Performance Modeling based on Multidimensional Surface Learning for Performance Predictions of Parallel Applications in Non-Dedicated Environments

Modeling the performance behavior of parallel applications to predict the execution times of the applications for larger problem sizes and number of processors has been an active area of research for several years. The existing curve fitting strategies for performance modeling utilize data from experiments that are conducted under uniform loading conditions. Hence the accuracy of these models degrade when the load conditions on the machines and network change. In this paper, we analyze a curve fitting model that attempts to predict execution times for any load conditions that may exist on the systems during application execution. Based on the experiments conducted with the model for a parallel eigenvalue problem, we propose a multi-dimensional curve-fitting model based on rational polynomials for performance predictions of parallel applications in non-dedicated environments. We used the rational polynomial based model to predict execution times for 2 other parallel applications on systems with large load dynamics. In all the cases, the model gave good predictions of execution times with average percentage prediction errors of less than 20%

Performance analysis for geometrical attack on digital image watermarking

We present a technique for irreversible watermarking approach robust to affine transform attacks in camera, biomedical and satellite images stored in the form of monochrome bitmap images. The watermarking approach is based on image normalisation in which both watermark embedding and extraction are carried out with respect to an image normalised to meet a set of predefined moment criteria. The normalisation procedure is invariant to affine transform attacks. The result of watermarking scheme is suitable for public watermarking applications, where the original image is not available for watermark extraction. Here, direct-sequence code division multiple access approach is used to embed multibit text information in DCT and DWT transform domains. The proposed watermarking schemes are robust against various types of attacks such as Gaussian noise, shearing, scaling, rotation, flipping, affine transform, signal processing and JPEG compression. Performance analysis results are measured using image processing metrics.

Variable Granularity Access Tracking Scheme for Improving the Performance of Software Transactional Memory

Software transactional memory (STM) has been proposed as a promising programming paradigm for shared memory multi-threaded programs as an alternative to conventional lock based synchronization primitives. Typical STM implementations employ a conflict detection scheme, which works with uniform access granularity, tracking shared data accesses either at word/cache line or at object level. It is well known that a single fixed access tracking granularity cannot meet the conflicting goals of reducing false conflicts without impacting concurrency adversely. A fine grained granularity while improving concurrency can have an adverse impact on performance due to lock aliasing, lock validation overheads, and additional cache pressure. On the other hand, a coarse grained granularity can impact performance due to reduced concurrency. Thus, in general, a fixed or uniform granularity access tracking (UGAT) scheme is application-unaware and rarely matches the access patterns of individual application or parts of an application, leading to sub-optimal performance for different parts of the application(s). In order to mitigate the disadvantages associated with UGAT scheme, we propose a Variable Granularity Access Tracking (VGAT) scheme in this paper. We propose a compiler based approach wherein the compiler uses inter-procedural whole program static analysis to select the access tracking granularity for different shared data structures of the application based on the application's data access pattern. We describe our prototype VGAT scheme, using TL2 as our STM implementation. Our experimental results reveal that VGAT-STM scheme can improve the application performance of STAMP benchmarks from 1.87% to up to 21.2%.

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.

Performance evaluation of neural network algorithms for multisensor data fusion in an airborne track while scan radar

This paper deals with the solution to the problem of multisensor data fusion for a single target scenario as detected by an airborne track-while-scan radar. The details of a neural network implementation, various training algorithms based on standard backpropagation, and the results of training and testing the neural network are presented. The promising capabilities of RPROP algorithm for multisensor data fusion for various parameters are shown in comparison to other adaptive techniques

Performance of inherently compensated flat pad aerostatic bearings subject to dynamic perturbation forces

The importance of air bearing design is growing in engineering. As the trend to precision and ultra precision manufacture gains pace and the drive to higher quality and more reliable products continues, the advantages which can be gained from applying aerostatic bearings to machine tools, instrumentation and test rigs is becoming more apparent. The inlet restrictor design is significant for air bearings because it affects the static and dynamic performance of the air bearing. For instance pocketed orifice bearings give higher load capacity as compared to inherently compensated orifice type bearings, however inherently compensated orifices, also known as laminar flow restrictors are known to give highly stable air bearing systems (less prone to pneumatic hammer) as compared to pocketed orifice air bearing systems. However, they are not commonly used because of the difficulties encountered in manufacturing and assembly of the orifice designs. This paper aims to analyse the static and dynamic characteristics of inherently compensated orifice based flat pad air bearing system. Based on Reynolds equation and mass conservation equation for incompressible flow, the steady state characteristics are studied while the dynamic state characteristics are performed in a similar manner however, using the above equations for compressible flow. Steady state experiments were also performed for a single orifice air bearing and the results are compared to that obtained from theoretical studies. A technique to ease the assembly of orifices with the air bearing plate has also been discussed so as to make the manufacturing of the inherently compensated bearings more commercially viable. (c) 2012 Elsevier Inc. All rights reserved.

