On pattern oriented software architecture for the grid

Precision, sophistication and economic factors in many areas of scientific research that demand very high magnitude of compute power is the order of the day. Thus advance research in the area of high performance computing is getting inevitable. The basic principle of sharing and collaborative work by geographically separated computers is known by several names such as metacomputing, scalable computing, cluster computing, internet computing and this has today metamorphosed into a new term known as grid computing. This paper gives an overview of grid computing and compares various grid architectures. We show the role that patterns can play in architecting complex systems, and provide a very pragmatic reference to a set of well-engineered patterns that the practicing developer can apply to crafting his or her own specific applications. We are not aware of pattern-oriented approach being applied to develop and deploy a grid. There are many grid frameworks that are built or are in the process of being functional. All these grids differ in some functionality or the other, though the basic principle over which the grids are built is the same. Despite this there are no standard requirements listed for building a grid. The grid being a very complex system, it is mandatory to have a standard Software Architecture Specification (SAS). We attempt to develop the same for use by any grid user or developer. Specifically, we analyze the grid using an object oriented approach and presenting the architecture using UML. This paper will propose the usage of patterns at all levels (analysis. design and architectural) of the grid development.

A Survey Of Software Dependability

This paper presents on overview of the issues in precisely defining, specifying and evaluating the dependability of software, particularly in the context of computer controlled process systems. Dependability is intended to be a generic term embodying various quality factors and is useful for both software and hardware. While the developments in quality assurance and reliability theories have proceeded mostly in independent directions for hardware and software systems, we present here the case for developing a unified framework of dependability—a facet of operational effectiveness of modern technological systems, and develop a hierarchical systems model helpful in clarifying this view. In the second half of the paper, we survey the models and methods available for measuring and improving software reliability. The nature of software “bugs”, the failure history of the software system in the various phases of its lifecycle, the reliability growth in the development phase, estimation of the number of errors remaining in the operational phase, and the complexity of the debugging process have all been considered to varying degrees of detail. We also discuss the notion of software fault-tolerance, methods of achieving the same, and the status of other measures of software dependability such as maintainability, availability and safety.

Software simulation of the EEG

The literature contains many examples of digital procedures for the analytical treatment of electroencephalograms, but there is as yet no standard by which those techniques may be judged or compared. This paper proposes one method of generating an EEG, based on a computer program for Zetterberg's simulation. It is assumed that the statistical properties of an EEG may be represented by stationary processes having rational transfer functions and achieved by a system of software fillers and random number generators.The model represents neither the neurological mechanism response for generating the EEG, nor any particular type of EEG record; transient phenomena such as spikes, sharp waves and alpha bursts also are excluded. The basis of the program is a valid ‘partial’ statistical description of the EEG; that description is then used to produce a digital representation of a signal which if plotted sequentially, might or might not by chance resemble an EEG, that is unimportant. What is important is that the statistical properties of the series remain those of a real EEG; it is in this sense that the output is a simulation of the EEG. There is considerable flexibility in the form of the output, i.e. its alpha, beta and delta content, which may be selected by the user, the same selected parameters always producing the same statistical output. The filtered outputs from the random number sequences may be scaled to provide realistic power distributions in the accepted EEG frequency bands and then summed to create a digital output signal, the ‘stationary EEG’. It is suggested that the simulator might act as a test input to digital analytical techniques for the EEG, a simulator which would enable at least a substantial part of those techniques to be compared and assessed in an objective manner. The equations necessary to implement the model are given. The program has been run on a DEC1090 computer but is suitable for any microcomputer having more than 32 kBytes of memory; the execution time required to generate a 25 s simulated EEG is in the region of 15 s.

The role of His-134, -147, and -150 residues in subunit assembly, cofactor binding, and catalysis of sheep liver cytosolic serine hydroxymethyltransferase

In an attempt to unravel the role of conserved histidine residues in the structure-function of sheep liver cytosolic serine hydroxymethyltransferase (SHMT), three site-specific mutants (H134N, H147N, and H150N) were constructed and expressed, H134N and H147N SHMTs had K-m values for L-serine, L-allo-threonine and beta-phenylserine similar to that of wild type enzyme, although the k(cat) values were markedly decreased, H134N SHMT was obtained in a dimeric form with only 6% of bound pyridoxal 5'-phosphate (PLP) compared with the wild type enzyme, Increasing concentrations of PLP (up to 500 mu M) enhanced the enzyme activity without changing its oligomeric structure, indicating that His-134 may be involved in dimer-dimer interactions, H147N SHMT was obtained in a tetrameric form but with very little PLP (3%) bound to it, suggesting that this residue was probably involved in cofactor binding, Unlike the wild type enzyme, the cofactor could be easily removed by dialysis from H147N SHMT, and the apoenzyme thus formed was present predominantly in the dimeric form, indicating that PLP binding is at the dimer-dimer interface, H150N SHMT was obtained in a tetrameric form with bound PLP, However, the mutant had very little enzyme activity (<2%). The k(cat)/K-m values for L-serine, L-allo-threonine and beta-phenylserine were 80-, 56-, and SS-fold less compared with wild type enzyme, Unlike the wild type enzyme, it failed to form the characteristic quinonoid intermediate and was unable to carry out the exchange of 2-S proton from glycine in the presence of H-4-folate. However, it could form an external aldimine with serine and glycine, The wild type and the mutant enzyme had similar K-d values for serine and glycine, These results suggest that His-150 may be the base that abstracts the alpha-proton of the substrate, leading to formation of the quinonoid intermediate in the reaction catalyzed by SHMT.

