15 resultados para Computers

em Massachusetts Institute of Technology


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Garbage collector performance in LISP systems on custom hardware has been substantially improved by the adoption of lifetime-based garbage collection techniques. To date, however, successful lifetime-based garbage collectors have required special-purpose hardware, or at least privileged access to data structures maintained by the virtual memory system. I present here a lifetime-based garbage collector requiring no special-purpose hardware or virtual memory system support, and discuss its performance.

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This technical report describes a new protocol, the Unique Token Protocol, for reliable message communication. This protocol eliminates the need for end-to-end acknowledgments and minimizes the communication effort when no dynamic errors occur. Various properties of end-to-end protocols are presented. The unique token protocol solves the associated problems. It eliminates source buffering by maintaining in the network at least two copies of a message. A token is used to decide if a message was delivered to the destination exactly once. This technical report also presents a possible implementation of the protocol in a worm-hole routed, 3-D mesh network.

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Computational models are arising is which programs are constructed by specifying large networks of very simple computational devices. Although such models can potentially make use of a massive amount of concurrency, their usefulness as a programming model for the design of complex systems will ultimately be decided by the ease in which such networks can be programmed (constructed). This thesis outlines a language for specifying computational networks. The language (AFL-1) consists of a set of primitives, ad a mechanism to group these elements into higher level structures. An implementation of this language runs on the Thinking Machines Corporation, Connection machine. Two significant examples were programmed in the language, an expert system (CIS), and a planning system (AFPLAN). These systems are explained and analyzed in terms of how they compare with similar systems written in conventional languages.

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Scientists are faced with a dilemma: either they can write abstract programs that express their understanding of a problem, but which do not execute efficiently; or they can write programs that computers can execute efficiently, but which are difficult to write and difficult to understand. We have developed a compiler that uses partial evaluation and scheduling techniques to provide a solution to this dilemma.

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Early and intermediate vision algorithms, such as smoothing and discontinuity detection, are often implemented on general-purpose serial, and more recently, parallel computers. Special-purpose hardware implementations of low-level vision algorithms may be needed to achieve real-time processing. This memo reviews and analyzes some hardware implementations of low-level vision algorithms. Two types of hardware implementations are considered: the digital signal processing chips of Ruetz (and Broderson) and the analog VLSI circuits of Carver Mead. The advantages and disadvantages of these two approaches for producing a general, real-time vision system are considered.

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As the size of digital systems increases, the mean time between single component failures diminishes. To avoid component related failures, large computers must be fault-tolerant. In this paper, we focus on methods for achieving a high degree of fault-tolerance in multistage routing networks. We describe a multipath scheme for providing end-to-end fault-tolerance on large networks. The scheme improves routing performance while keeping network latency low. We also describe the novel routing component, RN1, which implements this scheme, showing how it can be the basic building block for fault-tolerant multistage routing networks.

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Computers and Thought are the two categories that together define Artificial Intelligence as a discipline. It is generally accepted that work in Artificial Intelligence over the last thirty years has had a strong influence on aspects of computer architectures. In this paper we also make the converse claim; that the state of computer architecture has been a strong influence on our models of thought. The Von Neumann model of computation has lead Artificial Intelligence in particular directions. Intelligence in biological systems is completely different. Recent work in behavior-based Artificial Intelligenge has produced new models of intelligence that are much closer in spirit to biological systems. The non-Von Neumann computational models they use share many characteristics with biological computation.

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The development of increasingly sophisticated and powerful computers in the last few decades has frequently stimulated comparisons between them and the human brain. Such comparisons will become more earnest as computers are applied more and more to tasks formerly associated with essentially human activities and capabilities. The expectation of a coming generation of "intelligent" computers and robots with sensory, motor and even "intellectual" skills comparable in quality to (and quantitatively surpassing) our own is becoming more widespread and is, I believe, leading to a new and potentially productive analytical science of "information processing". In no field has this new approach been so precisely formulated and so thoroughly exemplified as in the field of vision. As the dominant sensory modality of man, vision is one of the major keys to our mastery of the environment, to our understanding and control of the objects which surround us. If we wish to created robots capable of performing complex manipulative tasks in a changing environment, we must surely endow them with (among other things) adequate visual powers. How can we set about designing such flexible and adaptive robots? In designing them, can we make use of our rapidly growing knowledge of the human brain, and if so, how at the same time, can our experiences in designing artificial vision systems help us to understand how the brain analyzes visual information?

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This report addresses the problem of fault tolerance to system failures for database systems that are to run on highly concurrent computers. It assumes that, in general, an application may have a wide distribution in the lifetimes of its transactions. Logging remains the method of choice for ensuring fault tolerance. Generational garbage collection techniques manage the limited disk space reserved for log information; this technique does not require periodic checkpoints and is well suited for applications with a broad range of transaction lifetimes. An arbitrarily large collection of parallel log streams provide the necessary disk bandwidth.

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Nonlinear multivariate statistical techniques on fast computers offer the potential to capture more of the dynamics of the high dimensional, noisy systems underlying financial markets than traditional models, while making fewer restrictive assumptions. This thesis presents a collection of practical techniques to address important estimation and confidence issues for Radial Basis Function networks arising from such a data driven approach, including efficient methods for parameter estimation and pruning, a pointwise prediction error estimator, and a methodology for controlling the "data mining'' problem. Novel applications in the finance area are described, including customized, adaptive option pricing and stock price prediction.

