ppxscal/embedding_network huggingface dataset:
Synthesizing Variable Instruction Issue Interpreters for Implementing Functional Parallelism on SIMD Computers
Authors: Nael B. Abu-Ghazaleh, Philip A. Wilsey, Xianzhi Fan Debra A. Hensgen
Venue: IEEE Transactions on Parallel and Distributed Systems (1997)

Functional parallelism can be supported on SIMD machines by interpretation. Under such a scheme, the programs and data of each task are loaded on the processing elements (PEs) and the Control Unit of the machine executes a central control algorithm that causes the concurrent interpretation of the tasks on the PEs. The central control algorithm is, in many respects, analogous to the control store program on microprogrammed machines. Accordingly, the organization of the control algorithm greatly influences the performance of the synthesized MIMD environment.Most central control algorithms are constructed to interpret the execution phase of all instructions during every cycle (iteration). However, it is possible to delay the interpretation of infrequent and costly instructions to improve the overall performance. Interpreters that attempt improved performance by delaying the issue of infrequent instructions are referred to as variable issue control algorithms. This paper examines the construction of optimized variable issue control algorithms. In particular, a mathematical model for the interpretation process is built and two objective functions (instruction throughput and PE utilization) are defined. The problem of deriving variable issue control algorithms for these objective functions has been shown elsewhere to be NP-complete. Therefore, this paper investigates three heuristic algorithms for constructing near optimal variable issue control algorithms. The performance of the algorithms is studied on four different instruction sets and the trends of the schedulers with respect to the instruction sets and the objective functions are analyzed.
The object shop&mdash;using CD-ROM multimedia to introduce object concepts
Authors: Mark Woodman, Robert Griffiths, Simon Holland, Andrew Law
Venue: Proceedings of the twenty-eighth SIGCSE technical symposium on Computer science education (1997)

This paper describes key features of a new multimedia CD-ROM pack produced by television makers in collaboration with computer science educators --- by the BBC for the Open University Computing Department. The pack, The Object Shop, forms an early component of an undergraduate course which introduces object-oriented computing and software development to students new to computing. Building on the results of empirical evaluation, The Object Shop has been designed to help students with no programming experience to understand core object programming concepts. Throughout the CD-ROM, video, animated graphics and an underlying object-oriented simulation of a virtual shopping environment provide an accessible introduction to the central ideas of object-oriented programming. The key power of the multimedia approach is that the student-user is able to gain a sound operational understanding of concepts before learning the details of programming code or syntax. Users can continually monitor their progress through a series of task-based, assessed exercises.
Fast Gossiping by Short Messages
Authors: Jean-Claude Bermond, Luisa Gargano, Adele A. Rescigno, Ugo Vaccaro
Venue: SIAM Journal on Computing (1998)

Gossiping is the process of information diffusion in which each node of a network holds a packet that must be communicated to all other nodes in the network. We consider the problem of gossiping in communication networks under the restriction that communicating nodes can exchange up to a fixed number p of packets at each round. In the first part of the paper we study the extremal case p=1 and we exactly determine the optimal number of communication rounds to perform gossiping for several classes of graphs, including Hamiltonian graphs and complete k-ary trees. For arbitrary graphs we give asymptotically matching upper and lower bounds. We also study the case of arbitrary p and we exactly determine the optimal number of communication rounds to perform gossiping under this hypothesis for complete graphs, hypercubes, rings, and paths. Finally, we investigate the problem of determining sparse networks in which gossiping can be performed in the minimum possible number of rounds.
Timely Communication: Efficient Algorithms for Solving a Fourth-Order Equation with the Spectral-Galerkin Method
Authors: Petter E. Bjørstad, Bjørn Peter Tjøstheim
Venue: SIAM Journal on Scientific Computing (1997)

We show that one can derive an $O(N^3)$ spectral-Galerkin method for fourth-order (biharmonic type) elliptic equations based on the use of Chebyshev polynomials. The use of Chebyshev polynomials provides a fast transform between physical and spectral space which is advantageous when a sequence of problems must be solved, e.g., as part of a nonlinear iteration. This improves the result of Shen [SIAM J. Sci. Comput., 16 (1995), pp. 74--87] which reported an $O(N^4)$ algorithm inferior to the $O(N^3)$ method developed earlier [Shen, SIAM J. Sci. Comput., 15 (1994), pp. 1440--1451] based on Legendre polynomials but less practical in the case of multiple problems. We further compare our method with an improved implementation of the Legendre--Galerkin method based on the same approach.
A CMOS continuous-time field programmable analog array
Authors: C. A. Looby, C. Lyden
Venue: Proceedings of the 1997 ACM fifth international symposium on Field-programmable gate arrays (1997)

