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Prof. Vikram Adve, U Illinois. March 21. 4pm. CS Small Auditorium.
by Margaret Martonosi 17 Mar '18

17 Mar '18

Prof. Vikram Adve from UIUC will be “in the neighborhood” next week and giving a seminar about his recent work. Please join us! Wednesday March 21, 4pm CS Small Auditorium TITLE: HPVM: Simplifying Heterogeneous Parallel Programming Prof. Vikram Adve, University of Illinois, Urbana-Champaign ABSTRACT: Heterogeneous parallel systems are attractive because they use specialized computing elements, including GPUs, vector hardware, FPGAs, and domain-specific accelerators, that can greatly improve energy efficiency, performance, or both, compared with traditional homogeneous systems. A major drawback, however, is that programming and reasoning about heterogeneous parallel systems is highly challenging for application developers, language and compiler designers, and hardware engineers. In the HPVM project, we are developing a unified parallel program representation, Heterogeneous Parallel Virtual Machine, that aims to capture the wide range of parallelism available in such systems. We use the HPVM representation for three different purposes: (1) a compiler intermediate representation (IR), (2) a virtual ISA for shipping (virtual) object code, and (3) a representation for runtime scheduling. We have implemented the HPVM IR and associated compiler tools as an extension of the LLVM compiler infrastructure. In this talk, I will describe the HPVM representation, experimental results demonstrating the ability of HPVM to achieve performance comparable to separately hand-tuned code for GPUs and vector hardware, and to enable highly flexible scheduling policies. I will conclude with a brief discussion of how well-chosen system interfaces can enable highly programmable, specialized hardware, and the influence of such interfaces on key layers of the system stack. BIO: Vikram Adve is the Donald B. Gillies Professor and Interim Head of Computer Science at the University of Illinois at Urbana-Champaign, and has affiliate appointments with the Coordinated Sciences Laboratory and the Information Trust Institute. Adve's research interests lie in developing and using compiler techniques to improve the performance, programmability and reliability of computer systems. Adve and his Ph.D. student, Chris Lattner, co-designed the LLVM Compiler Infrastructure, which enabled novel compilation capabilities for a wide range of languages. LLVM is widely used in industry today, ranging from mobile devices (e.g., in iOS and Android) to supercomputers (e.g., at Cray and NVIDIA) to data centers (e.g., at Google). Adve, Lattner and Evan Cheng received the ACM Software System Award in 2012 for co-developing LLVM (making UIUC the only University to win this Award twice: the Mosaic Web Browser won it in 1995). Adve has won a ten-year-retrospective Most Influential Paper award at CGO 2004, and distinguished paper awards at several conferences including PLDI 2005, SOSP 2007 and ICSE 2011. Adve's Ph.D. student, Robert Bocchino, won the 2010 ACM SIGPLAN Outstanding Dissertation Award and another Ph.D. student, John Criswell, won Honorable Mentions for both the 2014 ACM SIGOPS Dissertation Award and the 2014 ACM Doctoral Dissertation Award. Adve is a Fellow of the ACM and was named a University Scholar at the University of Illinois in 2015. Margaret Martonosi H. T. Adams '35 Professor of Computer Science. Director, Keller Center for Innovation in Engineering Education Princeton University ■ mrm(a)princeton.edu ■ http://www.princeton.edu/~mrm

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Colloquium Speaker-He He, Happening TODAY at 12:30
by Emily Lawrence 13 Mar '18

13 Mar '18

CS Department Colloquium Speaker He He from Stanford University Tuesday, March 13, 2018 - 12:30pm Computer Science - Room 105 Host: Barbara Engelhardt “Learning Interactive Agents” Abstract: AI has made huge advancement into our daily life and increasingly we require intelligent agents that work intimately with people in a changing environment. However, current systems mostly work in a passive mode: waiting for requests from users and processing them one at a time. An interactive agent must handle real-time, sequential inputs and actively collaborate with people through communication. In this talk, I will present my recent work addressing challenges in real-time language processing and collaborative dialogue. The first part involves making predictions with incremental inputs. I will focus on the application of simultaneous machine interpretation and show how we can produce both accurate and prompt translations. Then, I will present my work on building agents that collaborate with people through goal-oriented conversation. I will conclude by discussing future directions towards adaptive, active agents. Bio: He He is a postdoctoral researcher at Stanford University. She earned her Ph.D. in Computer Science at the University of Maryland, College Park. She is interested in natural language processing and machine learning. Her research focuses on building intelligent agents that work in a changing environment and interact with people, with an emphasis on language-related problems. Specific applications include dependency parsing, simultaneous machine interpretation, and goal-oriented dialogue. She is the recipient of the 2016 Larry S. Davis doctoral dissertation award.