Degradation studies of organic acids in commercially packed fruit juices: A reverse phase high performance liquid chromatographic approach

Organic acids are important constituents of fruit juices. They render tartness, flavour and specific taste to fruit juices. Shelf life and stability of fruit juices are important factors, which determine their nutritional quality and freshness. In this view, the effect of storage on the concentration of organic acids in commercially packed fruit juices is studied by reverse phase high performance liquid chromatography (RP-HPLC). Ten packed fruit juices from two different brands are stored at 30 C for 24, 48 and 72 hours. A reverse phase high performance liquid chromatographic method is used to determine the concentration of oxalic, tartaric, malic, ascorbic and citric acid in the fruit juices during storage. The chromatographic analysis of organic acids is carried out using mobile phase 0.5% (w/v) ammonium dihydrogen orthophosphate buffer (pH 2.8) on C18 column with UV-Vis detector. The results show that the concentration of organic acids generally decreases in juices under study with the increase in storage time. All the fruit juices belonging to tropicana brand underwent less organic acid degradation in comparison to juices of real brand. Orange fruit juice is found to be least stable among the juices under study, after the span of 72 hours. Amongst all the organic acids under investigation minimum stability is shown by ascorbic acid followed by malic and citric acid.

Performance of telecommunication modules to 0.5µS-100kHz ring wave surges

This paper presents an experimental investigations performed on various electronic components used in telecommunication networks and those used in avionics for the ring wave surge voltages. IEEE Std C 62.41.1-2002 specifies a stringent requirement of waveforms to be applied for the evaluation of telecom components. To meet the necessary requirements in the absence of commercial equipment for generating the required waveforms, special efforts were made to fabricate a ring wave surge generator as per prescribed standards. The developed surge generator is capable of delivering an output of 0.5 mu s-100kHz which meets the requirements of telecom standards prescribed for evaluation of various modules used in low voltage ac power circuits used in communication networks. The results of the experimental investigations obtained on various modules used in communication networks are presented.

Correlations of vaporization performance of conventional and biofuel sprays in a crossflow heated chamber

Pre-vaporization and pre-mixing are the two main features of LPP type of combustor that operate on liquid fuels. The pre-vaporization length scale is one of its most important design parameters. In this study, the goal is to put forward a simulation based correlation for fuel vaporization performance as a function of dimensionless parameters for crossflow type of injections. Two types of fuels are studied here: jet-A and one of its potential biofuel substitutes, RME. Different sets of spray simulations are considered for crossflow type of injections. Correlations are provided for both jet-A and RME's vaporization performance as a function of non-dimensional inlet air temperature, fuel/air momentum flux ratio and normalized spray traverse distance. (C) 2012 Elsevier Ltd. All rights reserved.

Performance of a class of multi-robot deploy and search strategies based on centroidal voronoi configurations

This article considers a class of deploy and search strategies for multi-robot systems and evaluates their performance. The application framework used is deployment of a system of autonomous mobile robots equipped with required sensors in a search space to gather information. The lack of information about the search space is modelled as an uncertainty density distribution. The agents are deployed to maximise single-step search effectiveness. The centroidal Voronoi configuration, which achieves a locally optimal deployment, forms the basis for sequential deploy and search (SDS) and combined deploy and search (CDS) strategies. Completeness results are provided for both search strategies. The deployment strategy is analysed in the presence of constraints on robot speed and limit on sensor range for the convergence of trajectories with corresponding control laws responsible for the motion of robots. SDS and CDS strategies are compared with standard greedy and random search strategies on the basis of time taken to achieve reduction in the uncertainty density below a desired level. The simulation experiments reveal several important issues related to the dependence of the relative performances of the search strategies on parameters such as the number of robots, speed of robots and their sensor range limits.

Extended histories: improving regularity and performance in correlation prefetchers

Data Prefetchers identify and make use of any regularity present in the history/training stream to predict future references and prefetch them into the cache. The training information used is typically the primary misses seen at a particular cache level, which is a filtered version of the accesses seen by the cache. In this work we demonstrate that extending the training information to include secondary misses and hits along with primary misses helps improve the performance of prefetchers. In addition to empirical evaluation, we use the information theoretic metric entropy, to quantify the regularity present in extended histories. Entropy measurements indicate that extended histories are more regular than the default primary miss only training stream. Entropy measurements also help corroborate our empirical findings. With extended histories, further benefits can be achieved by triggering prefetches during secondary misses also. In this paper we explore the design space of extended prefetch histories and alternative prefetch trigger points for delta correlation prefetchers. We observe that different prefetch schemes benefit to a different extent with extended histories and alternative trigger points. Also the best performing design point varies on a per-benchmark basis. To meet these requirements, we propose a simple adaptive scheme that identifies the best performing design point for a benchmark-prefetcher combination at runtime. In SPEC2000 benchmarks, using all the L2 accesses as history for prefetcher improves the performance in terms of both IPC and misses reduced over techniques that use only primary misses as history. The adaptive scheme improves the performance of CZone prefetcher over Baseline by 4.6% on an average. These performance gains are accompanied by a moderate reduction in the memory traffic requirements.