A circuit design for a Field Programmable Analog Array is presented which improves accuracy and repeatability compared to previous designs. Controlled by a configuration register, continuous-time signals are routed among programmable analog blocks to implement the user's chosen circuit. The configurable connections are realized by CMOS switches and a new innovation is that these are either buffered or nulled to cancel parasitic error. The function blocks are Op-Amps combined with passive networks which allow programmable transfer functions with accuracy insensitive to variations in process parameters and environment. The intended application area is the rapid development of analog circuits which are presently prototyped by PCBs stuffed with Op-Amp and passive components. The concept has been demonstrated on a CMOS IC and the resulting performance shows the feasibility of this approach to general purpose FPAA technology.
Motion Perception Using Analog VLSI
Authors: Andre J. S. Yakovleff, Alireza Moini
Venue: Analog Integrated Circuits and Signal Processing (1998)

Motion perception is arguably a fundamental mechanism used by natural species to accomplish a number of tasks, such as navigating freely in an unknown environment. Traditional motion perception methods tend to be computationally intensive, requiring powerful computers and large memories. However, by copying biological mechanisms, such as elementary motion discrimination at the early stages of the visual processing paths, it should be possible to build small and efficient motion perception systems. This paper describes the manner in which a simple motion perception model based on the insect visual system has been implemented using mixed analog/digital VLSI. The device has been fabricated in a 2 micron double metal, double polysilicon process, and comprises 61 photo-detectors, and associated analog and digital circuitry. While not entirely successful in that component mismatches hamper the detection of dark-to-bright changes in contrast, the results clearly show the feasibility of using such a device in autonomous control systems.
Moment-Based Image Normalization With High Noise-Tolerance
Authors: Matthias Gruber, Ken-Yuh Hsu
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (1997)

In this paper the effects of noise with nonzero mean on existing moment-based image normalization methods are studied. Several modifications to reduce noise sensitivity are presented and tested. They involve nonlinear mapping and fractional- and negative-order moments.
On the Accuracy of Meta-learning for Scalable Data Mining
Authors: Philip K. Chan, Salvatore J. Stolfo
Venue: Journal of Intelligent Information Systems (1997)

In this paper, we describe a general approach to scaling data mining applications that we have come to call meta-learning. Meta-Learning refers to a general strategy that seeks to learn how to combine a number of separate learning processes in an intelligent fashion. We desire a meta-learning architecture that exhibits two key behaviors. First, the meta-learning strategy must produce an accurate final classification system. This means that a meta-learning architecture must produce a final outcome that is at least as accurate as a conventional learning algorithm applied to all available data. Second, it must be fast, relative to an individual sequential learning algorithm when applied to massive databases of examples, and operate in a reasonable amount of time. This paper focussed primarily on issues related to the accuracy and efficacy of meta-learning as a general strategy. A number of empirical results are presented demonstrating that meta-learning is technically feasible in wide-area, network computing environments.
JavaScript as a first programming language for multimedia students
Authors: Robert Ward, Martin Smith
Venue: ACM SIGCSE Bulletin (1998)

Whilst there has been much discussion of Java as a first programming language, JavaScript has been comparatively ignored. This paper argues the merits of JavaScript as a first programming language for Multimedia students. It then describes the content of modules that use this approach, and reports experiences and findings on first delivery. As a result of positive experiences we are now planning to use JavaScript as precursor to Java for mainstream Computing students.
SMART: tools and methods for synthesis of VLSI chips with processor architecture
Authors: T. Bergstraesser, J. Gessner, K. Hafner, S. Wallstab
Venue: Proceedings of the 25th ACM/IEEE Design Automation Conference (1988)

A design environment supporting processor synthesis in data path style is presented in this paper. The programming model of a processor described in Common Lisp is transformed into a hardware structure by means of tools integrated into this environment. The generation of alternative designs is supported by the interactive graphical manipulation of behavior and hardware structure representations and their correspondences. The synthesis procedure is explained using an example.
Ada impacts on a second generation project
Authors: Keith Hines
Venue: Proceedings of the conference on TRI-ADA '90 (1990)

This paper presents the impacts of the Ada language on a project by comparing the software from two generations of equipments which perform the same functions. The first generation of software was developed using the C language and the second generation of software was developed using the Ada language. The comparisons include the impacts on the hardware design, the software development environment, the amount of training, the software design methodology, the software programming, the testing methodology, the software useability, the integrity of the software documentation, and the maintainability of the software.
Statically checkable pattern abstractions
Authors: Manuel Fähndrich, John Boyland
Venue: ACM SIGPLAN Notices (1997)