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CORRECTION-Colloquium Speaker-He He still scheduled for Tuesday, 3/16
by Emily Lawrence 12 Mar '18

12 Mar '18

Correction, He He’s talk is still scheduled for TOMORROW, Tuesday, March 13, 2018 at 12:30pm barring a potential weather emergency. CS Department Colloquium Speaker He He from Stanford University Tuesday, March 13, 2018 - 12:30pm Computer Science - Room 105 Host: Barbara Engelhardt “Learning Interactive Agents” Abstract: AI has made huge advancement into our daily life and increasingly we require intelligent agents that work intimately with people in a changing environment. However, current systems mostly work in a passive mode: waiting for requests from users and processing them one at a time. An interactive agent must handle real-time, sequential inputs and actively collaborate with people through communication. In this talk, I will present my recent work addressing challenges in real-time language processing and collaborative dialogue. The first part involves making predictions with incremental inputs. I will focus on the application of simultaneous machine interpretation and show how we can produce both accurate and prompt translations. Then, I will present my work on building agents that collaborate with people through goal-oriented conversation. I will conclude by discussing future directions towards adaptive, active agents. Bio: He He is a postdoctoral researcher at Stanford University. She earned her Ph.D. in Computer Science at the University of Maryland, College Park. She is interested in natural language processing and machine learning. Her research focuses on building intelligent agents that work in a changing environment and interact with people, with an emphasis on language-related problems. Specific applications include dependency parsing, simultaneous machine interpretation, and goal-oriented dialogue. She is the recipient of the 2016 Larry S. Davis doctoral dissertation award.

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Colloquium Speaker-He He, TODAY at 12:30
by Emily C. Lawrence 12 Mar '18

12 Mar '18

CS Department Colloquium Speaker He He from Stanford University Tuesday, March 13, 2018 - 12:30pm Computer Science - Room 105 Host: Barbara Engelhardt “Learning Interactive Agents” Abstract: AI has made huge advancement into our daily life and increasingly we require intelligent agents that work intimately with people in a changing environment. However, current systems mostly work in a passive mode: waiting for requests from users and processing them one at a time. An interactive agent must handle real-time, sequential inputs and actively collaborate with people through communication. In this talk, I will present my recent work addressing challenges in real-time language processing and collaborative dialogue. The first part involves making predictions with incremental inputs. I will focus on the application of simultaneous machine interpretation and show how we can produce both accurate and prompt translations. Then, I will present my work on building agents that collaborate with people through goal-oriented conversation. I will conclude by discussing future directions towards adaptive, active agents. Bio: He He is a postdoctoral researcher at Stanford University. She earned her Ph.D. in Computer Science at the University of Maryland, College Park. She is interested in natural language processing and machine learning. Her research focuses on building intelligent agents that work in a changing environment and interact with people, with an emphasis on language-related problems. Specific applications include dependency parsing, simultaneous machine interpretation, and goal-oriented dialogue. She is the recipient of the 2016 Larry S. Davis doctoral dissertation award.

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Reminder: Colloquium Speaker-He He, tomorrow at 12:30
by Emily C. Lawrence 12 Mar '18

12 Mar '18

CS Department Colloquium Speaker He He from Stanford University Tuesday, March 13, 2018 - 12:30pm Computer Science - Room 105 Host: Barbara Engelhardt “Learning Interactive Agents” Abstract: AI has made huge advancement into our daily life and increasingly we require intelligent agents that work intimately with people in a changing environment. However, current systems mostly work in a passive mode: waiting for requests from users and processing them one at a time. An interactive agent must handle real-time, sequential inputs and actively collaborate with people through communication. In this talk, I will present my recent work addressing challenges in real-time language processing and collaborative dialogue. The first part involves making predictions with incremental inputs. I will focus on the application of simultaneous machine interpretation and show how we can produce both accurate and prompt translations. Then, I will present my work on building agents that collaborate with people through goal-oriented conversation. I will conclude by discussing future directions towards adaptive, active agents. Bio: He He is a postdoctoral researcher at Stanford University. She earned her Ph.D. in Computer Science at the University of Maryland, College Park. She is interested in natural language processing and machine learning. Her research focuses on building intelligent agents that work in a changing environment and interact with people, with an emphasis on language-related problems. Specific applications include dependency parsing, simultaneous machine interpretation, and goal-oriented dialogue. She is the recipient of the 2016 Larry S. Davis doctoral dissertation award.

