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CS195T: Introduction to Graduate Computer Science;CS195T:Introduction to Graduate Computer Science;Fall 1996 (47865); Lecture: Monday, 12:00 - 1:00, in TAY 2.106.; Instructor: Robert Blumofe; Office: Taylor 4.118; Phone: 471-9557; Email: rdb@cs.utexas.edu; Office hours: Thursday 1:30 - 3:30,;but feel free to stop by any time.;This is a one-semester seminar course that can only be taken on a;pass/fail basis. For graduate students, the course is CS 195T:;Introduction to Graduate Computer Science. For undergraduates,;the course is CS 178: Undergraduate Topics in Computer Science;(Honors) (47730). To receive credit for the course, a student must be;registered for the course, and attend at least 11 of the 13 lectures.;Schedule;Speaker;Title;September 9;Dan Miranker;Alamo: The Net as a Data Warehouse;September 16;Ben Kuipers;The Spatial Semantic Hierarchy for Human;and Robot Cognitive Maps;September 23;Robert Blumofe;Cilk and Cilk-NOW: Adaptive and Reliable;Parallel Computing on Networks of Workstations;September 30;Risto Miikkulainen;Learning Sequential Decision Tasks Through;Symbiotic Evolution of Neural Networks;October 7;Vladimir Lifschitz;Mathematical Principles of Logic Programming;October 14;Paul Wilson;Extensible Languages, Open Compilers,;and Reflection;October 21;Ray Mooney;Learning to Process Natural Language Using;Inductive Logic Programming;October 28;Mike Dahlin;Distributed I/O: from Clusters to Internets;November 4;Gordon Novak;Software Reuse by Specialization of Generic;Procedures through Views;November 11;Vijaya Ramachandran;The Design and Evaluation of Parallel;Algorithms;November 18;Lorenzo Alvisi;Lighweight fault-tolerance;November 25;Calvin Lin;Adaptive Libraries and High Level Optimization;December 2;Greg Plaxton;Analysis of Algorithms;Lighweight fault-tolerance;Lorenzo Alvisi;Distributed systems have moved beyond the confines of academia and;research labs and are revolutionizing the way in which businesses,;governmental organizations, and simple citizens are processing and;collecting information. Current technological trends promise to;dramatically increase the pace of this revolution by enabling the;design of highly cooperative distributed applications that go beyond;the client-server paradigm to harness the computational power of;distributed systems.;In this new environment, the scope and emphasis of fault-tolerant;techniques are about to undergo dramatic changes. Fault-tolerance will;cease to be an expensive feature required by a handful of applications;to tolerate exotic failures. To the users of a highly distributed;information infrastructure, fault-tolerance will translate to a;competitive advantage, guaranteeing reliable access to critical;information.;In this talk we will explore a new way to design and engineer;fault-tolerant solutions, which we call lightweight fault-tolerance.;The goals of lightweight fault-tolerance are:;To require few dedicated resources and have a negligible;impact on performance during failure-free executions.;To scale its cost depending on the severity and number of;failures that need to be tolerated.;To integrate with applications in a way transparent to the;application programmer.;To enable and support emerging applications that will communicate;through messages as well as files.;To address software-generated faults effectively.;Cilk and Cilk-NOW: Adaptive and Reliable Parallel Computing on;Networks of Workstations;Robert Blumofe;This presentation overviews Cilk (pronounced;"silk"), an algorithmic parallel multithreaded language, and;Cilk-NOW, a runtime system that supports a functional;subset of Cilk on networks of workstations. Cilk-NOW provides;"adaptive parallelism" and fault tolerance tranparently to;user programs. Adaptive parallelism means that the set of;workstations on which a Cilk program runs can grow and shrink;dynamically depending on the availability of idle workstations and on;the amount of parallelism within the program. In addition, a Cilk;program can continue execution even if one or more of its workstations;crashes, because the Cilk-NOW runtime system automatically detects and;recovers from such failures. The presentation includes a live;demonstration.;Distributed I/O: from Clusters to Internets;Mike Dahlin;This presentation gives an overview of current issues in;distributed file system I/O. Technology trends and new applications;motivate more aggressive cluster and wide area network I/O systems. In;clusters, fast networks allow machines to cooperate closely to service;I/O requests. The xFS file system uses close cooperation among nodes;to provide better performance and availability than a single central;server. In wide area networks, the challenge is to provide good;performance, availability, and