NUVIEW:software for display and interactive manipulation of nucleic acid models

The NUVIEW software package allows skeletal models of any double helical nucleic acid molecule to be displayed out a graphics monitor and to apply various rotations, translations and scaling transformations interactively, through the keyboard. The skeletal model is generated by connecting any pair of representative points, one from each of the bases in the basepair. In addition to the above mentioned manipulations, the base residues can be identified by using a locator and the distance between any pair of residues can be obtained. A sequence based color coded display allows easy identification of sequence repeats, such as runs of Adenines. The real time interactive manipulation of such skeletal models for large DNA/RNA double helices, can be used to trace the path of the nucleic acid chain in three dimensions and hence get a better idea of its topology, location of linear or curved regions, distances between far off regions in the sequence etc. A physical picture of these features will assist in understanding the relationship between base sequence, structure and biological function in nucleic acids.

NUPARM and NUCGEN: software for analysis and generation of sequence dependent nucleic acid structures

Software packages NUPARM and NUCGEN, are described, which can be used to understand sequence directed structural variations in nucleic acids, by analysis and generation of non-uniform structures. A set of local inter basepair parameters (viz. tilt, roll, twist, shift, slide and rise) have been defined, which use geometry and coordinates of two successive basepairs only and can be used to generate polymeric structures with varying geometries for each of the 16 possible dinucleotide steps. Intra basepair parameters, propeller, buckle, opening and the C6...C8 distance can also be varied, if required, while the sugar phosphate backbone atoms are fixed in some standard conformation ill each of the nucleotides. NUPARM can be used to analyse both DNA and RNA structures, with single as well as double stranded helices. The NUCGEN software generates double helical models with the backbone fixed in B-form DNA, but with appropriate modifications in the input data, it can also generate A-form DNA ar rd RNA duplex structures.

Software Pipelined Execution of Stream Programs on GPUs

The StreamIt programming model has been proposed to exploit parallelism in streaming applications on general purpose multi-core architectures. This model allows programmers to specify the structure of a program as a set of filters that act upon data, and a set of communication channels between them. The StreamIt graphs describe task, data and pipeline parallelism which can be exploited on modern Graphics Processing Units (GPUs), as they support abundant parallelism in hardware. In this paper, we describe the challenges in mapping StreamIt to GPUs and propose an efficient technique to software pipeline the execution of stream programs on GPUs. We formulate this problem - both scheduling and assignment of filters to processors - as an efficient Integer Linear Program (ILP), which is then solved using ILP solvers. We also describe a novel buffer layout technique for GPUs which facilitates exploiting the high memory bandwidth available in GPUs. The proposed scheduling utilizes both the scalar units in GPU, to exploit data parallelism, and multiprocessors, to exploit task and pipelin parallelism. Further it takes into consideration the synchronization and bandwidth limitations of GPUs, and yields speedups between 1.87X and 36.83X over a single threaded CPU.

Sensor network deployment for agronomical data gathering in semi-arid regions

We share our experience in planning, designing and deploying a wireless sensor network of one square kilometre area. Environmental data such as soil moisture, temperature, barometric pressure, and relative humidity are collected in this area situated in the semi-arid region of Karnataka, India. It is a hope that information derived from this data will benefit the marginal farmer towards improving his farming practices. Soon after establishing the need for such a project, we begin by showing the big picture of such a data gathering network, the software architecture we have used, the range measurements needed for determining the sensor density, and the packaging issues that seem to play a crucial role in field deployments. Our field deployment experiences include designing with intermittent grid power, enhancing software tools to aid quicker and effective deployment, and flash memory corruption. The first results on data gathering look encouraging.

Data mining approaches to software fault diagnosis

Automatic identification of software faults has enormous practical significance. This requires characterizing program execution behavior and the use of appropriate data mining techniques on the chosen representation. In this paper, we use the sequence of system calls to characterize program execution. The data mining tasks addressed are learning to map system call streams to fault labels and automatic identification of fault causes. Spectrum kernels and SVM are used for the former while latent semantic analysis is used for the latter The techniques are demonstrated for the intrusion dataset containing system call traces. The results show that kernel techniques are as accurate as the best available results but are faster by orders of magnitude. We also show that latent semantic indexing is capable of revealing fault-specific features.