Interference in Multiprocessor Systems with Localized Memory Access Probabilities

Past studies of memory interference in multiprocessor systems have generally assumed that the references of each processor are uniformly distributed among the memory modules. In this paper we develop a model with local referencing, which reflects more closely the behavior of real-life programs. This model is analyzed using Markov chain techniques and expressions are derived for the multiprocessor performance. New expressions are also obtained for the performance in the traditional uniform reference model and are compared with other expressions-available in the literature. Results of a simulation study are given to show the accuracy of the expressions for both models.

Parallel Computation of 2D Morse-Smale Complexes

The Morse-Smale complex is a useful topological data structure for the analysis and visualization of scalar data. This paper describes an algorithm that processes all mesh elements of the domain in parallel to compute the Morse-Smale complex of large two-dimensional data sets at interactive speeds. We employ a reformulation of the Morse-Smale complex using Forman's Discrete Morse Theory and achieve scalability by computing the discrete gradient using local accesses only. We also introduce a novel approach to merge gradient paths that ensures accurate geometry of the computed complex. We demonstrate that our algorithm performs well on both multicore environments and on massively parallel architectures such as the GPU.

Reactive pulsed laser deposition and characterization of niobium nitride thin films

We present a systematic study to explore the effect of important process variables on the composition and structure of niobium nitride thin films synthesized by Reactive Pulsed Laser Deposition (RPLD) technique through ablation of high purity niobium target in the presence of low pressure nitrogen gas. Secondary Ion Mass Spectrometry has been used in a unique way to study and fix gas pressure, substrate temperature and laser fluence, in order to obtain optimized conditions for one variable in single experimental run. The x-ray diffraction and electron microscopic characterization have been complemented by proton elastic backscattering spectroscopy and x-ray photoelectron spectroscopy to understand the incorporation of oxygen and associated non-stoichiometry in the metal to nitrogen ratio. The present study demonstrates that RPLD can be used for obtaining thin film architectures using non-equilibrium processing. Finally the optimized NbN thin films were characterized for their hardness using nano-indentation technique and found to be similar to 30 GPa at the deposition pressure of 8 Pa. (C) 2011 Elsevier B.V. All rights reserved.

Performance modeling and architecture exploration of network processors

This paper proposes a Petri net model for a commercial network processor (Intel iXP architecture) which is a multithreaded multiprocessor architecture. We consider and model three different applications viz., IPv4 forwarding, network address translation, and IP security running on IXP 2400/2850. A salient feature of the Petri net model is its ability to model the application, architecture and their interaction in great detail. The model is validated using the Intel proprietary tool (SDK 3.51 for IXP architecture) over a range of configurations. We conduct a detailed performance evaluation, identify the bottleneck resource, and propose a few architectural extensions and evaluate them in detail.

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.

Transport through an electrostatically defined quantum dot lattice in a two-dimensional electron gas

Quantum dot lattices (QDLs) have the potential to allow for the tailoring of optical, magnetic, and electronic properties of a user-defined artificial solid. We use a dual gated device structure to controllably tune the potential landscape in a GaAs/AlGaAs two-dimensional electron gas, thereby enabling the formation of a periodic QDL. The current-voltage characteristics, I (V), follow a power law, as expected for a QDL. In addition, a systematic study of the scaling behavior of I (V) allows us to probe the effects of background disorder on transport through the QDL. Our results are particularly important for semiconductor-based QDL architectures which aim to probe collective phenomena.

Criticality guided energy aware speculation for speculative multithreaded processors

Unending quest for performance improvement coupled with the advancements in integrated circuit technology have led to the development of new architectural paradigm. Speculative multithreaded architecture (SpMT) philosophy relies on aggressive speculative execution for improved performance. However, aggressive speculative execution comes with a mixed flavor of improving performance, when successful, and adversely affecting the energy consumption (and performance) because of useless computation in the event of mis-speculation. Dynamic instruction criticality information can be usefully applied to control and guide such an aggressive speculative execution. In this paper, we present a model of micro-execution for SpMT architecture that we have developed to determine the dynamic instruction criticality. We have also developed two novel techniques utilizing the criticality information namely delaying the non-critical loads and the criticality based thread-prediction for reducing useless computations and energy consumption. Experimental results showing break-up of critical instructions and effectiveness of proposed techniques in reducing energy consumption are presented in the context of multiscalar processor that implements SpMT architecture. Our experiments show 17.7% and 11.6% reduction in dynamic energy for criticality based thread prediction and criticality based delayed load scheme respectively while the improvement in dynamic energy delay product is 13.9% and 5.5%, respectively. (c) 2012 Published by Elsevier B.V.