consistency despite limited network;performance and node or network failures. The wFS file system project;will explore these issues.;The Spatial Semantic Hierarchy for Human and Robot Cognitive Maps;Benjamin Kuipers;Human cognitive maps rely on several different representations for;large-scale space, each with its own ontology. Similarly, a variety;of different approaches have been proposed for robot exploration and;mapping of unknown environments. We cast these diverse;representations into a natural structure that we call the Spatial;Semantic Hierarchy (SSH), in which the objects, relations, and;assumptions at each level are abstracted from the levels below.;Each level of the SSH has its own mathematical foundation. The;control level allows the robot and its environment to be formalized as;a continuous dynamical system, whose stable equilibrium points can be;abstracted to a discrete set of "distinctive states.";Trajectories linking these states can be abstracted to actions, giving;a discrete causal graph representation of the state space. The causal;graph of states and actions can in turn be abstracted to a topological;network of places and paths. Local metrical models, such as occupancy;grids, of neighborhoods of places and paths can then be built on the;framework of the topological network without their usual problems of;global consistency.;Mathematical Principles of Logic Programming;Vladimir Lifschitz;Logic programming, as well as its sister approach, functional;programming, is based on the view that a computer program does not;need to contain any explicit operational instructions. Instead, it;can simply provide a set of facts about the problem that is sufficient;to solve it. Such a "declarative" program can be executed;using methods of automated reasoning. Prolog is the best known logic;programming language.;The mathematical theory of logic programming is concerned with;defining the semantics of logic programming languages, describing the;reasoning algorithms used to implement them, and investigating the;soundness of these algorithms.;Adaptive Libraries and High Level Optimization;Calvin Lin;This talk describes a new approach to building software libraries.;By making libraries that can adapt---in both their implementation and;their interfaces---to different application needs and different;hardware platforms, we can produce libraries that are more efficient;and more widely usable. We describe a new framework for building such;libraries, we describe three planned experiments that apply these;techniques to libraries for parallel scientific computation, and we;explain how our approach facilitates high level optimizations.;Learning Sequential Decision Tasks Through Symbiotic Evolution of;Neural Networks;Risto Miikkulainen;A novel reinforcement learning method called SANE;(Symbiotic, Adaptive Neuro-Evolution) evolves a population of neurons;through genetic algorithms to form a neural network for a given task.;Symbiotic evolution promotes both cooperation and specialization in;the population, which results in a fast, efficient genetic search and;discourages convergence to suboptimal solutions. SANE is able to;extract domain-specific information even under sparse reinforcement,;which makes it an effective approach to a broad range of sequential;decision tasks such as robot control, game playing, and resource;management.;Alamo: The Net as a Data Warehouse;Dan Miranker;The Alamo effort is directed at intra-net development, and;inter-net users who can enumerate interesting sites and data;sources. The goal is to integrate the data sources and provide the;user with the illusion of a single virtual database, followed by;query, analysis and presentation tools.;Central to the Alamo architecture is a software bus called the;Abstract Search Machine (ASM). The ASM is a CORBA compliant interface;that provides a uniform interface to heterogeneous data;sources. Beyond simple data access, the ASM embodies a higher level of;abstraction enabling the efficient coding of clever search algorithms;and separating and isolating system concerns, including buffering and;data prefetch.;The broad claim is that high performance, often optimal,;implementations of advanced database facilities such as an;object-oriented query engine, a deductive inference engine, an active;database engine and data mining facilities can all be constructed;using the ASM as a common interface.;Finally, since the output of each of these advanced database;facilities can themselves serve as data sources, the components of the;Alamo architecture can be composed to resolve higher level data;integration problems. In particular we anticipate using the elements;of Alamo itself to represent meta-data and resolve both structural and;semantic conflicts