Sharded Router: A novel on-chip router architecture employing bandwidth sharding and stealing

Packet-based networks-on-chip (NoC) are considered among the most viable candidates for the on-chip interconnection network of many-core chips. Unrelenting increases in the number of processing elements on a single chip die necessitate a scalable and efficient communication fabric. The resulting enlargement of the on-chip network size has been accompanied by an equivalent widening of the physical inter-router channels. However, the growing link bandwidth is not fully utilized, because the packet size is not always a multiple of the channel width. While slicing of the physical channel enhances link utilization, it incurs additional delay, because the number of flit per packet also increases. This paper proposes a novel router micro-architecture that employs fine-grained bandwidth “sharding” (i.e., partitioning) and stealing in order to mitigate the elevation in the zero-load latency caused by slicing. Consequently, the zero-load latency of the Sharded Router becomes identical with that of a conventional router, whereas its throughput is markedly improved by fully utilizing all available bandwidth. Detailed experiments using a full-system simulation framework indicate that the proposed router reduces the average network latency by up to 19% and the execution time of real multi-threaded workloads by up to 43%. Finally, hardware synthesis analysis verifies the modest area overhead of the Sharded Router over a conventional design.     

A constructive bin-oriented heuristic for the two-dimensional bin packing problem with guillotine cuts

A new heuristic algorithm for solving the two-dimensional bin-packing problem with guillotine cuts (2DBP|?|G)$(2\mathrm{DBP}|?|\mathrm{G})$ is presented. The heuristic constructs a solution by packing a bin at a time. Central to the adopted solution scheme is the principle of average-area sufficiency proposed by the authors for guiding selection of items to fill a bin. The algorithm is tested on a set of standard benchmark problem instances and compared with existing heuristics producing the best-known results. The results presented attest to the efficacy of the proposed scheme.     

Sorptive removal of trivalent and hexavalent chromium from binary aqueous solutions by composite alginate-goethite beads

In this study, the removal of hexavalent and trivalent chromium ions from binary aqueous solutions by composite alginate-goethite beads was investigated in a batch mode. Equilibrium sorption experiments were carried out at different temperatures and pH values. The data were correlated with Langmuir and Freundlich equations. The thermodynamic parameters calculated were: change in free energy, in enthalpy, in entropy and the heat of adsorption. The influence of mixing rate, sorbent concentration and sorbent particle size was studied at kinetic runs. The effective diffusion coefficients were evaluated by employing the homogeneous diffusion model and the shrinking core model for hexavalent and trivalent chromium, respectively. Desorption experiments were conducted by employing various eluants showed that the loaded material could be regenerated satisfactorily.     

Circuit design using a recent minimax approach

Over the past decade a number of researchers in mathematical programming and engineering design have become interested in both the theoretical and practical applications to minimax optimization. Recently Charalambous proposed a method of accelerating the original Bandler-Charalambous least pth algorithm for minimax optimization. The purpose of this paper is to demonstrate the usefulness of the new approach to the design of networks.     

A Data‐Driven Framework for Visual Crowd Analysis

We present a novel approach for analyzing the quality of multi‐agent crowd simulation algorithms. Our approach is data‐driven, taking as input a set of user‐defined metrics and reference training data, either synthetic or from video footage of real crowds. Given a simulation, we formulate the crowd analysis problem as an anomaly detection problem and exploit state‐of‐the‐art outlier detection algorithms to address it. To that end, we introduce a new framework for the visual analysis of crowd simulations. Our framework allows us to capture potentially erroneous behaviors on a per‐agent basis either by automatically detecting outliers based on individual evaluation metrics or by accounting for multiple evaluation criteria in a principled fashion using Principle Component Analysis and the notion of Pareto Optimality. We discuss optimizations necessary to allow real‐time performance on large datasets and demonstrate the applicability of our framework through the analysis of simulations created by several widely‐used methods, including a simulation from a commercial game.     

