קולוקוויום וסמינרים

כדי להצטרף לרשימת תפוצה של קולוקוויום מדעי המחשב, אנא בקר בדף מנויים של הרשימה.

קולוקוויום וסמינרים בקרוב

  • ceClub: Thunderstrike: EFI firmware bootkits for Apple MacBooks

    דובר:
    טראמל האדסון (TWO SIGMA)
    תאריך:
    יום שני, 25.5.2015, 11:30
    מקום:
    חדר 337, בניין טאוב למדעי המחשב

    In this presentation we demonstrate the installation of persistent firmware modifications into the EFI boot ROM of Apple's popular MacBooks. The bootkit can be easily installed by an evil-maid via the externally accessible Thunderbolt ports and can survive reinstallation of OSX as well as hard drive replacements. Once installed, it can prevent software attempts to remove it and could spread virally across air-gaps by infecting additional Thunderbolt devices.

    Bio:
    Trammell Hudson works at Two Sigma Investments on security, networking and distributed computation projects. Prior to coming to New York, he worked for many years at Sandia National Labs on message passing and operating systems for Top500 parallel supercomputers. More info: http://twosigma.com and https://trmm.net/

  • CGGC Seminar: Geometric Tools for Isogeometric Analysis

    דובר:
    פאדי מצראווי (מדעי המחשב, טכניון)
    תאריך:
    יום שני, 25.5.2015, 14:00
    מקום:
    טאוב 401

    Isogeometric analysis (IGA) has brought new problems to the field of Computer Aided Geometry for Design (CAGD); in return the latter brings to the computation of solution of PDEs new methods and algorithms. The present work develops both aspects. In the first one, IGA has renewed the interest for trivariate spline objects and their manipulation: construction of multi patch primitives that are C0 or G1, construction of trivariate splines resulting from classic CSG operations such as extrusion, sweep, ruled volume, and volume of revolution. One must then analyse the singularities that these constructors may carry, as well as the possibility to get non-singular parameterisations. Conversely, IGA implies the intrinsic usage of CAD elements. Hence (new) tools from geometric modelling can naturally be introduced to define new algorithms and higher precision computations or higher order approximations of domain boundaries defined by trimmed surfaces. This can beperformed by untrimming, i.e. precisely representing the trimmed surface by a set of higher order tensor product splines. Thus, function evaluations on such boundaries can be very accurate: by an up to machine precision determination of the exact position, as well normals and tangents (an important property for handling some boundary conditions such as flux preserving for incompressible fluid) and obviously integral properties.

    The full ability of geometric modelling and IGA is used to address several key issues in the context of large deformation contact analysis. With the aid of unique precise analysis tools available from geometric modelling, we can investigate surface-to-surface algorithms, with reaction forces defined on medial surfaces or integral properties such as penetration area/volume rather than contact boundaries of a slave body, as is commonplace in currently available methods. As for the medial axis, we similarly present capabilities to employ precise algorithms to directly compute Bisectors and Voronoi cells of splines.

    The algorithms developed are included in the Irit geometric modelling library, and numerous examples are given using GuIrit, its graphical interface.

  • Pixel Club: Micron level NMR Imaging

    דובר:
    ניר סוכן (אונ' תל-אביב)
    תאריך:
    יום שלישי, 26.5.2015, 11:30
    מקום:
    חדר 1061, בניין מאייר, הפקולטה להנדסת חשמל

    We will give a new derivation of the Bloch-Torrey equation that governs the behaviour of water molecules in porous media and biological tissues. We will show that this new derivation reveals new term that was ignored in the past. We further show how one can solve this equation analytically for few specific geometries. These solutions enables us to solve the inverse problem of finding the geometric parameters at a micron level from NMR measurements.

    These predictions are verified in many experiments paving the way to new MRI modality.

  • Moore's Law: Yesterday, Today and Tomorrow

    Moore's Law: Yesterday, Today and Tomorrow

    דובר:
    מרק בוהר (אינטל)
    תאריך:
    יום שלישי, 26.5.2015, 14:30
    מקום:
    אודיטוריום 2 בניין טאוב למדעי המחשב
    קישור:
    http://www.cs.technion.ac.il/~colloq/20150526_14_30_Bohr.html

    Our industry has reaped the benefits of Moore's Law for 50 years now, making integrated circuits that have grown from tens to billions of transistors and performing an increased range of functions from memory to logic to signal processing. Scaled transistors have provided significant improvements in performance and low power, but the main benefit of scaling has been lower cost per transistor. As we scale to 10 nm and below it is becoming increasingly difficult to achieve traditional improvements in performance, power and cost due to inherent leakage and resistance increases of scaled devices, and the increased cost of added masking layers. Moore's Law will continue beyond 10 nm by developing new materials and device structures to meet performance and power requirements. The focus of future scaling will expand from traditional device scaling on single chips to scaling larger systems using multiple chips in dense 3-dimensional packages. To continue Moore's Law in the coming decades will require collaborative research between industry and academic institutions.

