ppxscal/embedding_network huggingface dataset:
Building a 2D-Compatible Multilayer Neural Network
Authors: Bernard Girau
Venue: Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 2 - Volume 2 (2000)

Various fast parallel implementations of neural networks have been developed ([13]). The very fine-grain parallelism of neural networks uses many information exchanges, so that it better fits hardware implementations. Configurable hardware devices such as FPGAs 1 (Field Programmable Gate Arrays) offer a cheap compromise between the hardware efficiency of ASICs and the flexibility of a simple software-like handling. Moreover, FPGAs offer several advantages for neural network implementations, such as prototyping and embedding, while FPGA-based implementations may be mapped onto new improved FPGAs (unlike the use of neuroprocessors, which rapidly become outdated). However, the 2D-topology of FPGAs does not allow handling the complex connection graphs of standard neural network models, as well as their numerous area-greedy operators (multipliers, transfer functions). Usual solutions ([3, 7, 15, 5, 4, 2]) handle sequentialized computations with a FPGA used as a small neuroprocessor, or they implement very small low-precision neural networks without on-chip learning. Connectivity problems are not solved even by the use of several FPGAs with a bit-serial arithmetic ([6]), or by the use of small-area stochastic bitstream operators (stochastic bit-stream in [1, 17], or frequency-based in [12]).An upstream work is needed: neural computation paradigms may be defined to counterbalance the topological problems, and the use of such paradigms naturally leads to neural models that are more tolerant of hardware constraints. The theoretical and practical framework developed in [9] aims at developing such neural architectures that are easy to map onto FPGAs, thanks to a simplified topology and an original data exchange scheme. These Field Programmable Neural Arrays (FPNAs) reconcile the high connection density of neural architectures with the need of a limited interconnection scheme in hardware implementations.A global study of FPNAs may be found in [9]. The use of FPGAs for neural network implementations is justified in [11]. This paper focuses on the FPNA-based simplification of the architecture of a multilayer shortcut perceptron used in a pattern classification problem. Section 2 shortly defines FPNAs along with their computation algorithm. Section 3 describes the way FPNAs have been applied to the Proben 1:diabetes problem, as well as the classification and implementation performances that have been reached.
Simulation of a magneto-mechanical damping machine: analysis, discretization, results
Authors: Bouillault F., Buffa A., Maday Y., Rapetti F.
Venue:  (2000)

This paper presents and analyzes a method for the simulation of the dynamical behavior of a coupled magneto-mechanical system such as a damping machine. We consider a two-dimensional model based on the transverse magnetic formulation of the eddy currents problem for the electromagnetic part and on the motion equation of a rotating rigid body for the mechanical part. The magnetic system is discretized in space by means of Lagrangian finite elements and the sliding mesh mortar method is used to account for the rotation. In time, a one step Euler method is used, implicit for the magnetic and velocity equations. The coupled differential system is solved with an explicit procedure.
The Cycle Server: A Web Platform for Running Parallel Monte Carlo Applications on a Heterogeneous Condor Pool of Workstations
Authors: Mike Zhou, Michael Mascagni
Venue: Proceedings of the 2000 International Workshop on Parallel Processing (2000)

We have developed a scientific computing tool, which we call the cycle server. This tool enables Monte Carlo computations on the Condor cycle scavenging system. The tool presents users with a graphical web interface, which hides the complexity of distributed computing from users. Users need only upload codes and download results via the web GUI anywhere there is web access. Parallel random number support (via SPRNG random number library), running tasks on heterogeneous platforms (via the remote compiler), and using Condor to migrate jobs from busy or dead machines to idle ones, are all integrated seamlessly with the tool and are transparent to the user. At the same time, the cycle server acts as a gatekeeper for the workstation pool. No user accounts are needed on pool computers, and jobs only run at otherwise idle times without accessing local file systems. We show the utility of the cycle server on a large Monte Carlo computation from biochemical physics.
ON ENERGY EFFICIENCY AND NETWORK CONNECTIVITY OF MOBILE AD HOC NETWORKS
Authors: Wing Ho Yuen, Chi Wan Sung
Venue: Proceedings of the 23rd International Conference on Distributed Computing Systems (2003)

