Abstract: In this work, we study the impact of dynamically changing link slowdowns on the stability properties of packetswitched networks under the Adversarial Queueing Theory framework. Especially, we consider the Adversarial, Quasi-Static Slowdown Queueing Theory model, where each link slowdown may take on values in the two-valued set of integers {1, D} with D > 1 which remain fixed for a long time, under a (w, p)-adversary. In this framework, we present an innovative systematic construction for the estimation of adversarial injection rate lower bounds, which, if exceeded, cause instability in networks that use the LIS (Longest-in- System) protocol for contention-resolution. In addition, we show that a network that uses the LIS protocol for contention-resolution may result in dropping its instability bound at injection rates p > 0 when the network size and the high slowdown D take large values. This is the best ever known instability lower bound for LIS networks.
Abstract: In the past few years there is a change in the view of high performance applications and parallel computing. Initially such applications were targeted towards dedicated parallel machines. Recently trend is changing towards building meta-applications composed of several modules that exploit heterogeneous platforms and employ hybrid forms of parallelism. The aim of this paper is to propose a model of virtual parallel computing. Virtual parallel computing system provides a flexible object oriented software framework that makes it easy for programmers to write various parallel applications.
Abstract: The work reported in this paper proposes
Swarm-Array computing, a novel technique inspired by swarm
robotics, and built on the foundations of autonomic and parallel
computing. The approach aims to apply autonomic computing
constructs to parallel computing systems and in effect achieve the
self-ware objectives that describe self-managing systems. The
constitution of swarm-array computing comprising four constituents,
namely the computing system, the problem/task, the swarm and the
landscape is considered. Approaches that bind these constituents
together are proposed. Space applications employing FPGAs are
identified as a potential area for applying swarm-array computing for
building reliable systems. The feasibility of a proposed approach is
validated on the SeSAm multi-agent simulator and landscapes are
generated using the MATLAB toolkit.
Abstract: Message Passing Interface is widely used for Parallel
and Distributed Computing. MPICH and LAM are popular open
source MPIs available to the parallel computing community also
there are commercial MPIs, which performs better than MPICH etc.
In this paper, we discuss a commercial Message Passing Interface, CMPI
(C-DAC Message Passing Interface). C-MPI is an optimized
MPI for CLUMPS. It is found to be faster and more robust compared
to MPICH. We have compared performance of C-MPI and MPICH
on Gigabit Ethernet network.
Abstract: One of the major problems in genomic field is to perform sequence comparison on DNA and protein sequences. Executing sequence comparison on the DNA and protein data is a computationally intensive task. Sequence comparison is the basic step for all algorithms in protein sequences similarity. Parallel computing is an attractive solution to provide the computational power needed to speedup the lengthy process of the sequence comparison. Our main research is to enhance the protein sequence algorithm using dynamic programming method. In our approach, we parallelize the dynamic programming algorithm using multithreaded program to perform the sequence comparison and also developed a distributed protein database among many PCs using Remote Method Interface (RMI). As a result, we showed how different sizes of protein sequences data and computation of scoring matrix of these protein sequence on different number of processors affected the processing time and speed, as oppose to sequential processing.
Abstract: With the rapid development in the field of life
sciences and the flooding of genomic information, the need for faster
and scalable searching methods has become urgent. One of the
approaches that were investigated is indexing. The indexing methods
have been categorized into three categories which are the lengthbased
index algorithms, transformation-based algorithms and mixed
techniques-based algorithms. In this research, we focused on the
transformation based methods. We embedded the N-gram method
into the transformation-based method to build an inverted index
table. We then applied the parallel methods to speed up the index
building time and to reduce the overall retrieval time when querying
the genomic database. Our experiments show that the use of N-Gram
transformation algorithm is an economical solution; it saves time and
space too. The result shows that the size of the index is smaller than
the size of the dataset when the size of N-Gram is 5 and 6. The
parallel N-Gram transformation algorithm-s results indicate that the
uses of parallel programming with large dataset are promising which
can be improved further.