Exact filters for Newton–Raphson parameter estimation algorithms for continuous-time partially observed stochastic systems

This paper presents explicit finite-dimensional filters for implementing Newton–Raphson (NR) parameter estimation algorithms. The models which exhibit nonlinear parameter dependence are stochastic, continuous-time and partially observed. The implementation of the NR algorithm requires evaluation of the log-likelihood gradient and the Fisher information matrix. Fisher information matrices are important in bounding the estimation error from below, via the Cramer–Rao bound. The derivations are based on relations between incomplete and complete data, likelihood, gradient and Hessian likelihood functions, which are derived using Girsanov's measure transformations.     

Application of Monte Carlo Simulation Technique to Design Flood Estimation: A Case Study for North Johnstone River in Queensland, Australia

The traditional rainfall-runoff modelling based on the Design Event Approach has some serious limitations as this ignores the probabilistic nature of the key flood producing variables in the modelling except for rainfall depth. A more holistic approach of design flood estimation such as the Joint Probability Approach/Monte Carlo simulation can overcome some of the limitations associated with the Design Event Approach. The Monte Carlo simulation technique is based on the principle that flood producing variables are random variables instead of fixed values. This allows accounting for the inherent variability in the flood producing variables in the rainfall-runoff modelling. This paper applies the Monte Carlo simulation technique and hydrologic model URBS to a large catchment with multiple pluviograph and stream gauging stations. It has been found that it is quite feasible to apply the Monte Carlo simulation technique to large catchments. The Monte Carlo simulation technique has much greater flexibility than the Design Event approach and can provide more realistic design flood estimates with multiple scenarios, which is likely to replace the Design Event Approach. The method developed here can be applied to other catchments in Australia and other countries.     

Discrete-Time Risk-Sensitive Filters with Non-Gaussian Initial Conditions and Their Ergodic Properties

In this paper, we study asymptotic stability properties of risk-sensitive filters with respect to their initial conditions. In particular, we consider a linear time-invariant systems with initial conditions that are not necessarily Gaussian. We show that in the case of Gaussian initial conditions, the optimal risk-sensitive filter asymptotically converges to a suboptimal filter initialized with an incorrect covariance matrix for the initial state vector in the mean square sense provided the incorrect initializing value for the covariance matrix results in a risk-sensitive filter that is asymptotically stable, that is, results in a solution for a Riccati equation that is asymptotically stabilizing. For non-Gaussian initial conditions, we derive the expression for the risk-sensitive filter in terms of a finite number of parameters. Under a boundedness assumption satisfied by the fourth order absolute moment of the initial state variable and a slow growth condition satisfied by a certain Radon-Nikodym derivative, we show that a suboptimal risk-sensitive filter initialized with Gaussian initial conditions asymptotically approaches the optimal risk-sensitive filter for non-Gaussian initial conditions in the mean square sense. Some examples are also given to substantiate our claims.     

Symmetry properties for a generalised thin film equation

Symmetry properties are presented for a fourth-order parabolic equation written in conservation form. It was introduced in the literature as a generalisation of the fourth-order thin film equation. We derive equivalence transformations, Lie symmetries, potential symmetries, non-classical symmetries and potential non-classical symmetries. A chain of such equations is introduced. We conclude by presenting similar results for the third-order equation of this chain.     

In-situ observation of oxygen mobility and abnormal lattice expansion in ceria during flash sintering

Flash sintering has been shown to be an effective method of sintering for many types of ceramics. However, the characteristics of flash sintering for each type of ceramic varies. When ionically conducting ceramics are sintered under a DC electric field, a strong dependence of densification with respect to position is observed. Microstructural analysis of the effect of electric field on oxygen ion conductors shows non-stoichiometry (oxygen deficiency) at the cathode which continues to build up over time under flash. In oxygen ion conductors, dominant charge carriers during flash are oxygen ions and the final density of the specimen is related to the availability of oxygen. This effect is no longer evident when using an AC power supply. Thus, use of AC instead of DC electric field is preferable for flash sintering of ionically conducting ceramics.