Reconfigurable Viterbi decoder on mesh connected multiprocessor architecture

In modern wireline and wireless communication systems, Viterbi decoder is one of the most compute intensive and essential elements. Each standard requires a different configuration of Viterbi decoder. Hence there is a need to design a flexible reconfigurable Viterbi decoder to support different configurations on a single platform. In this paper we present a reconfigurable Viterbi decoder which can be reconfigured for standards such as WCDMA, CDMA2000, IEEE 802.11, DAB, DVB, and GSM. Different parameters like code rate, constraint length, polynomials and truncation length can be configured to map any of the above mentioned standards. Our design provides higher throughput and scalable power consumption in various configuration of the reconfigurable Viterbi decoder. The power and throughput can also be optimized for different standards.

RECONNECT: A NoC for polymorphic ASICs using a low overhead single cycle router

A polymorphic ASIC is a runtime reconfigurable hardware substrate comprising compute and communication elements. It is a ldquofuture proofrdquo custom hardware solution for multiple applications and their derivatives in a domain. Interoperability between application derivatives at runtime is achieved through hardware reconfiguration. In this paper we present the design of a single cycle Network on Chip (NoC) router that is responsible for effecting runtime reconfiguration of the hardware substrate. The router design is optimized to avoid FIFO buffers at the input port and loop back at output crossbar. It provides virtual channels to emulate a non-blocking network and supports a simple X-Y relative addressing scheme to limit the control overhead to 9 bits per packet. The 8times8 honeycomb NoC (RECONNECT) implemented in 130 nm UMC CMOS standard cell library operates at 500 MHz and has a bisection bandwidth of 28.5 GBps. The network is characterized for random, self-similar and application specific traffic patterns that model the execution of multimedia and DSP kernels with varying network loads and virtual channels. Our implementation with 4 virtual channels has an average network latency of 24 clock cycles and throughput of 62.5% of the network capacity for random traffic. For application specific traffic the latency is 6 clock cycles and throughput is 87% of the network capacity.

Optimizing a piezometric network in the estimation of the groundwater budget: a case study from a crystalline-rock watershed in southern India

An estimate of the groundwater budget at the catchment scale is extremely important for the sustainable management of available water resources. Water resources are generally subjected to over-exploitation for agricultural and domestic purposes in agrarian economies like India. The double water-table fluctuation method is a reliable method for calculating the water budget in semi-arid crystalline rock areas. Extensive measurements of water levels from a dense network before and after the monsoon rainfall were made in a 53 km(2)atershed in southern India and various components of the water balance were then calculated. Later, water level data underwent geostatistical analyses to determine the priority and/or redundancy of each measurement point using a cross-validation method. An optimal network evolved from these analyses. The network was then used in re-calculation of the water-balance components. It was established that such an optimized network provides far fewer measurement points without considerably changing the conclusions regarding groundwater budget. This exercise is helpful in reducing the time and expenditure involved in exhaustive piezometric surveys and also in determining the water budget for large watersheds (watersheds greater than 50 km(2)).

Towards a green synthesis of isoquinoline: Beckmann rearrangement of E,-cinnamaldoxime over H-zeolites

Isoquinoline was prepared through the Beckmann rearrangement of cinnamaldoxime over different H-zeolites, K-10 montmorillonite clay, amorphous SiO2–Al2O3 and γ-alumina under well-optimized conditions of temperature, weight hourly space velocity and catalyst loading. Cinnamaldoxime under ambient reaction conditions over the catalysts underwent migration of the anti-styryl moiety to electron deficient nitrogen (Beckmann rearrangement) followed by an intramolecular cyclization to yield isoquinoline. Cinnamo-nitrile (dehydration product) and cinnamaldehyde were formed as by-products. Isoquinoline formation was high on zeolite catalysts (ca. >86.5%) and mordenite (ca. 92.3%) was the most efficient in the series. Catalysts were susceptible for deactivation and the decrease in the percentage conversion of oxime with time is associated with a corresponding increase in the acid hydrolysis producing salicylaldehyde at later stages of the reaction. However, these catalysts retain activity considerably and can be recycled without loss of activity and change of product distribution.

Identification of Hadronically Decaying Tau Leptons in Searches for Heavy MSSM Higgs Bosons with the CMS Detector at the CERN LHC

