling concurrency in the database by guaranteeing serializability . Serializability shields applications from reasoning about concurrency, and allows developers to focus entirely on implementing application logic. Unfortunately, in the 40-plus years since its inception, serializability has not seen wide adoption in practice. This is because weaker guarantees, which expose applications to concurrency and the inevitable bugs that arise, perform significantly better. In this talk, I will discuss my research on addressing the performance limitations of serializability via deterministic transaction execution. Deterministic transaction execution exploits the fact that a large class of modern server applications do not require the full generality of conventional database transactions. By tailoring transaction execution mechanisms for this class of applications, my research shows that it is possible to achieve serializability with minimal performance overhead. I will first describe a serializable multi-versioning mechanism that decouples conflicting reads and writes, and subsequently outperforms a state-of-the-art implementation of the weaker guarantee of snapshot isolation by over 3x. Next, I will describe piecewise visibility, a concurrency control mechanism that isolates requests at a finer granularity than entire transactions, which consequently permits aggressive serializable transaction interleavings and outperforms the weaker guarantee of read committed by over 3x. Finally, I will discuss ongoing work that applies deterministic transaction execution principles to address replication lag in Facebook’s production MySQL infrastructure. Bio: Jose Faleiro is a PhD candidate in computer science at Yale University. His research interests are in data management systems, multi-core systems, and distributed systems. His thesis research investigates the use of deterministic execution to enable scalable and efficient transaction processing on main-memory multi-core database systems. In addition to his academic research at Yale, Jose has worked on large-scale real world systems, including Microsoft’s Orleans cloud programming framework, and Facebook’s production MySQL infrastructure. He is the recipient of the Alan J. Perlis Fellowship at Yale, and a Microsoft Research Tech Transfer Award. He has an undergraduate degree in computer science from the Birla Institute of Technology and Science (BITS), Pilani , India.a

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Reminder: Colloquium Speaker-Jose Faleiro, tomorrow at 12:30
by Emily C. Lawrence 08 Apr '18

08 Apr '18

CS Department Colloquium Speaker Jose Faleiro from Yale University Monday, April 9, 2018 - 12:30pm Computer Science - Room 105 Host: Wyatt Lloyd "High Performance Serializable Transactions via Deterministic Execution" Abstract: Concurrency, the processing of multiple requests simultaneously, is one of the most challenging problems large-scale server applications face in practice. Accordingly, database systems research has long made the case for automatically handling concurrency in the database by guaranteeing serializability . Serializability shields applications from reasoning about concurrency, and allows developers to focus entirely on implementing application logic. Unfortunately, in the 40-plus years since its inception, serializability has not seen wide adoption in practice. This is because weaker guarantees, which expose applications to concurrency and the inevitable bugs that arise, perform significantly better. In this talk, I will discuss my research on addressing the performance limitations of serializability via deterministic transaction execution. Deterministic transaction execution exploits the fact that a large class of modern server applications do not require the full generality of conventional database transactions. By tailoring transaction execution mechanisms for this class of applications, my research shows that it is possible to achieve serializability with minimal performance overhead. I will first describe a serializable multi-versioning mechanism that decouples conflicting reads and writes, and subsequently outperforms a state-of-the-art implementation of the weaker guarantee of snapshot isolation by over 3x. Next, I will describe piecewise visibility, a concurrency control mechanism that isolates requests at a finer granularity than entire transactions, which consequently permits aggressive serializable transaction interleavings and outperforms the weaker guarantee of read committed by over 3x. Finally, I will discuss ongoing work that applies deterministic transaction execution principles to address replication lag in Facebook’s production MySQL infrastructure. Bio: Jose Faleiro is a PhD candidate in computer science at Yale University. His research interests are in data management systems, multi-core systems, and distributed systems. His thesis research investigates the use of deterministic execution to enable scalable and efficient transaction processing on main-memory multi-core database systems. In addition to his academic research at Yale, Jose has worked on large-scale real world systems, including Microsoft’s Orleans cloud programming framework, and Facebook’s production MySQL infrastructure. He is the recipient of the Alan J. Perlis Fellowship at Yale, and a Microsoft Research Tech Transfer Award. He has an undergraduate degree in computer science from the Birla Institute of Technology and Science (BITS), Pilani , India.a

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Colloquium Speaker-Saurabh Gupta, Thursday, April 12
by Emily C. Lawrence 06 Apr '18

06 Apr '18

Saurabh Gupta, University of California at Berkeley Thursday, April 12, 2018 - 12:30pm Computer Science - Room 105 Host: Szymon Rusinkiewicz “Visual Perception and Navigation in 3D Scenes” Abstract: In recent times, computer vision has made great leaps towards 2D understanding of sparse visual snapshots of the world. This is insufficient for robots that need to exist and act in the 3D world around them based on a continuous stream of multi-modal inputs. In this talk, I will present some of my efforts in bridging this gap between computer vision and robotics. I will show how thinking about computer vision and robotics together, brings out limitations of current computer vision tasks and techniques, and motivates joint study of perception and action for robotic tasks. I will showcase these aspects via three examples: 3D scene understanding, representation learning for varied modalities, and visual navigation. I will conclude by pointing out future research directions at the intersection of computer vision and robotics, thus showing how the two fields are ready to get back together. Bio: Saurabh Gupta is a Ph.D. student at UC Berkeley, where he is advised by Jitendra Malik. His research interests include computer vision, robotics and machine learning. His PhD work focuses on 3D scene understanding, and visual navigation. His work is supported by a Berkeley Fellowship and a Google Fellowship in Computer Vision.

