Abstract

Abstract
In this paper we present the architecture of RTPM, a middle-ware framework aimed at supporting the development and management of information systems for high-speed public transportation systems. The framework is based on a peer-to-peer overlay infrastructure with the main focus being on providing a scalable, resilient, reconfigurable, highly available platform for real-time and QoS computing. Copyright 2008 ACM.

Abstract
The efficiency of scheduling algorithms is essential in order to attain optimal performances from parallel programming systems. In this paper we use a portable parallel programming environment we have implemented, the pSystem, to evaluate and compare the performance of various scheduling algorithms on shared memory parallel machines. © Springer-Verlag Berlin Heidelberg 1994.

Abstract
Many natural and artificial structures can be represented as complex networks. Computing the frequency of all subgraphs of a certain size can give a very comprehensive structural characterization of these networks. This is known as the subgraph census problem, and it is also important as an intermediate step in the computation of other features of the network, such as network motifs. The subgraph census problem is computationally hard and most associated algorithms for it are sequential. Here we present several increasingly efficient parallel strategies for, culminating in a scalable and adaptive parallel algorithm. We applied our strategies to a representative set of biological networks and achieved almost linear speedups up to 128 processors, paving the way for making it possible to compute the census for bigger networks and larger subgraph sizes.

Abstract
Mining meaningful data from complex biological networks is a critical task in many areas of research. One important example is calculating the frequency of all subgraphs of a certain size, also known as the sub graph census problem. This can provide a very comprehensive structural characterization of a network and is also used as an intermediate step in the computation of network motifs, an important basic building block of networks, that try to bridge the gap between structure and function. The subgraph census problem is com-putationally hard and here we present several parallel strategies to solve this problem. Our initial strategies were refined towards achieving an efficient and scalable adaptive parallel algorithm. This algorithm achieves almost linear speedups up to 128 cores when applied to a representative set of biological networks from different domains and makes the calculation of census for larger subgraph sizes feasible.

Abstract
We present the architecture of a parallel programming system, the di_pSystem. Our target machine consists of clusters of multiprocessors interconnected with very fast networks. The system aims to provide a programming style close to the shared memory programming model. This is achieved by a software layer between the programmer and the operating system that supports the communication between individual computational agents and that dynamically balances the work-load in the system. This layer effectively hides much of the complexity of programming distributed architectures from the programmer while being competitive in performance. The low-level communication in the di_pSystem is implemented using MPI as a backbone. Initial results indicate that the system is close in performance to MPI, a fact that we attribute to its ability to dynamically balance the work-load in the computations. © Springer-Verlag Berlin Heidelberg 1999.