Search results for "Computation"
showing 10 items of 7362 documents
Two-way quantum and classical machines with small memory for online minimization problems
2019
We consider online algorithms. Typically the model is investigated with respect to competitive ratio. In this paper, we explore algorithms with small memory. We investigate two-way automata as a model for online algorithms with restricted memory. We focus on quantum and classical online algorithms. We show that there are problems that can be better solved by two-way automata with quantum and classical states than classical two-way automata in the case of sublogarithmic memory (sublinear size).
Work Partitioning on Parallel and Distributed Agent-Based Simulation
2017
Work partitioning is a key challenge with ap- plications in many scientific and technological fields. The problem is very well studied with a rich literature on both distributed and parallel computing architectures. In this paper we deal with the work partitioning problem for parallel and distributed agent-based simulations which aims at (i) balancing the overall load distribution, (ii) minimizing, at the same time, the communication overhead due to agents' inter-dependencies. We introduce a classification taxonomy of work partitioning strategies and present a space-based work partitioning ap- proach, based on a Quad-tree data structure, which enables to: identify a good space partitioning …
An improved quantum query algorithm for computing AND Boolean function
2010
We consider the quantum query model for computing Boolean functions. The definition of the function is known, but a black box contains the input X = (x 1 , x 2 , …, x n ). Black box can be accessed by querying x i values. The goal is to develop an algorithm, which would compute the function value for arbitrary input using as few queries to the black box as possible. We present two different quantum query algorithms for computing the basic Boolean function — logical AND of two bits. Both algorithms use only one query to determine the function value. Correct answer probability for the first algorithm is 80%, but for the second algorithm it is 90%. To compute this function with the same probab…
OpenCMISS: A multi-physics & multi-scale computational infrastructure for the VPH/Physiome project
2011
The VPH/Physiome Project is developing the model encoding standards CellML (cellml.org) and FieldML (fieldml.org) as well as web-accessible model repositories based on these standards (models.physiome.org). Freely available open source computational modelling software is also being developed to solve the partial differential equations described by the models and to visualise results. The OpenCMISS code (opencmiss.org), described here, has been developed by the authors over the last six years to replace the CMISS code that has supported a number of organ system Physiome projects. OpenCMISS is designed to encompass multiple sets of physical equations and to link subcellular and tissue-level b…
Canonical Retina-to-Cortex Vision Model Ready for Automatic Differentiation
2020
Canonical vision models of the retina-to-V1 cortex pathway consist of cascades of several Linear+Nonlinear layers. In this setting, parameter tuning is the key to obtain a sensible behavior when putting all these multiple layers to work together. Conventional tuning of these neural models very much depends on the explicit computation of the derivatives of the response with regard to the parameters. And, in general, this is not an easy task. Automatic differentiation is a tool developed by the deep learning community to solve similar problems without the need of explicit computation of the analytic derivatives. Therefore, implementations of canonical visual neuroscience models that are ready…
A study on graph representations for genetic programming
2020
Graph representations promise several desirable properties for Genetic Programming (GP); multiple-output programs, natural representations of code reuse and, in many cases, an innate mechanism for neutral drift. Each graph GP technique provides a program representation, genetic operators and overarching evolutionary algorithm. This makes it difficult to identify the individual causes of empirical differences, both between these methods and in comparison to traditional GP. In this work, we empirically study the behavior of Cartesian Genetic Programming (CGP), Linear Genetic Programming (LGP), Evolving Graphs by Graph Programming (EGGP) and traditional GP. By fixing some aspects of the config…
Classical and Quantum Computations with Restricted Memory
2018
Automata and branching programs are known models of computation with restricted memory. These models of computation were in focus of a large number of researchers during the last decades. Streaming algorithms are a modern model of computation with restricted memory. In this paper, we present recent results on the comparative computational power of quantum and classical models of branching programs and streaming algorithms.
On parsing optimality for dictionary-based text compression—the Zip case
2013
Dictionary-based compression schemes are the most commonly used data compression schemes since they appeared in the foundational paper of Ziv and Lempel in 1977, and generally referred to as LZ77. Their work is the base of Zip, gZip, 7-Zip and many other compression software utilities. Some of these compression schemes use variants of the greedy approach to parse the text into dictionary phrases; others have left the greedy approach to improve the compression ratio. Recently, two bit-optimal parsing algorithms have been presented filling the gap between theory and best practice. We present a survey on the parsing problem for dictionary-based text compression, identifying noticeable results …
On the role of non-effective code in linear genetic programming
2019
In linear variants of Genetic Programming (GP) like linear genetic programming (LGP), structural introns can emerge, which are nodes that are not connected to the final output and do not contribute to the output of a program. There are claims that such non-effective code is beneficial for search, as it can store relevant and important evolved information that can be reactivated in later search phases. Furthermore, introns can increase diversity, which leads to higher GP performance. This paper studies the role of non-effective code by comparing the performance of LGP variants that deal differently with non-effective code for standard symbolic regression problems. As we find no decrease in p…
Efficient evaluation for a subset of recursive queries
1991
Abstract We consider the efficient evaluation of recursive queries in logic databases where the queries are expressed using a Datalog program (function-free Horn-clause program) that contains only regularly or linearly recursive predicates. Using well-known results on graph traversal, we develop an efficient algorithm for evaluating relations defined by a binary-chain program. We also present a transformation by which the evaluation of a subset of queries involving nonbinary relations can be reduced to the evaluation of binary-chain queries. This transformation is guided by the choice of bound arguments in the query, and the bindings are propagated through the program so that in the evaluat…