In mobile ad hoc networks, it is often moreimportant to optimize for energy efficiency than throughput.In this paper, we investigate the effect of transmit range onenergy efficiency of packet transmissions. We determine acommon range for all nodes such that the average energyexpenditure per received packet is minimized. In the first partof this paper, we consider stationary networks. We show thatenergy efficiency depends on various system parameters thatincludes path loss exponent of the channel, energy dissipationmodel and network offered load. In particular, when thepath loss exponent is large, energy efficiency decreases whenthe transmit range increases. Hence, the network should beoperated at the critical range that just maintains networkconnectivity. However, when the path loss exponent is small,operating at the critical range yields inferior throughput andenergy efficiency. Our results show that energy efficiency isintimately connected to network connectivity. Three networkconnectivity regimes are identified as the transmit range ofall nodes increases. In the second part, we examine the effectof node mobility on energy efficiency. We show that at normaloffered load, an optimal transmit range exists such that energyefficiency is maximized. The optimal range turns out to beinsensitive to node mobility, and is much larger than thecritical range. We show that the energy expenditure can bereduced by 15% to 73% in different mobility scenarios, if thenetwork is operated at the optimal range.
Constraints: A Uniform Approach to Aliasing and Typing
Authors: Leslie Lamport, Fred B. Schneider
Venue:  (1984)

No abstract supplied.
Well-posedness and Time Discretization of a Nonlinear Volterra Integrodifferential Equation
Authors: Ulisse Stefanelli
Venue:  (1999)

This paper deals with a nonlinear abstract evolution integrodifferential equation of Volterra type. This equation contains two nonlinearities, namely a maximal monotone operator and a Lipschitz continuous operator, and may arise from a Stefan problem in materials with memory. Uniqueness of a solution to the associated Cauchy problem is proved. Then, global existence is achieved via a semi-implicit time discretization procedure. Moreover, some estimates for the discretization error are established.
Personalizing the Interaction in a Web-based Educational Hypermedia System: the case of INSPIRE
Authors: Kyparisia A. Papanikolaou, Maria Grigoriadou, Harry Kornilakis, George D. Magoulas
Venue: User Modeling and User-Adapted Interaction (2003)

In this paper we present an Adaptive Educational Hypermedia prototype, named INSPIRE. The approach employed in INSPIRE emphasizes the fact that learners perceive and process information in very different ways, and integrates ideas from theories of instructional design and learning styles. Our aim is to make a shift towards a more 'learning-focused' paradigm of instruction by providing a sequence of authentic and meaningful tasks that matches learner' preferred way of studying. INSPIRE, throughout its interaction with the learner, dynamically generates learner-tailored lessons that gradually lead to the accomplishment of learner's learning goals. It supports several levels of adaptation: from full system-control to full learner-control, and offers learners the option to decide on the level of adaptation of the system by intervening in different stages of the lesson generation process and formulating the lesson contents and presentation. Both the adaptive and adaptable behavior of INSPIRE are guided by the learner model which provides information about the learner, such as knowledge level on the domain concepts and learning style. The learner model is exploited in multiple ways: curriculum sequencing, adaptive navigation support, adaptive presentation, and supports system's adaptable behavior. An empirical study has been performed to evaluate the adaptation framework and assess learners' attitudes towards the proposed instructional design.
Mob --- A Parallel Heuristic for Graph-Embedding
Authors: John E. Savage, Markus G. Wloka
Venue:  (1993)

We have extended the {\em Mob}\ heuristic for graph partitioning to grid and hypercube embedding and have efficiently implemented our new heuristic on the CM-2 Connection Machine. We have conducted an extensive series of experiments to show that it exploits parallelism, is fast, and gives very low embedding costs. For example, on the 32K-processor CM-2 it runs in less than 30 minutes on random graphs of 1 million edges and shows impressive reductions in edge costs. Due to excessive run times, other heuristics reported in the literature can only construct graph embeddings for graphs that are 100 to 1000 times smaller than those used in our experiments.
Experiences on the KSR1: Complex Matrix-vector Multiply
Authors: Anne E. Trefethen
Venue:  (1993)