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EE Faculty candidate Alexandros Daglis, Monday March 12
by Scott Karlin 09 Mar '18

09 Mar '18

EE SEMINAR SERIES Speaker: Alexandros Daglis (EPFL) Title: Network-Centric Computing for Online Services Day: Monday, March 12 , 2018 Time: 4:30 pm Room: B205 Engineering Quadrangle Host: Prof. David Wentzlaff Abstract: Modern datacenters offer an abundance of online services to billions of daily users. The most demanding online services come with tight response latency requirements, forcing service providers to keep their massive datasets memory-resident, distributed across the datacenter’s servers. Every user request accesses the memory of hundreds of servers; therefore, fast access to the aggregate memory pool is of crucial importance for service quality. The entity binding all the memory resources together is the datacenter network. Unfortunately, despite the dramatic evolution of datacenter fabrics over the past decade, networking still incurs a latency overhead of tens of microseconds to every remote memory access, making memory pooling impractical. In this talk, I will propose a holistic network-centric system redesign to enable memory pooling in future datacenters, which includes (i) a specialized lightweight network stack; (ii) on-chip integration of the network interface logic; and (iii) new network operations with richer, end-to-end semantics. I will highlight the role and demonstrate the effect of each of these three key features with systems built throughout my dissertation. Bio: Alexandros (Alex) Daglis is a sixth-year PhD student at EPFL, advised by Prof. Babak Falsafi and Prof. Edouard Bugnion. His research interests lie in rack-scale computing and datacenter architectures. Alex advocates tighter integration and co-design of network and compute resources as a necessary approach to tackling the performance overheads associated with inter-node communication in scale-out architectures. He has been a founding member of Scale-Out NUMA, an architecture, programming model, and communication protocol for low-latency, distributed in-memory processing. Scale-Out NUMA has been prototyped and awarded a US patent. As an intern at HP Labs, Alex worked on the design of The Machine’s unique memory subsystem. More details can be found on his CV .

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Colloquium Speaker-He He, Tuesday, March 13
by Emily C. Lawrence 07 Mar '18

07 Mar '18

CS Department Colloquium Speaker He He from Stanford University Tuesday, March 13, 2018 - 12:30pm Computer Science - Room 105 Host: Barbara Engelhardt “Learning Interactive Agents” Abstract: AI has made huge advancement into our daily life and increasingly we require intelligent agents that work intimately with people in a changing environment. However, current systems mostly work in a passive mode: waiting for requests from users and processing them one at a time. An interactive agent must handle real-time, sequential inputs and actively collaborate with people through communication. In this talk, I will present my recent work addressing challenges in real-time language processing and collaborative dialogue. The first part involves making predictions with incremental inputs. I will focus on the application of simultaneous machine interpretation and show how we can produce both accurate and prompt translations. Then, I will present my work on building agents that collaborate with people through goal-oriented conversation. I will conclude by discussing future directions towards adaptive, active agents. Bio: He He is a postdoctoral researcher at Stanford University. She earned her Ph.D. in Computer Science at the University of Maryland, College Park. She is interested in natural language processing and machine learning. Her research focuses on building intelligent agents that work in a changing environment and interact with people, with an emphasis on language-related problems. Specific applications include dependency parsing, simultaneous machine interpretation, and goal-oriented dialogue. She is the recipient of the 2016 Larry S. Davis doctoral dissertation award.

