bluuebunny/crossref_metadata_2025 huggingface dataset:
Mobile P2P Web Services Using SIP
Authors: Gehlen Guido , Aijaz Fahad , Zhu Yi , Walke Bernhard
Published: January 2015

Telecommunication networks and the Internet are growing together. Peer‐to‐Peer (P2P) services which are originally offered by network providers, like telephony and messaging, are provided through VoIP and Instant Messaging (IM) by Internet service providers, too. The IP Multimedia Subsystem (IMS) is the answer of the telecommunication industry to this trend and aims at providing Internet P2P and multimedia services controlled by the network operators. The IMS provides mobility and session management as well as message routing, security, and billing.
Investigating Solution Convergence in a Global Ocean Model Using a 2048‐Processor Cluster of Distributed Shared Memory Machines
Authors: Hill Chris , Menemenlis Dimitris , Ciotti Bob , Henze Chris
Published: January 2015

Up to 1920 processors of a cluster of distributed shared memory machines at the NASA Ames Research Center are being used to simulate ocean circulation globally at horizontal resolutions of 1/4, 1/8, and 1/16‐degree with the Massachusetts Institute of Technology General Circulation Model, a finite volume code that can scale to large numbers of processors. The study aims to understand physical processes responsible for skill improvements as resolution is increased and to gain insight into what resolution is sufficient for particular purposes. This paper focuses on the computational aspects of reaching the technical objective of efficiently performing these global eddy‐resolving ocean simulations. At 1/16‐degree resolution the model grid contains 1.2 billion cells. At this resolution it is possible to simulate approximately one month of ocean dynamics in about 17 hours of wallclock time with a model timestep of two minutes on a cluster of four 512‐way NUMA Altix systems. The Altix systems′ large main memory and I/O subsystems allow computation and disk storage of rich sets of diagnostics during each integration, supporting the scientific objective to develop a better understanding of global ocean circulation model solution convergence as model resolution is increased.
Mobile Information Systems for the Private Everyday Life
Authors: Bohl Oliver , Manouchehri Shakib , Winand Udo
Published: January 2015

Despite the high penetration of the private sector in mobile devices, only few applications and services based on mobile technologies are used, and those are rather trivial. This article suggests an approach for the identification of alternatives for the support of processes of everyday life by establishing services based on mobile applications, mobile devices and infrastructures for mobile dispositions. Therefore, a framework for the identification, as well as criteria for the analysis of potential fields of application is discussed. Exemplary benchmarks for selected basic processes in private everyday life visualise the suggested framework, which can be adapted for individual methodical analyses.
Conditional Workflow Management: A Survey and Analysis
Authors: Bahsi Emir M. , Ceyhan Emrah , Kosar Tevfik
Published: January 2015

Workflows form the essential part of the process execution both in a single machine and in distributed environments. Although providing conditional structures is not mandatory for a workflow management system, support for conditional workflows is very important in terms of error handling, flexibility and robustness. Several of the existing workflow management systems already support conditional structures via use of different constructs. In this paper, we study the most widely used workflow management systems and their support for conditional structures such as if, switch, and while. We compare implementation of common conditional structures using each of these workflow management systems via case studies, and discuss capabilities of each system.
Mixed Task and Data Parallel Executions in General Linear Methods
Authors: Rauber Thomas , Rünger Gudula
Published: January 2015

On many parallel target platforms it can be advantageous to implement parallel applications as a collection of multiprocessor tasks that are concurrently executed and are internally implemented with fine‐grain SPMD parallelism. A class of applications which can benefit from this programming style are methods for solving systems of ordinary differential equations. Many recent solvers have been designed with an additional potential of method parallelism, but the actual effectiveness of mixed task and data parallelism depends on the specific communication and computation requirements imposed by the equation to be solved. In this paper we study mixed task and data parallel implementations for general linear methods realized using a library for multiprocessor task programming. Experiments on a number of different platforms show good efficiency results.
Optimizing Workflow Data Footprint
Authors: Singh Gurmeet , Vahi Karan , Ramakrishnan Arun , Mehta Gaurang , Deelman Ewa , Zhao Henan , Sakellariou Rizos , Blackburn Kent , Brown Duncan , Fairhurst Stephen , Meyers David , Berriman G. Bruce , Good John , Katz Daniel S.
Published: January 2015