In this report we examine the serial and parallel implementation of complex matrix vector multiply on the KSR1. The implementations are in Fortran. We attempt to illustrate the type of compiler performance that can be expected from the KSR1 at the present time and also the tools that are available for parallelizing Fortran code. Code for several of the implementations is presented together with their Mflop ratings.
Applications of Surface Networks to Sampling Problems in Computer Graphics
Authors: Brian Von Herzen
Venue:  (1988)

This thesis develops the theory, algorithms and data structures for adaptive sampling of parametric functions, which can represent the shapes and motions of physical objects. For the first time, ensured methods are derived for determining collisions and other interactions for a broad class of parametric functions. A new data structure, called a surface network, is developed for the collision algorithm and for other sampling problems in computer graphics. A surface network organizes a set of parametric samples into a hierarchy. Surface networks are shown to be good for rendering images, for approximating surfaces, and for modeling physical environments. The basic notion of a surface network is generalized to higher-dimensional problems such as collision detection. We may think of a two-dimensional network covering a three-dimensional solid, or an n-dimensional network embedded in a higher-dimensional space. Surface networks are applied to the problems of adaptive sampling of static parametric surfaces, to adaptive sampling of time-dependent parametric surfaces, and to a variety of applications in computer graphics, robotics, and aviation. First we develop the theory for adaptive sampling of static surfaces. We explore bounding volumes that enclose static surfaces, subdivision mechanisms that adjust the sampling density, and subdivision criteria that determine where samples should be placed. A new method is developed for creating bounding ellipsoids of parametric surfaces using a Lipschitz condition to place bounds on the derivatives of parametric functions. The bounding volumes are arranged in a hierarchy based on the hierarchy of the surface network. The method ensures that the bounding volume hierarchy contains the parametric surface completely. The bounding volumes are useful for computing surface intersections. They are potentially useful for ray tracing of parametric surfaces. We develop and examine a variety of subdivision mechanisms to control the sampling process for parametric functions. Some of the methods are shown to improve the robustness of adaptive sampling. Algorithms for one mechanism, using bintrees of right parametric triangles, are particularly simple and robust. A set of empirical subdivision criteria determine where to sample a surface, when we have no additional information about the surface. Parametric samples are concentrated in regions of high curvature, and along intersection boundaries. Once the foundations of adaptive sampling for static surfaces are described, we examine time-dependent surfaces. Based on results with the empirical subdivision criteria for static surfaces, we derive ensured criteria for collision determination. We develop a new set of rectangular bounding volumes, apply a standard L-dimensional subdivision mechanism called k-d trees, and develop criteria for ensuring that we detect collisions between parametric surfaces. We produce rectangular bounding boxes using a "Jacobian''''-style matrix of Lipschit
The use of communications networks to increase personal privacy
Authors: N. F. Maxemchuk, S. Low
Venue: Proceedings of the Fourteenth Annual Joint Conference of the IEEE Computer and Communication Societies (Vol. 2)-Volume - Volume 2 (1995)

Communications networks can separate as well as join information. This ability can be used to increase personal privacy in an environment where advances in technology makes it possible to collect and correlate increasing amounts of information about individuals. The tools and principles necessary to increase personal privacy are demonstrated by creating an anonymous credit card, in which a person's identity and purchases are separated, and a national health insurance plan, in which treatment, payment and an individual's identity are separated. An analysis technique is developed to determine how well the information is separated.
Ab Initio Calculations on the Structure and Conformation of Group V Bent Metallocenethiolates
Authors: Charles Q. Simpson,  II, Michael B. Hall
Venue:  (1991)