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Colloquium Speaker-Brian Smith, TODAY at 12:30
by Emily C. Lawrence 05 Mar '18

05 Mar '18

CS Department Colloquium Speaker Brian Smith, Columbia University Monday, March 5, 2018 - 12:30pm Computer Science - Room 105 Host: Prof. Arvind Narayanan "Analyzing Human Behavior to Make Computing More Useful" Abstract: Computing devices play a more significant role in our lives than ever before, so it is more important than ever for them to understand who we are as people on a deep level. But many of today’s user interfaces do not have such an understanding: rather, their designs are based on developers’ intuitions alone. This often leads to mismatches between how useful computing systems promise to be and how useful they are in practice. In this talk, I will show how analyzing and even modeling human behavior can unlock insights that help resolve such mismatches, resulting in systems that are significantly more useful than what they would otherwise be. I will discuss four results that I have worked on: (1) a system for interacting with objects by looking at them, (2) a system for typing on smartphones more quickly and with much fewer errors, (3) a system that can recognize players and recommend video game levels from controller inputs alone, and (4) a system that makes it possible for people who are blind to play the same types of racing games that sighted players can play with the same speed and sense of control that sighted players have. Bio: Brian A. Smith is a Ph.D. candidate in Computer Science at Columbia University, where he is a member of the Computer Vision Laboratory and the Computer Graphics and User Interfaces Laboratory. His research is in human–computer interaction, accessibility, and game design, and focuses on analyzing human behavior to make computing more useful. He has been awarded the NDSEG Fellowship, an NSF IGERT data science traineeship, and Columbia Engineering’s Extraordinary Teaching Assistant Award. He received his MS and BS in Computer Science from Columbia University.

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Reminder: Colloquium Speaker-Brian Smith, tomorrow at 12:30
by Emily C. Lawrence 04 Mar '18

04 Mar '18

CS Department Colloquium Speaker Brian Smith, Columbia University Monday, March 5, 2018 - 12:30pm Computer Science - Room 105 Host: Prof. Arvind Narayanan "Analyzing Human Behavior to Make Computing More Useful" Abstract: Computing devices play a more significant role in our lives than ever before, so it is more important than ever for them to understand who we are as people on a deep level. But many of today’s user interfaces do not have such an understanding: rather, their designs are based on developers’ intuitions alone. This often leads to mismatches between how useful computing systems promise to be and how useful they are in practice. In this talk, I will show how analyzing and even modeling human behavior can unlock insights that help resolve such mismatches, resulting in systems that are significantly more useful than what they would otherwise be. I will discuss four results that I have worked on: (1) a system for interacting with objects by looking at them, (2) a system for typing on smartphones more quickly and with much fewer errors, (3) a system that can recognize players and recommend video game levels from controller inputs alone, and (4) a system that makes it possible for people who are blind to play the same types of racing games that sighted players can play with the same speed and sense of control that sighted players have. Bio: Brian A. Smith is a Ph.D. candidate in Computer Science at Columbia University, where he is a member of the Computer Vision Laboratory and the Computer Graphics and User Interfaces Laboratory. His research is in human–computer interaction, accessibility, and game design, and focuses on analyzing human behavior to make computing more useful. He has been awarded the NDSEG Fellowship, an NSF IGERT data science traineeship, and Columbia Engineering’s Extraordinary Teaching Assistant Award. He received his MS and BS in Computer Science from Columbia University.

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Jieming Mao will present a pre-FPO talk on Tuesday, March 6, 2018 at 2:00 pm in CS 402
by Barbara A. Mooring 28 Feb '18

28 Feb '18

Jieming Mao will present a pre-FPO talk on Tuesday, March 6, 2018 at 2:00 pm in CS 402. Members of his Committee are as follows: Mark Braverman (Adviser) - Princeton University Matt Weinberg (Reader) - Princeton University Bernard Chazelle (Reader) - Princeton University Ran Raz (Examiner) - Princeton University Elad Hazan (Examiner) - Princeton University All are welcome to attend. ================ Title: Algorithms in Strategic or Noisy Environments Abstract: Algorithms are often used in strategic or noisy environments. These factors can significantly affect the performance of algorithms. My research aims to design algorithms that are robust against such factors.In the first half of the talk, I will talk about no-regret learning algorithms in strategic environments. We study a specific setting in which a fully strategic seller repeatedly sells goods to a buyer who no-regret learns over time. We give a full characterization of whether the seller can extract additional revenue from the buyer. In the second half of the talk, I will talk about parallel algorithms for finding top-k items with noisy pairwise comparisons. The problem has applications in crowdsourcing, peer grading and recommender systems. We show tight trade-offs between sample complexity and round complexity.

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