In this paper we examine the issue of optimizing disk usage and scheduling large‐scale scientific workflows onto distributed resources where the workflows are data‐intensive, requiring large amounts of data storage, and the resources have limited storage resources. Our approach is two‐fold: we minimize the amount of space a workflow requires during execution by removing data files at runtime when they are no longer needed and we demonstrate that workflows may have to be restructured to reduce the overall data footprint of the workflow. We show the results of our data management and workflow restructuring solutions using a Laser Interferometer Gravitational‐Wave Observatory (LIGO) application and an astronomy application, Montage, running on a large‐scale production grid‐the Open Science Grid. We show that although reducing the data footprint of Montage by 48% can be achieved with dynamic data cleanup techniques, LIGO Scientific Collaboration workflows require additional restructuring to achieve a 56% reduction in data space usage. We also examine the cost of the workflow restructuring in terms of the application′s runtime.
A Simulated Annealing Based Location Area Optimization in Next Generation Mobile Networks
Authors: Simon Vilmos , Imre Sándor
Published: January 2015

Mobile networks have faced rapid increase in the number of mobile users and the solution for supporting the growing population is to reduce the cell sizes and to increase the bandwidth reuse. This will cause the number of location management operations and call deliveries to increase significantly, and result in high signaling overhead. We focus on minimizing this overhead, by efficient Location Area Planning (LAP). In this paper we seek to determine the location areas to achieve the minimization of the registration cost, constrained by the paging cost. For that we propose a simulated annealing algorithm, which is applied on a basic Location Area partition of cells formed by a greedy algorithm. We used our realistic mobile environment simulator to generate input (cell changing and incoming call statistics) for our algorithm, and by comparing the values of the registration cost function we recognized that significant reduction was achieved in the amount of the signaling traffic.
Causal Analysis for Performance Modeling of Computer Programs
Authors: Lemeire Jan , Dirkx Erik , Verbist Frederik
Published: January 2015

Causal modeling and the accompanying learning algorithms provide useful extensions for in‐depth statistical investigation and automation of performance modeling. We enlarged the scope of existing causal structure learning algorithms by using the form‐free information‐theoretic concept of mutual information and by introducing the complexity criterion for selecting direct relations among equivalent relations. The underlying probability distribution of experimental data is estimated by kernel density estimation. We then reported on the benefits of a dependency analysis and the decompositional capacities of causal models. Useful qualitative models, providing insight into the role of every performance factor, were inferred from experimental data. This paper reports on the results for a LU decomposition algorithm and on the study of the parameter sensitivity of the Kakadu implementation of the JPEG‐2000 standard. Next, the analysis was used to search for generic performance characteristics of the applications.
A Context‐Aware Tour Guide: User Implications
Authors: Gulliver S. R. , Ghinea G. , Patel M. , Serif T.
Published: January 2015

Although examples of tourist guides abound, the role of context aware feedback in such systems is an issue that has been insufficiently explored. Given the potential importance of such feedback, this paper investigates, from a usability perspective, two tour guide systems developed for Brunel University: one with context‐aware user feedback and the other without. An empirical study was undertaken in which each of the applications was assessed through the prism of three usability measurements: efficiency, effectiveness, and satisfaction. Incorporating the participant feedback gathered as a result, the paper compares the use of the two applications in order to determine the impact of real‐time feedback with respect to user location. Efficiency, understood as the time taken by a participant to successfully complete a task, was found to be significantly affected by the use of context‐aware functionality. Effectiveness, understood as the amount of information a participant assimilated from the application, was shown not to be impacted by the provision of context‐aware feedback, even though average experiment duration was found to be significantly shorter in this case. Lastly, participants′ subjective satisfaction when using context‐aware functionality was shown to be significantly higher than when using the non‐context aware application.
Large-Scale Phylogenetic Analysis on Current HPC Architectures
Authors: Ott Michael , Zola Jaroslaw , Aluru Srinivas , Johnson Andrew D. , Janies Daniel , Stamatakis Alexandros
Published: January 2015