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Colloquium Speaker-Amit Levy, Tuesday, April 10
by Emily C. Lawrence 04 Apr '18

04 Apr '18

Amit Levy from Stanford University Tuesday, April 10, 2018 - 12:30pm Computer Science - Room 105 Host: Mike Freedman "Closing the Loop on Secure System Design" Abstract: Despite decades of research building secure operating systems, many deployed systems must still choose between flexible application APIs and security. As a result, the vast majority of programmers are unable to improve these systems. This is not merely a result of poor system building. It is hard to design highly extensible systems that are both secure and useful. Moreover, evaluating novel designs with actual developers is critical in order to make sure system builders can adopt research systems in practice. Fortunately, in emerging application domains, such as the Internet of Things, there are no entrenched operating systems and application portability is less important. This makes it possible evaluate research techniques for building more secure and extensible systems with developers who are willing to adopt them. I'll describe Tock, an operating system for microcontrollers that enables third-party developers to extend the system. Tock uses the Rust type-system to isolate kernel extensions and the hardware to isolate applications. I'll discuss how we continuously evaluate Tock by engaging with practitioners, and how lessons from practitioners have fed back into the system's design. Bio: Amit Levy is a PhD candidate in Computer Science at Stanford University. He builds secure operating system kernels, web platforms, and network systems that help make computers more programmable by third-party application developers.

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Colloquium Speaker-Jose Faleiro, Monday, April 9
by Emily C. Lawrence 04 Apr '18

04 Apr '18

CS Department Colloquium Speaker Jose Faleiro from Yale University Monday, April 9, 2018 - 12:30pm Computer Science - Room 105 Host: Wyatt Lloyd "High Performance Serializable Transactions via Deterministic Execution" Abstract: Concurrency, the processing of multiple requests simultaneously, is one of the most challenging problems large-scale server applications face in practice. Accordingly, database systems research has long made the case for automatically handling concurrency in the database by guaranteeing serializability . Serializability shields applications from reasoning about concurrency, and allows developers to focus entirely on implementing application logic. Unfortunately, in the 40-plus years since its inception, serializability has not seen wide adoption in practice. This is because weaker guarantees, which expose applications to concurrency and the inevitable bugs that arise, perform significantly better. In this talk, I will discuss my research on addressing the performance limitations of serializability via deterministic transaction execution. Deterministic transaction execution exploits the fact that a large class of modern server applications do not require the full generality of conventional database transactions. By tailoring transaction execution mechanisms for this class of applications, my research shows that it is possible to achieve serializability with minimal performance overhead. I will first describe a serializable multi-versioning mechanism that decouples conflicting reads and writes, and subsequently outperforms a state-of-the-art implementation of the weaker guarantee of snapshot isolation by over 3x. Next, I will describe piecewise visibility, a concurrency control mechanism that isolates requests at a finer granularity than entire transactions, which consequently permits aggressive serializable transaction interleavings and outperforms the weaker guarantee of read committed by over 3x. Finally, I will discuss ongoing work that applies deterministic transaction execution principles to address replication lag in Facebook’s production MySQL infrastructure. Bio: Jose Faleiro is a PhD candidate in computer science at Yale University. His research interests are in data management systems, multi-core systems, and distributed systems. His thesis research investigates the use of deterministic execution to enable scalable and efficient transaction processing on main-memory multi-core database systems. In addition to his academic research at Yale, Jose has worked on large-scale real world systems, including Microsoft’s Orleans cloud programming framework, and Facebook’s production MySQL infrastructure. He is the recipient of the Alan J. Perlis Fellowship at Yale, and a Microsoft Research Tech Transfer Award. He has an undergraduate degree in computer science from the Birla Institute of Technology and Science (BITS), Pilani , India.a

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Colloquium Speaker-Samira Khan, TODAY at 12:30pm
by Emily C. Lawrence 03 Apr '18

03 Apr '18

Samira Khan from the University of Virginia Tuesday, April 3, 2018 - 12:30pm Computer Science - Room 105 Host: Margaret Martonosi "Solving the DRAM Scaling Challenge" Abstract: Technology scaling of DRAM cells has enabled higher capacity memory for the last few decades. Unfortunately, DRAM cells become vulnerable to failure as they scale down to a smaller size. Enabling high-performance, energy-efficient, scalable memory systems without sacrificing the reliability is a major research challenge. My work focuses on designing a scalable memory system by rethinking the traditional assumptions in abstraction and separation of responsibilities across system layers. In this talk, I will discuss three fundamental ways to enable DRAM scaling. First, we can enable scaling by letting the manufacturers build smaller cells without providing any strict reliability guarantee. I envision manufacturers shipping DRAMs without fully ensuring correct operation, and the system being responsible for detecting and mitigating DRAM failures while operating in the field. However, designing such a system is difficult due to intermittent DRAM failures. In this talk, I will discuss a system design, capable of providing reliability guarantees even in the presence of intermittent failures. Second, we can enable high-capacity memory leveraging the emerging non-volatile memory technologies that are predicted to be more scalable. I will present my vision to redefine the hardware and operating system interface to unify memory and storage system with non-volatile memory and discuss the opportunities and challenges of such a system. Third, tolerating failures in the application can improve memory scalability. The fundamental challenge of such a system is how to assure, verify, and quantify the quality of the results. I envision a system that limits the impact of memory failures such that it is possible to statically determine the worst-case results from the maximum possible error in the input. Bio: Samira Khan is an Assistant Professor at the University of Virginia ( UVa ). Prior to joining UVa , she was a Post Doctoral Researcher at Carnegie Mellon University, funded by Intel Labs. Her research focuses on improving the performance, efficiency, and reliability of the memory system. She is the recipient of NSF CRII Award, NSF GOALI Award, and Rising Stars in EECS Award. She received her PhD from the University of Texas at San Antonio. During her graduate studies, she worked at Intel, AMD, and EPFL.

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