A Novel Cache Architecture and Placement Framework for Packet Forwarding Engines

Packet forwarding is a memory-intensive application requiring multiple accesses through a trie structure. With the requirement to process packets at line rates, high-performance routers need to forward millions of packets every second with each packet needing up to seven memory accesses. Earlier work shows that a single cache for the nodes of a trie can reduce the number of external memory accesses. It is observed that the locality characteristics of the level-one nodes of a trie are significantly different from those of lower level nodes. Hence, we propose a heterogeneously segmented cache architecture (HSCA) which uses separate caches for level-one and lower level nodes, each with carefully chosen sizes. Besides reducing misses, segmenting the cache allows us to focus on optimizing the more frequently accessed level-one node segment. We find that due to the nonuniform distribution of nodes among cache sets, the level-one nodes cache is susceptible t high conflict misses. We reduce conflict misses by introducing a novel two-level mapping-based cache placement framework. We also propose an elegant way to fit the modified placement function into the cache organization with minimal increase in access time. Further, we propose an attribute preserving trace generation methodology which emulates real traces and can generate traces with varying locality. Performanc results reveal that our HSCA scheme results in a 32 percent speedup in average memory access time over a unified nodes cache. Also, HSC outperforms IHARC, a cache for lookup results, with as high as a 10-fold speedup in average memory access time. Two-level mappin further enhances the performance of the base HSCA by up to 13 percent leading to an overall improvement of up to 40 percent over the unified scheme.

Spatial Data Mining and Modeling for visualisation of Rapid Urbanisation

Rapid urbanisation in India has posed serious challenges to the decision makers in regional planning involving plethora of issues including provision of basic amenities (like electricity, water, sanitation, transport, etc.). Urban planning entails an understanding of landscape and urban dynamics with causal factors. Identifying, delineating and mapping landscapes on temporal scale provide an opportunity to monitor the changes, which is important for natural resource management and sustainable planning activities. Multi-source, multi-sensor, multi-temporal, multi-frequency or multi-polarization remote sensing data with efficient classification algorithms and pattern recognition techniques aid in capturing these dynamics. This paper analyses the landscape dynamics of Greater Bangalore by: (i) characterisation of direct impervious surface, (ii) computation of forest fragmentation indices and (iii) modeling to quantify and categorise urban changes. Linear unmixing is used for solving the mixed pixel problem of coarse resolution super spectral MODIS data for impervious surface characterisation. Fragmentation indices were used to classify forests – interior, perforated, edge, transitional, patch and undetermined. Based on this, urban growth model was developed to determine the type of urban growth – Infill, Expansion and Outlying growth. This helped in visualising urban growth poles and consequence of earlier policy decisions that can help in evolving strategies for effective land use policies.

An empirical evaluation of a framework for design for variety and novelty

The objective of this paper is to empirically evaluate a framework for designing – GEMS of SAPPhIRE as req-sol – to check if it supports design for variety and novelty. A set of observational studies is designed where three teams of two designers each, solve three different design problems in the following order: without any support, using the framework, and using a combination of the framework and a catalogue. Results from the studies reveal that both variety and novelty of the concept space increases with the use of the framework or the framework and the catalogue. However, the number of concepts and the time taken by the designers decreases with the use of the framework and, the framework and the catalogue. Based on the results and the interview sessions with the designers, an interactive framework for designing to be supported on a computer is proposed as future work.

Learning from positive and unlabelled examples using maximum margin clustering

Learning from Positive and Unlabelled examples (LPU) has emerged as an important problem in data mining and information retrieval applications. Existing techniques are not ideally suited for real world scenarios where the datasets are linearly inseparable, as they either build linear classifiers or the non-linear classifiers fail to achieve the desired performance. In this work, we propose to extend maximum margin clustering ideas and present an iterative procedure to design a non-linear classifier for LPU. In particular, we build a least squares support vector classifier, suitable for handling this problem due to symmetry of its loss function. Further, we present techniques for appropriately initializing the labels of unlabelled examples and for enforcing the ratio of positive to negative examples while obtaining these labels. Experiments on real-world datasets demonstrate that the non-linear classifier designed using the proposed approach gives significantly better generalization performance than the existing relevant approaches for LPU.