Pattern abstractions increase the expressiveness of pattern matthing, enabling the programmer to describe a broader class of regular forests with patterns. Furthermore, pattern abstractions support code reuse and code factoring, features that facilitate maintenance and evolution of code. Past research on pattern abstractions has generally ignored the aspect of compile-time checks for exhaustiveness and redundancy. In this paper we propose a class of expressive patterns that admits these compile-time checks.
Comparing mostly-copying and mark-sweep conservative collection
Authors: Frederick Smith, Greg Morrisett
Venue: Proceedings of the 1st international symposium on Memory management (1998)

Many high-level language compilers generate C code and then invoke a C compiler for code generation. To date, most, of these compilers link the resulting code against a conservative mark-sweep garbage collector in order to reclaim unused memory. We introduce a new collector, MCC, based on an extension of mostly-copying collection.We analyze the various design decisions made in MCC and provide a performance comparison to the most widely used conservative mark-sweep collector (the Boehm-Demers-Weiser collector). Our results show that a good mostly-copying collector can outperform a mature highly-optimized mark-sweep collector when physical memory is large relative to the live data. A surprising result of our analysis is that cache behavior can have a greater impact on overall performance than either collector time or allocation time.
Simulating requirements gathering
Authors: Martin L. Barrett
Venue: ACM SIGCSE Bulletin (1997)

One of the difficulties in teaching a project-based Software Engineering course for undergraduates is giving students experience with requirements gathering before they begin the course project. This paper describes a simulation of Joint Application Design (JAD), a technique used in industry to gather requirements from users. The simulation is a role-playing exercise in which students play the parts of both developers and customers involved in specifying a new software product. Each participant is given a script of behaviors to act out for his or her role and a set of specific requirements for the product. The participants must work out conflicts and ambiguities built into the simulation to produce a consistent product specification.
Filters, Random Fields and Maximum Entropy (FRAME): Towards a Unified Theory for Texture Modeling
Authors: Song Chun Zhu, Yingnian Wu, David Mumford
Venue: International Journal of Computer Vision (1998)

This article presents a statistical theory for texture modeling. This theory combines filtering theory and Markov random field modeling through the maximum entropy principle, and interprets and clarifies many previous concepts and methods for texture analysis and synthesis from a unified point of view. Our theory characterizes the ensemble of images I with the same texture appearance by a probability distribution f(I) on a random field, and the objective of texture modeling is to make inference about f(I), given a set of observed texture examples.In our theory, texture modeling consists of two steps. (1) A set of filters is selected from a general filter bank to capture features of the texture, these filters are applied to observed texture images, and the histograms of the filtered images are extracted. These histograms are estimates of the marginal distributions of f( I). This step is called feature extraction. (2) The maximum entropy principle is employed to derive a distribution p(I), which is restricted to have the same marginal distributions as those in (1). This p(I) is considered as an estimate of f( I). This step is called feature fusion. A stepwise algorithm is proposed to choose filters from a general filter bank. The resulting model, called FRAME (Filters, Random fields And Maximum Entropy), is a Markov random field (MRF) model, but with a much enriched vocabulary and hence much stronger descriptive ability than the previous MRF models used for texture modeling. Gibbs sampler is adopted to synthesize texture images by drawing typical samples from p(I), thus the model is verified by seeing whether the synthesized texture images have similar visual appearances to the texture images being modeled. Experiments on a variety of 1D and 2D textures are described to illustrate our theory and to show the performance of our algorithms. These experiments demonstrate that many textures which are previously considered as from different categories can be modeled and synthesized in a common framework.
Gradient Based Image Motion Estimation Without Computing Gradients
Authors: Naresh Gupta, Laveen Kanal
Venue: International Journal of Computer Vision (1997)

Computing an optical flow field using the classical image motion constraint equation I_x \, u + I_y \, v + I_t = 0, is difficult owing to the aperture problem and the need to compute the image intensity derivatives via numerical differentiation&mdash;an extremely unstable operation. We integrate the above constraint equation over a significant spatio-temporal support and use Gauss&lsquo;s Divergence theorem to replace the volume integrals by surface integrals, thereby eliminating the intensity derivatives and numerical differentiation. We tackle the aperture problem by fitting an affine flow field model to a small space-time window. Using this affine model our new integral motion constraint approach leads to a robust and accurate algorithm to compute the optical flow field. Extensive experimentation confirms that the algorithm is indeed robust and accurate.
Dynamic memory usage in parallel simulation: a case study of a large-scale military logistics application
Authors: Chris J. M. Booth, David I. Bruce, Peter R. Hoare, Michael J. Kirton, K. Roy Milner, Ian J. Relf
Venue: Proceedings of the 28th conference on Winter simulation (1996)