    Short Bio:
    Mark Bohr is an Intel Senior Fellow and Director of Process Architecture and Integration. He joined Intel in 1978 after graduating from the University of Illinois and is a member of the Logic Technology Development group located in Hillsboro, Oregon. Mark is currently directing early process development activities for Intel's 7 nm generation logic technology. He is an IEEE Fellow, recipient of the 2003 IEEE Andrew S. Grove Award, recipient of the 2012 IEEE Jun-ichi Nishizawa Medal, and a member of the U.S. National Academy of Engineering. He holds 77 patents in the area of integrated circuit processing and has authored or co-authored 50 published papers.

    Desserts will be served from 14:15
    Lecture starts at 14:30.

  • יריד פרוייקטים ראשון במדעי המחשב

    יריד פרוייקטים ראשון במדעי המחשב

    תאריך:
    יום שלישי, 26.5.2015, 15:30
    מקום:
    בניין טאוב למדעי המחשב

    אנו שמחים להזמינכם ליריד פרוייקטים ראשון בפקולטה למדעי המחשב אשר יתקיים ביום ג', 26 במאי 2015, בין השעות 15:30-18:00, בלובי בניין טאוב למדעי המחשב.
    .
    באירוע, בו יתארחו נציגים בכירים מהתעשייה ומחברות מובילות בהי-טק, יציגו סטודנטים לתואר ראשון פרוייקטים שפיתחו במהלך לימודיהם.

    האירוע הוא הזדמנות מצויינת הן עבור התעשייה להיחשף להבטים יישומיים שנלמדים במהלך התואר, ולהכיר את יכולות הפיתוח והיישום של הסטודנטים, לטובת שיתופי פעולה עתידיים, הן עבור סטודנטים צעירים לגלות התנסויות עתידיות הצפויות להם במהלך לימודיהם.

    ההשתתפות באירוע אינה כרוכה בתשלום אך דורשת הרשמה מוקדמת.

    כולם מוזמנים!

  • ceClub: Coded Retransmission in Wireless Networks Via Abstract MDPs

    דובר:
    מארק שיפרין (אונ' בן-גוריון)
    תאריך:
    יום רביעי, 27.5.2015, 11:30
    מקום:
    חדר 861, בניין מאייר, הפקולטה להנדסת חשמל

    We consider a transmission scheme with a single transmitter and multiple receivers over a faulty broadcast channel. For each receiver, the transmitter has a unique infinite stream of packets, and its goal is to deliver them at the highest throughput possible. While such multiple-unicast models are unsolved in general, several network coding based schemes were suggested. In such schemes, the transmitter can either send an uncoded packet, or a coded packet which is a function of a few packets. Sent packets can be received by the designated receiver (with some probability) or heard and stored by other receivers. Two functional modes are considered; the first presumes that the storage time is unlimited, while in the second it is limited by a given Time To Live (TTL) parameter. We model the transmission process as an infinite horizon Markov Decision Process (MDP). Since the large state space renders exact solutions computationally impractical, we introduce policy restricted and induced MDPs with significantly reduced state space, which with properly chosen reward have equal optimal value function. We then derive a reinforcement learning algorithm, which approximates the optimal strategy and significantly improves over uncoded schemes. The algorithm adapts to the packet loss rates, unknown in advance, attains high gain over the uncoded setup and is comparable with the upper bound by Wang, derived for a much stronger coding scheme.

    Bio:
    Mark Shifrin received his PHD from EE, Technion, in 2014. He is recipient of Kreitman postdoctoral fellowship in Ben Gurion university, where he currently pursues topics in wireless communication using stochastic control methods, at department of Communication Systems Engineering.

  • The Ring of Gyges: Using Smart Contracts for Crime

    דובר:
    Ari Juels - COLLOQUIUM LECTURE
    תאריך:
    יום חמישי, 28.5.2015, 14:30
    מקום:
    חדר 337-8 טאוב.
    קישור:
    http://www.cs.technion.ac.il/~colloq/20150528_14_30_Jules.html
  • Streaming Property Testing of Visibly Pushdown Languages

    דובר:
    Michel de Rougemont - SPECIAL LECTURE - Note unusual hour
    תאריך:
    יום חמישי, 28.5.2015, 15:30
    מקום:
    חדר 337-8 טאוב.
    קישור:
    http://www.cs.technion.ac.il/~colloq/20150528_15_30_Rougement.html
  • CGGC Seminar: Dynamic Obstacle Avoidance using Convex Methods

    דובר:
    אברהם סטיפל (מדעי המחשב, טכניון)
    תאריך:
    יום ראשון, 31.5.2015, 15:30
    מקום:
    טאוב 401

    We take a new approach to motion planning specifically designed for handling mobile obstacles. Previous methods are modified versions of the algorithms for static obstacles, but with speed-ups designed to ensure real-time operation. Because of this logic, each iteration requires a complete reconstruction of the path, based on the new locations of the robot and the obstacle. Ideally, the algorithm would consist of faster iterations that create a complete approximate path, but can re-use information so that our approximation improves during each iteration.