Characterization of alinite cements through X-ray diffraction and mas 29Si NMR studies

Alinite cements have been synthesized using mining and steel plant wastes and pulverized fuel ash (fly ash) as raw materials and a clinkering temperature of 1150°C. The cements possess hydration characteristics comparable to those of portland cements. X-ray diffraction studies on these samples confirm the presence of alinite as the predominant phase. MAS 29Si NMR spectra have been used to distinguish alinite and alite cements. While both show resonances characteristic of Q° type silicate species, the portland cements exhibit three distinct peaks corresponding to three inequivalent SiO4 units present, while alinite shows a single sharp peak corresponding to the unique Si position.

Formal description, compression and transformation of digital pictures

This paper describes the application of vector spaces over Galois fields, for obtaining a formal description of a picture in the form of a very compact, non-redundant, unique syntactic code. Two different methods of encoding are described. Both these methods consist in identifying the given picture as a matrix (called picture matrix) over a finite field. In the first method, the eigenvalues and eigenvectors of this matrix are obtained. The eigenvector expansion theorem is then used to reconstruct the original matrix. If several of the eigenvalues happen to be zero this scheme results in a considerable compression. In the second method, the picture matrix is reduced to a primitive diagonal form (Hermite canonical form) by elementary row and column transformations. These sequences of elementary transformations constitute a unique and unambiguous syntactic code-called Hermite code—for reconstructing the picture from the primitive diagonal matrix. A good compression of the picture results, if the rank of the matrix is considerably lower than its order. An important aspect of this code is that it preserves the neighbourhood relations in the picture and the primitive remains invariant under translation, rotation, reflection, enlargement and replication. It is also possible to derive the codes for these transformed pictures from the Hermite code of the original picture by simple algebraic manipulation. This code will find extensive applications in picture compression, storage, retrieval, transmission and in designing pattern recognition and artificial intelligence systems.

Coordination polymers and hybrid networks of different dimensionalities formed by metal sulfites

In our effort to explore the use of the sulfite ion to design hybrid and open-framework materials, we have been able to prepare, under hydrothermal conditions, zero-dimensional [Zn(C12H8N2)(SO3)]center dot 2H(2)O, I (a = 7.5737(5) angstrom, b = 10.3969(6) angstrom, c = 10.3986(6) angstrom, alpha = 64.172(1)degrees, beta = 69.395(1)degrees, gamma = 79.333(1)degrees, Z = 2, and space group P (1) over bar), one-dimensional [Zn-2(C12H8N2)(SO3)(2)(H2O)], II (a = 8.0247(3) angstrom, b = 9.4962(3) angstrom, c = 10.2740(2) A, alpha = 81.070(1)degrees, beta = 80.438(1)degrees, gamma = 75.66(5)degrees, Z = 2, and space group P (1) over bar), two-dimensional [Zn-2(C10H8N2)(SO3)(2)]center dot H2O, III (a = 16.6062(1) angstrom, b = 4.7935(1) angstrom, c = 19.2721(5) angstrom, beta = 100.674(2)degrees, Z = 4, and space group C2/c), and three-dimensional [Zn-4(C6H12N2)(SO3)(4)(H2O)(4)], IV (a = 11.0793(3) angstrom, c = 8.8246(3) angstrom, Z = 2, and space group P42nm), of which the last three are coordination polymers. A hybrid open-framework sulfite-sulfate of the composition [C2H10N2][Nd(SO3)(SO4)(H2O)](2), V (a = 9.0880(3) angstrom, b = 6.9429(2) angstrom, c = 13.0805(5) A, beta = 91.551(2)degrees, Z = 2, and space group P2(1)/c), with a layered structure containing metal-oxygen-metal bonds has also been described.

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.

Diffusion Anomaly in Silicalite and VPI-5 from Molecular Dynamics Simulations

Molecular dynamics (MD) simulations on rigid and flexible framework models of silicalite and a rigid framework model of the aluminophosphate VPI-5 for different sorbate diameters are reported. The sorbate-host interactions are modeled in terms of simple atom-atom Lennard-Jones interactions. The results suggest that the diffusion coefficient exhibits an anomaly as gamma approaches unity. The MD results confirm the existence of a linear regime for sorbate diameters significantly smaller than the channel diameter and an anomalous regime observed for sorbate diameters comparable to the channel diameter. The power spectra obtained by Fourier transformation of the velocity autocorrelation function indicate that there is an increase in the intensity of the low-frequency component for the velocity component parallel to the direction of motion for the sorbate diameter in the anomalous regime. The present results suggest that the diffusion anomaly is observed irrespective of (1) the geometry and topology of the pore structure and (2) the nature of the host material. The results are compared with the work of Derouane and co-workers, who have suggested the existence of ''floating molecules'' on the basis of earlier theoretical and computational approaches.