We report on a comparative study of the performance of shared and distributed memory parallel simulation algo rithms on a large-scale military logistics simulation, and describe the nature of the application and its parallelisa tion in some detail. We demonstrate that the patterns of communication in the simulation were such that a standard implementation of Breathing Time Buckets (BTB) was unable to achieve any speed-up. New variants of BTB were designed and implemented, and we were able to achieve a speed-up of 7.4 compared to a critical path limit of 16.9. The logistics simulation contained a number of complex data structures and its parallel implementation was highly memory-intensive. The resulting patterns of memory access significantly degraded the shared memory simulation performance relative to the equivalent distributed memory version. These results cast doubt on the effectiveness of the current generation of shared memory parallel computers in dealing with optimistic simulations of large, dynamic scenarios.
Intensional polymorphism in type-erasure semantics
Authors: Karl Crary, Stephanie Weirich, Greg Morrisett
Venue: Proceedings of the third ACM SIGPLAN international conference on Functional programming (1998)

Intensional polymorphism, the ability to dispatch to different routines based on types at run time, enables a variety of advanced implementation techniques for polymorphic languages, including tag-free garbage collection, unboxed function arguments, polymorphic marshalling, and flattened data structures. To date, languages that support intensional polymorphism have required a type-passing (as opposed to type-erasure) interpretation where types are constructed and passed to polymorphic functions at run time. Unfortunately, type-passing suffers from a number of drawbacks: it requires duplication of constructs at the term and type levels, it prevents abstraction, and it severely complicates polymorphic closure conversion.We present a type-theoretic framework that supports intensional polymorphism, but avoids many of the disadvantages of type passing. In our approach, run-time type information is represented by ordinary terms. This avoids the duplication problem, allows us to recover abstraction, and avoids complications with closure conversion. In addition, our type system provides another improvement in expressiveness; it allows unknown types to be refined in place thereby avoiding certain beta-expansions required by other frameworks.
A Globally Convergent Sequential Quadratic Programming Algorithm for Mathematical Programs with Linear Complementarity Constraints
Authors: Masao Fukushima, Zhi-Quan Luo, Jong-Shi Pang
Venue: Computational Optimization and Applications (1998)

This paper presents a sequential quadratic programming algorithm for computing a stationary point of a mathematical program with linear complementarity constraints. The algorithm is based on a reformulation of the complementarity condition as a system of semismooth equations by means of Fischer-Burmeister functional, combined with a classical penalty function method for solving constrained optimization problems. Global convergence of the algorithm is established under appropriate assumptions. Some preliminary computational results are reported.
CATAPULT: concurrent automatic testing allowing parallelization and using limited topology
Authors: Rhonda Kay Gaede, Don E. Ross, M. Ray Mercer, Kenneth M. Butler
Venue: Proceedings of the 25th ACM/IEEE Design Automation Conference (1988)

This paper deals with an improved algorithm for identifying redundant faults and finding tests for &ldquo;hard faults&rdquo; in combinational circuits. A new, concurrent approach is proposed which is based upon the concepts of functional decomposition, explicit representation of fanout stems and the Boolean difference. The data structure to be used is the Binary Decision Diagram as developed by Lee, Akers and Bryant. This algorithm operates as a backend to test generators which use random patterns or heuristics or a combination of the two.
Impact of Partial Separability on Large-Scale Optimization
Authors: Ali Bouaricha, Jorge J. Morè
Venue: Computational Optimization and Applications (1997)

ELSO is an environment for the solution of large-scale optimization problems. With ELSO the user is required to provide only code for the evaluation of a partially separable function. ELSO exploits the partial separability structure of the function to compute the gradient efficiently using automatic differentiation. We demonstrate ELSO&lsquo;s efficiency by comparing the various options available in ELSO. Our conclusion is that the hybrid option in ELSO provides performance comparable to the hand-coded option, while having the significant advantage of not requiring a hand-coded gradient or the sparsity pattern of the partially separable function. In our test problems, which have carefully coded gradients, the computing time for the hybrid AD option is within a factor of two of the hand-coded option.
Broadening the computer science curriculum
Authors: James Robergé, C. R. Carlson
Venue: ACM SIGCSE Bulletin (1997)

Too often, students in undergraduate computer science programs come to equate computer science with the "nuts and bolts" of the field---programming, data structures, algorithms, operating systems, programming languages and so forth. If we are to attract students to computer science and produce graduates who will excel in the profession, we must broaden our students' perspective on our discipline. In this paper, we examine an initiative that seeks to broaden the undergraduate computer science experience by introducing three new elements into the curriculum: a first-year experience that focuses on the challenges of computer science, a fourth-year experience that focuses on the initial stages of the software design process, and a student portfolio that unifies the existing curriculum, broadens its content, and provides us with a mechanism for assessing the growth of our students' technical and non-technical skills.