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This thesis presents methods for implementing robust hexpod locomotion on an autonomous robot with many sensors and actuators. The controller is based on the Subsumption Architecture and is fully distributed over approximately 1500 simple, concurrent processes. The robot, Hannibal, weighs approximately 6 pounds and is equipped with over 100 physical sensors, 19 degrees of freedom, and 8 on board computers. We investigate the following topics in depth: distributed control of a complex robot, insect-inspired locomotion control for gait generation and rough terrain mobility, and fault tolerance. The controller was implemented, debugged, and tested on Hannibal. Through a series of experiments, we examined Hannibal's gait generation, rough terrain locomotion, and fault tolerance performance. These results demonstrate that Hannibal exhibits robust, flexible, real-time locomotion over a variety of terrain and tolerates a multitude of hardware failures.

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This thesis examines a tactile sensor and a thermal sensor for use with the Utah-MIT dexterous four fingered hand. Sensory feedback is critical or full utilization of its advanced manipulatory capabilities. The hand itself provides tendon tensions and joint angles information. However, planned control algorithms require more information than these sources can provide. The tactile sensor utilizes capacitive transduction with a novel design based entirely on silicone elastomers. It provides an 8 x 8 array of force cells with 1.9 mm center-to-center spacing. A pressure resolution of 8 significant bits is available over a 0 to 200 grams per square mm range. The thermal sensor measures a material's heat conductivity by radiating heat into an object and measuring the resulting temperature variations. This sensor has a 4 x 4 array of temperature cells with 3.5 mm center-to-center spacing. Experiments show that the thermal sensor can discriminate among material by detecting differences in their thermal conduction properties. Both sensors meet the stringent mounting requirements posed by the Utah-MIT hand. Combining them together to form a sensor with both tactile and thermal capabilities will ultimately be possible. The computational requirements for controlling a sensor equipped dexterous hand are severe. Conventional single processor computers do not provide adequate performance. To overcome these difficulties, a computational architecture based on interconnecting high performance microcomputers and a set of software primitives tailored for sensor driven control has been proposed. The system has been implemented and tested on the Utah-MIT hand. The hand, equipped with tactile and thermal sensors and controlled by its computational architecture, is one of the most advanced robotic manipulatory devices available worldwide. Other ongoing projects will exploit these tools and allow the hand to perform tasks that exceed the capabilities of current generation robots.

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The STUDENT problem solving system, programmed in LISP, accepts as input a comfortable but restricted subset of English which can express a wide variety of algebra story problems. STUDENT finds the solution to a large class of these problems. STUDENT can utilize a store of global information not specific to any one problem, and may make assumptions about the interpretation of ambiguities in the wording of the problem being solved. If it uses such information or makes any assumptions, STUDENT communicates this fact to the user. The thesis includes a summary of other English language questions-answering systems. All these systems, and STUDENT, are evaluated according to four standard criteria. The linguistic analysis in STUDENT is a first approximation to the analytic portion of a semantic theory of discourse outlined in the thesis. STUDENT finds the set of kernel sentences which are the base of the input discourse, and transforms this sequence of kernel sentences into a set of simultaneous equations which form the semantic base of the STUDENT system. STUDENT then tries to solve this set of equations for the values of requested unknowns. If it is successful it gives the answers in English. If not, STUDENT asks the user for more information, and indicates the nature of the desired information. The STUDENT system is a first step toward natural language communication with computers. Further work on the semantic theory proposed should result in much more sophisticated systems.

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We will take the view that the end result of problem solving in some world should be increased expertness. In the context of computers, increasing expertness means writing programs. This thesis is about a process, reasoning by analogy that writes programs. Analogy relates one problem world to another. We will call the world in which we have an expert problem solver the IMAGE world, and the other world the DOMAIN world. Analogy will construct an expert problem solver in the domain world using the image world expert for inspiration.

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"The Structure and Interpretation of Computer Programs" is the entry-level subject in Computer Science at the Massachusetts Institute of Technology. It is required of all students at MIT who major in Electrical Engineering or in Computer Science, as one fourth of the "common core curriculum," which also includes two subjects on circuits and linear systems and a subject on the design of digital systems. We have been involved in the development of this subject since 1978, and we have taught this material in its present form since the fall of 1980 to approximately 600 students each year. Most of these students have had little or no prior formal training in computation, although most have played with computers a bit and a few have had extensive programming or hardware design experience. Our design of this introductory Computer Science subject reflects two major concerns. First we want to establish the idea that a computer language is not just a way of getting a computer to perform operations, but rather that it is a novel formal medium for expressing ideas about methodology. Thus, programs must be written for people to read, and only incidentally for machines to execute. Secondly, we believe that the essential material to be addressed by a subject at this level, is not the syntax of particular programming language constructs, nor clever algorithms for computing particular functions of efficiently, not even the mathematical analysis of algorithms and the foundations of computing, but rather the techniques used to control the intellectual complexity of large software systems.