This thesis describes methods for the reliable identification of hadronically decaying tau leptons in the search for heavy Higgs bosons of the minimal supersymmetric standard model of particle physics (MSSM). The identification of the hadronic tau lepton decays, i.e. tau-jets, is applied to the gg->bbH, H->tautau and gg->tbH+, H+->taunu processes to be searched for in the CMS experiment at the CERN Large Hadron Collider. Of all the event selections applied in these final states, the tau-jet identification is the single most important event selection criterion to separate the tiny Higgs boson signal from a large number of background events. The tau-jet identification is studied with methods based on a signature of a low charged track multiplicity, the containment of the decay products within a narrow cone, an isolated electromagnetic energy deposition, a non-zero tau lepton flight path, the absence of electrons, muons, and neutral hadrons in the decay signature, and a relatively small tau lepton mass compared to the mass of most hadrons. Furthermore, in the H+->taunu channel, helicity correlations are exploited to separate the signal tau jets from those originating from the W->taunu decays. Since many of these identification methods rely on the reconstruction of charged particle tracks, the systematic uncertainties resulting from the mechanical tolerances of the tracking sensor positions are estimated with care. The tau-jet identification and other standard selection methods are applied to the search for the heavy neutral and charged Higgs bosons in the H->tautau and H+->taunu decay channels. For the H+->taunu channel, the tau-jet identification is redone and optimized with a recent and more detailed event simulation than previously in the CMS experiment. Both decay channels are found to be very promising for the discovery of the heavy MSSM Higgs bosons. The Higgs boson(s), whose existence has not yet been experimentally verified, are a part of the standard model and its most popular extensions. They are a manifestation of a mechanism which breaks the electroweak symmetry and generates masses for particles. Since the H->tautau and H+->taunu decay channels are important for the discovery of the Higgs bosons in a large region of the permitted parameter space, the analysis described in this thesis serves as a probe for finding out properties of the microcosm of particles and their interactions in the energy scales beyond the standard model of particle physics.

Microarchitecture sensitive empirical models for compiler optimizations.

This paper proposes the use of empirical modeling techniques for building microarchitecture sensitive models for compiler optimizations. The models we build relate program performance to settings of compiler optimization flags, associated heuristics and key microarchitectural parameters. Unlike traditional analytical modeling methods, this relationship is learned entirely from data obtained by measuring performance at a small number of carefully selected compiler/microarchitecture configurations. We evaluate three different learning techniques in this context viz. linear regression, adaptive regression splines and radial basis function networks. We use the generated models to a) predict program performance at arbitrary compiler/microarchitecture configurations, b) quantify the significance of complex interactions between optimizations and the microarchitecture, and c) efficiently search for'optimal' settings of optimization flags and heuristics for any given microarchitectural configuration. Our evaluation using benchmarks from the SPEC CPU2000 suits suggests that accurate models (< 5% average error in prediction) can be generated using a reasonable number of simulations. We also find that using compiler settings prescribed by a model-based search can improve program performance by as much as 19% (with an average of 9.5%) over highly optimized binaries.

A genetic algorithm with characteristic amplification through multiple geographically isolated populations and varied fitness landscapes

This paper proposes a new approach, wherein multiple populations are evolved on different landscapes. The problem statement is broken down, to describe discrete characteristics. Each landscape, described by its fitness landscape is used to optimize or amplify a certain characteristic or set of characteristics. Individuals from each of these populations are kept geographically isolated from each other Each population is evolved individually. After a predetermined number of evolutions, the system of populations is analysed against a normalized fitness function. Depending on this score and a predefined merging scheme, the populations are merged, one at a time, while continuing evolution. Merging continues until only one final population remains. This population is then evolved, following which the resulting population will contain the optimal solution. The final resulting population will contain individuals which have been optimized against all characteristics as desired by the problem statement. Each individual population is optimized for a local maxima. Thus when populations are merged, the effect is to produce a new population which is closer to the global maxima.

A genetic algorithm with characteristic amplification through multiple geographically isolated populations and varied fitness landscapes

This paper proposes a new approach, wherein multiple populations are evolved on different landscapes. The problem statement is broken down, to describe discrete characteristics. Each landscape, described by its fitness landscape is used to optimize or amplify a certain characteristic or set of characteristics. Individuals from each of these populations are kept geographically isolated from each other Each population is evolved individually. After a predetermined number of evolutions, the system of populations is analysed against a normalized fitness function. Depending on this score and a predefined merging scheme, the populations are merged, one at a time, while continuing evolution. Merging continues until only one final population remains. This population is then evolved, following which the resulting population will contain the optimal solution. The final resulting population will contain individuals which have been optimized against all characteristics as desired by the problem statement. Each individual population is optimized for a local maxima. Thus when populations are merged, the effect is to produce a new population which is closer to the global maxima.

An alkaline direct borohydride fuel cell with hydrogen peroxide as oxidant

A novel alkaline direct borohydride fuel cell (ADBFC) using varying concentrations of hydrogen peroxide as oxidant and sodium borohydride with sodium hydroxide, each of differing concentration, as fuel is reported. A peak power density of ca. 150 in W cm(-2) at a cell voltage of 540 mV can be achieved from the optimized ADBFC operating at 70 degrees C. (c) 2004 Elsevier B.V. All rights reserved.