Ab initio geometry optimizations are reported for several models of the bent metallocenethiolates (n5-C5H5)2M(SR)2. The S-M-S angle and R-S-M-S dihedral angle depend upon the metal d count, the nature of the M and R group, and on each other in subtle ways. While in most Nb d1 complexes the SR groups reside in an exo conformation, in the V d1 complexes they reside in an endo conformation. This unexpected difference is due to a combination of steric hindrance in the more compact V complexes and weaker electronic (overlap) effects of the more contracted 3d orbitals. Although Cp2Nb(SC6H5)2 is found in the expected exo conformation, the para-chloro derivative Cp2Nb(SC6H4CL)2 adopts the endo conformation. The calculations show that this change must be a result of intermolecular force such as H-bonding and crystal packing.
A Software Falsifier
Authors: Daniel Brand
Venue: Proceedings of the 11th International Symposium on Software Reliability Engineering (2000)

A falsifier is a tool for discovering errors by static source-code analysis. Its goal is to discover them while requiring minimal programmer's effort. In contrast to lint-like tools or verifiers, which try to maximize the number of errors reported at the expense of allowing ¿false errors¿, falsifier's goal is to guarantee no false errors. To further minimize programmer's effort, no specification or extra information about his program is required. That, however, does not preclude project specific information from being built in. The class of errors detectable without any specification is important not only because of the low cost of detection, but also because it includes errors of portability, irreproducible behavior, etc, which are very expensive to detect by testing. This paper describes the design and implementation of such a falsifier, and reports on the experience with its use for design automation software. The main contribution of this work lies in combining data-flow analysis with symbolic execution to take advantage of their relative advantages.
High-level proofs of mathematical programs using automatic differentiation, simplification, and some common sense
Authors: Richard Fateman
Venue: Proceedings of the 2003 international symposium on Symbolic and algebraic computation (2003)

One problem in applying elementary methods to prove correctness of interesting scientific programs is the large discrepancy in level of discourse between low-level proof methods and the logic of scientific calculation, especially that used in a complex numerical program. The justification of an algorithm typically relies on algebra or analysis, but the correctness of the program requires that the arithmetic expressions are written correctly and that iterations converge to correct values in spite of truncation of infinite processes or series and the commission of numerical roundoff errors. We hope to help bridge this gap by showing how we can, in some cases, state a high-level requirement and by using a computer algebra system (CAS) demonstrate that a program satisfies that requirement. A CAS can contribute program manipulation, partial evaluation, simplification or other algorithmic methods. A novelty here is that we add to the usual list of techniques automatic differentiation, a method already widely used in optimization contexts where algorithms are differentiated. We sketch a proof of a numerical program to compute sine, and display a related approach to a version of a Bessel function algorithm for J0(x) based on a recurrence.
Analyzing and Understanding Architectural Characteristics of COM+ Components
Authors: Martin Pinzger, Johann Oberleitner, Harald Gall
Venue: Proceedings of the 11th IEEE International Workshop on Program Comprehension (2003)

Understanding architectural characteristics of software components that constitute distributed systems is crucial for maintaining and evolving them. One component framework heavily used for developing component-based software systems is Microsoft's COM+. In this paper we particularly concentrate on the analysis of COM+ components and introduce an iterative and interactive approach that combines component inspection techniques with source code analysis to obtain a complete abstract model of each COM+ component. The model describes important architectural characteristics such as transactions, security, and persistency, as well as create and use dependencies between components, and maps these higher-level concepts down to their implementation in source files. Based on the model, engineers can browse the software system's COM+ components and navigate from the list of architectural characteristics to the corresponding source code statements. We also discuss the Island Hopper application with which our approach has been validated.
Latency reduction from runtime-interference to the parallel Quantum Chemistry program GREMLIN in heterogeneous and homogeneous environments
Authors: Siegfried Höfinger
Venue: Future Generation Computer Systems (2003)

The runtime behaviour of the PVM version of the Quantum Chemistry program GREMLIN is monitored and analyzed with respect to the latency of the different participating hosts. A priori parallel performance is far from optimal, because of the multifold variabilities influencing the heterogeneous cluster environment. The article discusses the improvement gained when periodically re-partitioning the load based on the current actual latencies of the parallel nodes. It is also shown that even on homogeneous parallel architectures this dynamic version of Speed Weighted Load Balancing (SWLB) may aid to optimize parallel performance considerably.
Memory Subsystem Performance of Programs with Intensive Heap Allocation
Authors: Amer Diwan, David Tarditi, Eliot Moss
Venue:  (1993)

