The paper describes a parallel computational model simulating continuously variable transmission (CVT) dynamics. A specific feature of the CVT model is the combination of relatively small problem sizes (about 1000 unknowns) and high computational costs (up to several weeks of sequential code computations for a thirty seconds simulation period). The main source of computational complexity here i...

There are numerous parallel scientific computing applications in which the same computation is successively repeated over a problem instance for many times with different parameters. In most of these applications, although the initial task-to-processor mapping may be satisfactory in terms of both computational load balance and communication requirements, the quality of this initial mapping typi...

The quantification of intra-retinal boundaries in the Optical Coherence Tomography (OCT) is a crucial task to study and diagnose neurological and ocular diseases. Since the manual segmentation of layers is usually a time consuming task and relies on the user, an excessive volume of research has been done to do this job automatically and without interference of the user. Although, generally the ...

In this chapter, we present a methodology for efficient load balancing of computational problems that can be easily decomposed into multiple tasks, but where it is hard to predict the computation cost of each task, and where new tasks are created dynamically during runtime. We present this methodology and its exploitation and feasibility in the context of graphics processors. Work-stealing allo...

Geographic information systems often represent terrains, or other height elds, by triangulated irregular networks (TINs). The visualization of TINs is therefore a task any GIS has to be able to perform. This survey paper discusses two aspects of this task: the hidden-surface removal problem, which is to determine which parts of the TIN are visible from a given view point, and the computation of...

Computers that exploit quantum effects appear capable of outperforming their classical brethren. For example, a quantum computer can efficiently factor a whole number, while there is no known algorithm for our modern classical computers to efficiently perform this task [1]. Given this extra computational punch, a natural question to ask is “What gives quantum computers their added computational...

We present new algorithms for local planning over Markov decision processes. The base-level algorithm possesses several interesting features for control of computation, based on selecting computations according to their expected benefit to decision quality. The algorithms are shown to expand the agent’s knowledge where the world warrants it, with appropriate responsiveness to time pressure and ...

Which computational complexity assumptions are inherent to cryptography? We present a broad framework to pose and investigate this question. We first aim to understand the “cryptographic complexity” of various tasks, independent of any computational assumptions. In our framework the cryptographic tasks are modeled as multi-party computation functionalities. We consider a universally composable ...

This article proposes a general theory and methodology, called the minimax entropy principle, for building statistical models for images (or signals) in a variety of applications. This principle consists of two parts. The rst is the maximum entropy principle for feature binding (or fusion): for a given set of observed feature statistics, a distribution can be built to bind these feature statist...