Large improvements in application throughput of long-running multi-component applications using batch grids

Computational grids with multiple batch systems (batch grids) can be powerful infrastructures for executing long-running multi-component parallel applications. In this paper, we evaluate the potential improvements in throughput of long-running multi-component applications when the different components of the applications are executed on multiple batch systems of batch grids. We compare the multiple batch executions with executions of the components on a single batch system without increasing the number of processors used for executions. We perform our analysis with a foremost long-running multi-component application for climate modeling, the Community Climate System Model (CCSM). We have built a robust simulator that models the characteristics of both the multi-component application and the batch systems. By conducting large number of simulations with different workload characteristics and queuing policies of the systems, processor allocations to components of the application, distributions of the components to the batch systems and inter-cluster bandwidths, we show that multiple batch executions lead to 55% average increase in throughput over single batch executions for long-running CCSM. We also conducted real experiments with a practical middleware infrastructure and showed that multi-site executions lead to effective utilization of batch systems for executions of CCSM and give higher simulation throughput than single-site executions. Copyright (c) 2011 John Wiley & Sons, Ltd.

Understanding the Magnetization Reversal in Six-Fold Anisotropic Hexagonal Networks

Isolated magnetic nanowires have been studied extensively and the magnetization reversal mechanism is well understood in these systems. But when these nanowires are joined together in different architectures, they behave differently and can give novel properties. Using this approach, one can engineer the network architectures to get artificial anisotropy. Here, we report six-fold anisotropy by joining the magnetic nanowires into hexagonal network. For this study, we also benchmark the widely used micromagnetic packages: OOMMF, Nmag, and LLG-simulator. Further, we propose a local hysteresis method by post processing the spatial magnetization information. With this approach we obtained the hysteresis of nanowires to understand the six-fold anisotropy and the reversal mechanism within the hexagonal networks.

Metal cholate hydrogels: versatile supramolecular systems for nanoparticle embedded soft hybrid materials

This work describes the formation of hydrogels from sodium cholate solution in the presence of a variety of metal ions (Ca2+, Cu2+, Co2+, Zn2+, Cd2+, Hg2+ and Ag+). Morphological studies of the xerogels by electron microscopy reveal the presence of helical nanofibres. The rigid helical framework in the calcium cholate hydrogel was utilised to synthesize hybrid materials (AuNPs and AgNPs). Doping of transition metal salts into the calcium cholate hydrogel brings out the possibility of synthesising metal sulphide nano-architectures keeping the hydrogel network intact. These novel gel-nanoparticle hybrid materials have encouraging application potentials.

Arithmetic coding based lossless compression schemes for power system steady state operational data

Introduction of processor based instruments in power systems is resulting in the rapid growth of the measured data volume. The present practice in most of the utilities is to store only some of the important data in a retrievable fashion for a limited period. Subsequently even this data is either deleted or stored in some back up devices. The investigations presented here explore the application of lossless data compression techniques for the purpose of archiving all the operational data - so that they can be put to more effective use. Four arithmetic coding methods suitably modified for handling power system steady state operational data are proposed here. The performance of the proposed methods are evaluated using actual data pertaining to the Southern Regional Grid of India. (C) 2012 Elsevier Ltd. All rights reserved.

Mechanistic Aspects for the Formation of Copper Dimer Bridged by Phosphonic Acid and Extending Its Dimensionality by Organic and Inorganic Linkers: Synthesis, Structural Characterization, Magnetic Properties, and Theoretical Studies

Six new copper metal complexes with formulas Cu(H2O)(2,2'-bpy) (H2L)](2) center dot H4L center dot 4 H2O (1), {Cu(H2O)(2,2'-bpy)-(H3L)}(2)(H2L)]center dot 2H(2)O (2), Cu(H2O)(1,10-phen)(H2L)](2)center dot 6H(2)O (3), Cu(2,2'-bpy)(H2L)](n)center dot nH(2)O (4), Cu(1,10-phen)(H2L)](n)center dot 3nH(2)O (5), and {Cu(2,2'-bpy)(MoO3)}(2)(L)](n)center dot 2nH(2)O (6) have been synthesized starting from p-xylylenediphosphonic acid (H4L) and 2,2'-bipyridine (2,2'-bpy) or 1,10-phenanthroline (1,10-phen) as secondary linkers and characterized by single crystal X-ray diffraction analysis, IR spectroscopy, and thermogravimetric (TG) analysis. All the complexes were synthesized by hydrothermal methods. A dinuclear motif (Cu-dimer) bridged by phosphonic acid represents a new class of simple building unit (SBU) in the construction of coordination architectures in metal phosphonate chemistry. The initial pH of the reaction mixture induced by the secondary linker plays an important role in the formation of the molecular phosphonates 1, 2, and 3. Temperature dependent hydrothermal synthesis of the compounds 1, 2, and 3 reveals the mechanism of the self assembly of the compounds based on the solubility of the phosphonic acid H4L. Two-dimensional coordination polymers 4, 5, and 6, which are formed by increasing the pH of the reaction mixture, comprise Cu-dimers as nodes, organic (H2L) and inorganic (Mo4O12) ligands as linkers. The void space-areas, created by the (4,4) connected nets in compounds 4 and 5, are occupied by lattice water molecules. Thus compounds 4 and 5 have the potential to accommodate guest species/molecules. Variable temperature magnetic studies of the compounds 3, 4, 5, and 6 reveal the antiferromagnetic interactions between the two Cu(II) ions in the eight membered ring, observed in their crystal structures. A density functional theory (DFT) calculation correlates the conformation of the Cu-dimer ring with the magnitude of the exchange parameter based on the torsion angle of the conformation.