Heap allocation with copying garbage collection is a general storage management technique for modern programming languages. It is believed to have poor memory subsystem performance. To investigate this, we conducted an in-depth study of the memory subsystem performance of heap allocation for memory subsystems found on many machines. We studied the performance of mostly-functional Standard ML programs which made heavy use of heap allocation. We found that most machines support heap allocation poorly. However, with the appropriate memory subsystem organization, heap allocation can have good performance. The memory subsystem property crucial for achieving good performance was the ability to allocate and initialize a new object into the cache without a penalty. This can be achieved by having subblock placement with a subblock size of one word with a write allocate policy, along with fast page-mode writes or a write buffer. For caches with subblock placement, the data cache overhead was under 9% for a 64K of larger data cache; without subblock placement the overhead was often higher than 50%.
Second-order polynomial estimators from uncertain observations using covariance information
Authors: S. Nakamori, R. Caballero-Águila, A. Hermoso-Carazo, J. Linares-Pérez
Venue: Applied Mathematics and Computation (2003)

This paper presents recursive least mean-squared error second-order polynomial filtering and fixed-point smoothing algorithms to estimate a signal, from uncertain observations, when only the information on the moments up to fourth-order of the signal and observation noise is available. The estimators require the autocovariance and crosscovariance functions of the signal and their second-order powers in a semidegenerate kernel form, and the probability that the signal exists in the observed values.
On the Power of the Mesh with Hybrid Buses
Authors: Biing-Feng Wang, Stephan Olariu
Venue: Proceedings of the 1997 International Symposium on Parallel Architectures, Algorithms and Networks (1997)

The main contribution of this work is to fathom the power and flexibility of the Mesh with Hybrid Buses via simulation. We propose two algorithms that perform an O(1) time stepwise simulation of an N-processor dynamic Priority CRCW-PRAM endowed with M memory cells. Our first algorithm uses a Mesh with Hybrid Buses of size max{N, MN^(e/2)} * MN^(e/2), for some fixed constant e, 0
Experiments on FPRM Expressions for Partially Symmetric Logic Functions
Authors: S. N. Yanushkevich, V. P. Shmerko, J. T. Butler, G. W. Dueck
Venue: Proceedings of the 30th IEEE International Symposium on Multiple-Valued Logic (2000)

This paper focuses on the fixed polarity Reed-Muller (FPRM) expression of multiple-valued logic (MVL) symmetric functions. In the FPRM expression, each variable occurs in exactly one complemented form. We show properties of the FPRM of partially symmetric functions and report experimental results for certain benchmark functions.
Weak and Direct Eulerian-Lagrangian Localized Adjoint Methods for Nonlinear Physical Velocity and Reaction
Authors: R. V. Trujillo, T. A. Russell, D. W. Dean
Venue:  (1994)

Eulerian-Lagrangian localized adjoint methods (ELLAM), designed for the systematic numerical treatment of non-self-adjoint parabolic partial differential equations, use a space-time finite elements framework. ELLAM combine the crucial aspects of Eulerian methods for self-adjoint parabolic equations (e.g. systematic treatment of boundary conditions, discrete conservation) and of Lagrangian methods for first-order hyperbolic equations (e.g. front-tracking via characteristics). As a result, ELAM solutions are free from the usual Courant number restrictions and the usual defects of excessive non-physical oscillation and smearing of sharp fronts. Here, we extend weak and direct ELLAM to nonlinear physical velocities and reaction terms for model mass and momentum conservation laws, having in mind applications to petroleum reservoir simulation, groundwater contaminant transport, and Navier-Stokes problems in the velocity-pressure setting. Weak ELLAM are used when an Eulerian description of the solution is natural. Also, we stress the interconnections between the two methods and present numerical results for the viscous Burgers equation.