    We begin by performing a locally-optimal convex decomposition of the freespace. At each iteration, we update the decomposition so that concave regions are split, but neighboring regions that can be fused into a larger convex region are fused. We then construct a piecewise-linear path that passes from the robot to the target, such that the joins are on edges created by the convex decomposition. We then augment the path to a smooth curve with bounded curvature; the specific form of curve is not relevant, but we present a number of different methods. Once an initial path is constructed, we iteratively improve our path while updating the convex decomposition. To do so, we remove or add linear segments as the convex decomposition demands. We then adjust the locations of the segments joins on the dividing edge segments, so that the adjusted path is an approximation of the shortest path.

    We show that our method is computationally faster than pre-existing algorithms. Furthermore, we show that because of the structure of the algorithm we can more easily determine if the entire path avoids obstacles.

    This talk summarizes the M.Sc. research of the speaker under the supervision of Prof. Gill Barequet

  • Dynamic Obstacle Avoidance using Convex Methods

    דובר:
    אברהם סטיפל, הרצאה סמינריונית למגיסטר
    תאריך:
    יום ראשון, 31.5.2015, 15:30
    מקום:
    טאוב 401
    מנחה:
    Prof. G. Barequet

    We take a new approach to motion planning specifically designed for handling mobile obstacles. Previous methods are modified versions of the algorithms for static obstacles, but with speed-ups designed to ensure real-time operation. Because of this logic, each iteration requires a complete reconstruction of the path, based on the new locations of the robot and the obstacle. Ideally, the algorithm would consist of faster iterations that create a complete approximate path, but can re-use information so that our approximation improves during each iteration. We begin by performing a locally-optimal convex decomposition of the freespace. At each iteration, we update the decomposition so that concave regions are split, but neighboring regions that can be fused into a larger convex region are fused. We then construct a piecewise-linear path that passes from the robot to the target, such that the joins are on edges created by the convex decomposition. We then augment the path to a smooth curve with bounded curvature; the specific form of curve is not relevant, but we present a number of different methods. Once an initial path is constructed, we iteratively improve our path while updating the convex decomposition. To do so, we remove or add linear segments as the convex decomposition demands. We then adjust the locations of the segments joins on the dividing edge segments, so that the adjusted path is an approximation of the shortest path. We show that our method is computationally faster than pre-existing algorithms. Furthermore, we show that because of the structure of the algorithm we can more easily determine if the entire path avoids obstacles.

  • Processing Real-time Data Streams on GPU-Based Systems

    דובר:
    אורי ורנר, הרצאה סמינריונית לדוקטורט
    תאריך:
    יום רביעי, 3.6.2015, 11:30
    מקום:
    טאוב 337 (CeClub)
    מנחה:
    Prof. Assaf Schuster and Prof. Avi Mendelson

    Real-time stream processing of Big Data has an increasing demand in modern data centers. There, a continuous torrent of data, created from different streaming data-sources like social networks, video streams, and financial markets, is being processed and analyzed to produce valuable insights about its content, and, in some cases, their value has an expiration date. For example, in a silicon-wafer production inspection system, dozens of high-resolution cameras scan the wafer and generate high-rate streams of images, where defects as small as a pixel and even smaller are detected using image processing algorithms. The inspection is a computationally intensive task that must adhere to strict processing time limitations in order to keep up with the production line. High-end computing platforms, packed with CPUs and compute accelerators, are being used to deal with the large processing need. Optimizing such systems is a very challenging task because they are heterogeneous in both computation and communication. In this talk, I will present my PhD research work on the problem of processing multiple data streams with hard processing-latency bounds on multi-GPU compute nodes. The talk will describe the challenges in work distribution and communication scheduling in such a system, and present new methods that achieve higher utilization of the resources, while guaranteeing hard real-time compliance. The generalization of the previously discussed problems leads to an important new class of scheduling problems where processors affect each other's speed. To demonstrate its usefulness, a problem from this class is used to develop an efficient new scheduler that minimizes the makespan of compute jobs on Intel CPUs.

  • Algorithmic Exam Generation

    דובר:
    עומר גייגר, הרצאה סמינריונית למגיסטר
    תאריך:
    יום רביעי, 3.6.2015, 14:00
    מקום:
    טאוב 601
    מנחה:
    Prof. Shaul Markovitch

    Given a class of students, and a pool of questions in the domain of study, what subset will constitute a ``good'' exam? Millions of educators are dealing with this difficult problem worldwide, yet the task of composing exams is still performed manually. In this work we present a novel algorithmic framework for exam composition. Our framework requires two input components: a student population represented by a distribution over a set of overlay models, each consisting of a set of mastered abilities, or actions; and a that, given any two student models, defines which should be graded higher. To determine the performance of a student model on a potential question, we test whether it satisfies a disjunctive action landmark, i.e., whether its abilities are sufficient to follow at least one solution path. Based on these, we present a novel utility function for evaluating exams. An exam is highly evaluated if it is expected to order the student population with high correlation to the target order. The merit of our algorithmic framework is exemplified with real auto-generated questions in the domain of middle-school algebra.

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