Low dimensional fabrication of giant dielectric CaCu3Ti4O12 through soft e-beam lithography

We report low-dimensional fabrication of technologically important giant dielectric material CaCu3Ti4O12 (CCTO) using soft electron beam lithographic technique. Sol-gel precursor solution of CCTO was prepared using inorganic metal nitrates and Ti-isopropoxide. Employing the prepared precursor solution and e-beam lithographically fabricated resist mask CCTO dots with similar to 200 nm characteristic dimension were fabricated on platinized Si (111) substrate. Phase formation, chemical purity and crystalline nature of fabricated low dimensional structures were investigated with X-ray diffraction (XRD), energy dispersive X-ray spectroscopy (EDS) and selected area electron diffraction (SAED), respectively. Morphological investigations were carried out with the help of scanning electron microscopy (SEM) and transmission electron microscopy (TEM). This kind of solution based fabrication of patterned low-dimensional high dielectric architectures might get potential significance for cost-effective technological applications. (C) 2012 Elsevier B.V. All rights reserved.

Prediction of Ground Water Levels in the Uplands of a Tropical Coastal Riparian Wetland using Artificial Neural Networks

Artificial Neural Networks (ANNs) have been found to be a robust tool to model many non-linear hydrological processes. The present study aims at evaluating the performance of ANN in simulating and predicting ground water levels in the uplands of a tropical coastal riparian wetland. The study involves comparison of two network architectures, Feed Forward Neural Network (FFNN) and Recurrent Neural Network (RNN) trained under five algorithms namely Levenberg Marquardt algorithm, Resilient Back propagation algorithm, BFGS Quasi Newton algorithm, Scaled Conjugate Gradient algorithm, and Fletcher Reeves Conjugate Gradient algorithm by simulating the water levels in a well in the study area. The study is analyzed in two cases-one with four inputs to the networks and two with eight inputs to the networks. The two networks-five algorithms in both the cases are compared to determine the best performing combination that could simulate and predict the process satisfactorily. Ad Hoc (Trial and Error) method is followed in optimizing network structure in all cases. On the whole, it is noticed from the results that the Artificial Neural Networks have simulated and predicted the water levels in the well with fair accuracy. This is evident from low values of Normalized Root Mean Square Error and Relative Root Mean Square Error and high values of Nash-Sutcliffe Efficiency Index and Correlation Coefficient (which are taken as the performance measures to calibrate the networks) calculated after the analysis. On comparison of ground water levels predicted with those at the observation well, FFNN trained with Fletcher Reeves Conjugate Gradient algorithm taken four inputs has outperformed all other combinations.

Implications of program phase behavior on timing analysis

Knowledge about program worst case execution time (WCET) is essential in validating real-time systems and helps in effective scheduling. One popular approach used in industry is to measure execution time of program components on the target architecture and combine them using static analysis of the program. Measurements need to be taken in the least intrusive way in order to avoid affecting accuracy of estimated WCET. Several programs exhibit phase behavior, wherein program dynamic execution is observed to be composed of phases. Each phase being distinct from the other, exhibits homogeneous behavior with respect to cycles per instruction (CPI), data cache misses etc. In this paper, we show that phase behavior has important implications on timing analysis. We make use of the homogeneity of a phase to reduce instrumentation overhead at the same time ensuring that accuracy of WCET is not largely affected. We propose a model for estimating WCET using static worst case instruction counts of individual phases and a function of measured average CPI. We describe a WCET analyzer built on this model which targets two different architectures. The WCET analyzer is observed to give safe estimates for most benchmarks considered in this paper. The tightness of the WCET estimates are observed to be improved for most benchmarks compared to Chronos, a well known static WCET analyzer.