Vector Evaluated Particle Swarm Optimization (VEPSO) of Supersonic Ejector for Hydrogen Fuel Cells

Fuel cells are emerging as alternate green power producers for both large power production and for use in automobiles. Hydrogen is seen as the best option as a fuel; however, hydrogen fuel cells require recirculation of unspent hydrogen. A supersonic ejector is an apt device for recirculation in the operating regimes of a hydrogen fuel cell. Optimal ejectors have to be designed to achieve best performances. The use of the vector evaluated particle swarm optimization technique to optimize supersonic ejectors with a focus on its application for hydrogen recirculation in fuel cells is presented here. Two parameters, compression ratio and efficiency, have been identified as the objective functions to be optimized. Their relation to operating and design parameters of ejector is obtained by control volume based analysis using a constant area mixing approximation. The independent parameters considered are the area ratio and the exit Mach number of the nozzle. The optimization is carried out at a particularentrainment ratio and results in a set of nondominated solutions, the Pareto front. A set of such curves can be used for choosing the optimal design parameters of the ejector.

Recognition of active and inactive catalytic triads: A template based approach

It Is well established that a sequence template along with the database is a powerful tool for identifying the biological function of proteins. Here, we describe a method for predicting the catalytic nature of certain proteins among the several protein structures deposited in the Protein Data Bank (PDB) For the present study, we considered a catalytic triad template (Ser-His-Asp) found in serine proteases We found that a geometrically optimized active site template can be used as a highly selective tool for differentiating an active protein among several inactive proteins, based on their Ser-His-Asp interactions. For any protein to be proteolytic in nature, the bond angle between Ser O-gamma-Ser H-gamma His N-epsilon 2 in the catalytic triad needs to be between 115 degrees and 140 degrees The hydrogen bond distance between Ser H-gamma His N-epsilon 2 is more flexible in nature and it varies from 2 0 angstrom to 27 angstrom while in the case of His H-delta 1 Asp O-delta 1, it is from 1.6 angstrom to 2.0 angstrom In terms of solvent accessibility, most of the active proteins lie in the range of 10-16 angstrom(2), which enables easy accessibility to the substrate These observations hold good for most catalytic triads and they can be employed to predict proteolytic nature of these catalytic triads (C) 2010 Elsevier B V All rights reserved.

Ion channel formation by zervamicin-IIB. A molecular modelling study.

Zervamicin-IIB (Zrv-IIB) is a 16 residue peptaibol which forms voltage-activated, multiple conductance level channels in planar lipid bilayers. A molecular model of Zrv-IIB channels is presented. The structure of monomeric Zrv-IIB is based upon the crystal structure of Zervamicin-Leu. The helical backbone is kinked by a hydroxyproline residue at position 10. Zrv-IIB channels are modelled as helix bundles of from 4 to 8 parallel helices surrounding a central pore. The monomers are packed with their C-terminal helical segments in close contact, and the bundles are stabilized by hydrogen bonds between glutamine 11 and hydroxyproline 10 of adjacent helices. Interaction energy profiles for movement of three different probes species (K+, Cl- and water) through the central pore are analyzed. The conformations of: (a) the sidechain of glutamine 3; (b) the hydroxyl group of hydroxyproline 10; and (c) the C-terminal hydroxyl group are "optimized" in order to maximize favourable interactions between the channel and the probes, resulting in favourable interaction energy profiles for all three. This suggests that conformational flexibility of polar sidechains enables the channel lining to mimic an aqueous environment.

Measurement of the top quark mass with dilepton events selected using neuroevolution at CDF

We report a measurement of the top quark mass $M_t$ in the dilepton decay channel $t\bar{t}\to b\ell'^{+}\nu'_\ell\bar{b}\ell^{-}\bar{\nu}_{\ell}$. Events are selected with a neural network which has been directly optimized for statistical precision in top quark mass using neuroevolution, a technique modeled on biological evolution. The top quark mass is extracted from per-event probability densities that are formed by the convolution of leading order matrix elements and detector resolution functions. The joint probability is the product of the probability densities from 344 candidate events in 2.0 fb$^{-1}$ of $p\bar{p}$ collisions collected with the CDF II detector, yielding a measurement of $M_t= 171.2\pm 2.7(\textrm{stat.})\pm 2.9(\textrm{syst.})\mathrm{GeV}/c^2$.

An alkaline direct borohydride fuel cell with hydrogen peroxide as oxidant

A novel alkaline direct borohydride fuel cell (ADBFC) using varying concentrations of hydrogen peroxide as oxidant and sodium borohydride with sodium hydroxide, each of differing concentration, as fuel is reported. A peak power density of ca. 150 in W cm(-2) at a cell voltage of 540 mV can be achieved from the optimized ADBFC operating at 70 degrees C. (c) 2004 Elsevier B.V. All rights reserved.

SiD Letter of Intent

Letter of intent describing SiD (Silicon Detector) for consideration by the International Linear Collider IDAG panel. This detector concept is founded on the use of silicon detectors for vertexing, tracking, and electromagnetic calorimetry. The detector has been cost-optimized as a general-purpose detector for a 500 GeV electron-positron linear collider.