among the data sources. Ultimately, further;compositions will embody complex knowledge-bases and be able to answer;high-level queries.;Learning to Process Natural Language Using Inductive Logic;Programming;Raymond J. Mooney;Inductive Logic Programming (ILP) addresses the problem of learning;Prolog programs from examples. The representational power of;first-order logic offers advantages over standard machine learning;methods constrained to use fixed-length feature vectors. We are;applying ILP methods to natural-language learning where we believe;this richer representation offers important advantages. We have;developed an ILP system, CHILL, for learning deterministic parsers;from a corpus of parsed sentences. CHILL obtains superior results on;several artificial corpora previously used to test neural-network;methods, and encouraging results on the more realistic ATIS corpus of;airline queries. CHILL has also been used to the automatically;develop a complete natural-language interface that translates English;database queries into executable Prolog form, producing a more;accurate parser than a hand-built system for querying a small;geographic database. We have also developed an ILP system, FOIDL,;which has been applied to learning the past tense of English,;surpassing the previous results of neural-network and decision-tree;methods on this problem.;Software Reuse by Specialization of Generic Procedures through;Views;Gordon S. Novak Jr.;Software reuse is clearly a good idea, but it is difficult to;achieve in practice: if your data does not fit the assumptions of the;software, reusing the software will be difficult. In our approach,;views describe how application data types implement the abstract types;used in generic procedures. A compilation process can specialize a;generic procedure to produce a version that is customized for the;application data. Graphical user interfaces make it easy to specify;views. An Automatic Programming Server has been implemented on the;World Wide Web; it will write specialized programs for the user, in a;desired language, and serve the source code to the user as a file.;Analysis of Algorithms;Greg Plaxton;A major focus of theoretical computer science is the design and;analysis of asymptotically efficient algorithms;(sequential/parallel/distributed, deterministic/randomized) for;specific computational problems. In this research area, it is not;uncommon to come across well-written papers in which, informally: (i);the main underlying ideas are conceptually straightforward, (ii) the;formal presentation is surprisingly lengthy, and (iii) most of the;formalism deals with minor side-issues and special cases that have;little or nothing to do with the main underlying ideas. In such;papers, there seems to be a significant gap between the conceptual and;formal difficulty of the algorithm being presented. Are such gaps;inherent, or is conventional mathematical notation simply inadequate;for succinctly formalizing certain conceptually straightforward;algorithmic ideas?;In this talk, I will describe a notation for asymptotic analysis,;called $O_i$-notation, that significantly reduces the;"conceptual-to-formal gap" associated with a non-trivial;class of algorithms. As a concrete example, I consider the analysis;of the well-known linear-time selection algorithm due to Blum, Floyd,;Pratt, Rivest, and Tarjan.;The Design and Evaluation of Parallel Algorithms;Vijaya Ramachandran;The design and analysis of efficient parallel algorithms for;combinatorial problems has been an area of extensive study in recent;years, and a large number of algorithms have been developed on the;abstract PRAM model of parallel computation. In this talk we will;describe some of our work in the design of efficient parallel;algorithms, and our experience with implementing and evaluating these;algorithms on a massively parallel machine (Maspar MP-1). We will then;describe a "queuing" variant of the PRAM model, which we;propose as a more appropriate model for currently available parallel;shared-memory machines than traditional PRAM models.;Extensible Languages, Open Compilers, and Reflection;Paul Wilson;Extensible languages allow interesting new features to be added to;a language portably, from within the language itself.;Open compilers allow fairly easy modification of compilers to add;new features, analyses, and optimizations.;Reflection allows a program to examine a representation of;interesting parts of itself, and affect its own structure;accordingly.;I'll discuss these things, why they're useful for building modular,;portable, and adapatable software. I'll also discuss our recent work;on the RScheme compiler, an open compiler for an extensible;language.;Last modified: November 15, 1996;Robert Blumofe;rdb@cs.utexas.edu;