Thermodynamics of oxygen in liquid copper, lead and copper lead alloys

Solid oxide galvanic cells of the type Pt, Ni-NiO I Solid electrolyte ( Ometa,, Cermet. Pt were used to measure the activity coefficient of oxygen in liquid copper at 11 00 and 1 300eC, and in lead at 11 00'C. Similar cells were used to study the activity coefficient of oxygen in the whole range of Cu + Pb alloys at 1100'C and in lead-rich alloys at 900 and 750'C.The results obtained are discussed in terms of proposed solution models. An equation based on the formation of 'species' of the form M,O in solutions of oxygen in binary alloys is shown to fit the experimental data.

Gibbs free energies of formation of indium (III) oxide and sulphate

Emf measurements on the galvanic cell Pt, Ta, In + In,O, / Tho,-Y,03 / Cu + C+O, Pt were used to obtain the standard free energy of formation of 1%03fr om 600 to 900°C. Differential thermal analysis was used to detect the decomposition of In2(S0,), under controlled SO2 + O2 + Ar mixtures in thqtemperature range 640-8wC. X-ray diffraction analysis indicated that the decomposition product was 1%03 without an oxywlphate intermediate. The following equations were obtained for the variation of the standard free-energy change(Jlmole) with temperature:

An improved X-ray structural analysis for determining cation distribution in ZnFe2O4 and ZnFe2O4- Fe3O4 solid solutions

The distribution of zinc cation between crystallographically nonequivalent positions in ZnFe204 has been determined by anomalous X-ray scattering near the Zn K absorption edge. Measured intensity ratio with two energies close to the edge can be quantitatively explained only by assigning all zinc cations to the tetrahedral position in the approximately cubic close packed array of oxygen ions. A similar conclusion has also been reached for ZnxFe3-x04 solid solutions with x = 0.73, 0.54 and 0.35 employing the improved X-ray method. This is consistent with the EXAFS results which indicate an almost unchanged environmental structure around zinc cation in these solid solutions.

Thermodynamic properties of Ln-O (Ln = La, Pr, Nd) solid solutions and their deoxidation by molten salt electrolysis

The lanthanide metals lanthanum, praseodymium and neodymium containing 2,200, 2,600, 1,850 mass ppm oxygen, respectively, were deoxidized to 20-30 ppm level at 1,073 K by an electrochemical method. The metal to be deoxidized was used as the cathode in an electrolysis cell which consisted of a graphite anode and molten CaCl2 electrolyte. The calcium metal produced at the cathode by electrolysis effectively deoxidized the lanthanide metal. Calcium oxide produced by deoxidation, dissolved in the melt. The liberation of carbon monoxide/dioxide at the anode was found to prevent accumulation of oxygen in the melt. For a quantitative discussion of the limits of deoxidation achievable by this technique, a thermodynamic investigation of the lanthanide-oxygen (Ln-O ; Ln = La, Pr, Nd) solid solutions was conducted. The lanthanide metal, yttrium and titanium samples were immersed in calcium-saturated CaCl2 melt, containing a small quantity of dissolved CaO, at 1,093 K. The oxygen potential of the melt and the Ln-O solid solutions were obtained from the oxygen content of yttrium samples at equilibrium, and the known thermodynamic properties of yttrium-oxygen solid solution. The results were confirmed by using Y/Y2O3 equilibrium to control the oxygen potential of the molten salt reservoir. The oxygen affinity of the metals was found to decrease in the order : Y > Ti > Nd > Pr > La. The deoxidation results are consistent with the thermodynamic properties of the RE-O solid solutions.

Discovering injective episodes with general partial orders

Frequent episode discovery is a popular framework for temporal pattern discovery in event streams. An episode is a partially ordered set of nodes with each node associated with an event type. Currently algorithms exist for episode discovery only when the associated partial order is total order (serial episode) or trivial (parallel episode). In this paper, we propose efficient algorithms for discovering frequent episodes with unrestricted partial orders when the associated event-types are unique. These algorithms can be easily specialized to discover only serial or parallel episodes. Also, the algorithms are flexible enough to be specialized for mining in the space of certain interesting subclasses of partial orders. We point out that frequency alone is not a sufficient measure of interestingness in the context of partial order mining. We propose a new interestingness measure for episodes with unrestricted partial orders which, when used along with frequency, results in an efficient scheme of data mining. Simulations are presented to demonstrate the effectiveness of our algorithms.