Phylogenetic inference is considered a grand challenge in Bioinformatics due to its immense computational requirements. The increasing popularity and availability of large multi-gene alignments as well as comprehensive datasets of single nucleotide polymorphisms (SNPs) in current biological studies, coupled with rapid accumulation of sequence data in general, pose new challenges for high performance computing. By example of RAxML, which is currently among the fastest and most accurate programs for phylogenetic inference under the Maximum Likelihood (ML) criterion, we demonstrate how the phylogenetic ML function can be efficiently scaled to current supercomputer architectures like the IBM BlueGene/L (BG/L) and SGI Altix. This is achieved by simultaneous exploitation of coarse- and fine-grained parallelism which is inherent to every ML-based biological analysis. Performance is assessed using datasets consisting of 270 sequences and 566,470 base pairs (haplotype map dataset), and 2,182 sequences and 51,089 base pairs, respectively. To the best of our knowledge, these are the largest datasets analyzed under ML to date. Experimental results indicate that the fine-grained parallelization scales well up to 1,024 processors. Moreover, a larger number of processors can be efficiently exploited by a combination of coarse- and fine-grained parallelism. We also demonstrate that our parallelization scales equally well on an AMD Opteron cluster with a less favorable network latency to processor speed ratio. Finally, we underline the practical relevance of our approach by including a biological discussion of the results from the haplotype map dataset analysis, which revealed novel biological insights via phylogenetic inference.
Employ a Mobile Agent for Making a Payment
Authors: Wang Yan , Wong Duncan S. , Wang Huaxiong
Published: January 2015

The mobile agent paradigm offers flexibility and autonomy to e‐commerce applications. But it is challenging to employ a mobile agent to make a payment due to the security consideration. In this paper, we propose a new agent‐assisted secure payment protocol, which is based on SET payment protocol and aims at enabling the dispatched consumer‐agent to autonomously sign contracts and make the payment on behalf of the cardholder after having found the best merchant, without the possibility of disclosing any secret to any participant. This is realized by adopting the Signature‐Share scheme, and employing a Trusted Third Party (TTP). In the proposed protocol, the principle that each participant knows what is strictly necessary for his/her role is followed as in SET. In addition, mechanisms have been devised for preventing and detecting double payment, overspending and overpayment attacks. Finally the security properties of the proposed protocol are studied analytically. In comparison with other existing models, the proposed protocol is more efficient and can detect more attacks.
QoS Management and Control for an All‐IP WiMAX Network Architecture: Design, Implementation and Evaluation
Authors: Bohnert Thomas Michael , Castrucci Marco , Ciulli Nicola , Landi Giada , Marchetti Ilaria , Nardini Cristina , Sousa Bruno , Neves Pedro , Simoes Paulo
Published: January 2015

The IEEE 802.16 standard provides a specification for a fixed and mobile broadband wireless access system, offering high data rate transmission of multimedia services with different Quality‐of‐Service (QoS) requirements through the air interface. The WiMAX Forum, going beyond the air interface, defined an end‐to‐end WiMAX network architecture, based on an all‐IP platform in order to complete the standards required for a commercial rollout of WiMAX as broadband wireless access solution. As the WiMAX network architecture is only a functional specification, this paper focuses on an innovative solution for an end‐to‐end WiMAX network architecture offering in compliance with the WiMAX Forum specification. To our best knowledge, this is the first WiMAX architecture built by a research consortium globally and was performed within the framework of the European IST project WEIRD (WiMAX Extension to Isolated Research Data networks). One of the principal features of our architecture is support for end‐to‐end QoS achieved by the integration of resource control in the WiMAX wireless link and the resource management in the wired domains in the network core. In this paper we present the architectural design of these QoS features in the overall WiMAX all‐IP framework and their functional as well as performance evaluation. The presented results can safely be considered as unique and timely for any WiMAX system integrator.
Managing Scientific Software Complexity with Bocca and CCA
Authors: Allan Benjamin A. , Norris Boyana , Elwasif Wael R. , Armstrong Robert C.
Published: January 2015

In high-performance scientific software development, the emphasis is often on short time to first solution. Even when the development of new components mostly reuses existing components or libraries and only small amounts of new code must be created, dealing with the component glue code and software build processes to obtain complete applications is still tedious and error-prone. Component-based software meant to reduce complexity at the application level increases complexity to the extent that the user must learn and remember the interfaces and conventions of the component model itself. To address these needs, we introduce Bocca, the first tool to enable application developers to perform rapid component prototyping while maintaining robust software-engineering practices suitable to HPC environments. Bocca provides project management and a comprehensive build environment for creating and managing applications composed of Common Component Architecture components. Of critical importance for high-performance computing (HPC) applications, Bocca is designed to operate in a language-agnostic way, simultaneously handling components written in any of the languages commonly used in scientific applications: C, C++, Fortran, Python and Java. Bocca automates the tasks related to the component glue code, freeing the user to focus on the scientific aspects of the application. Bocca embraces the philosophy pioneered by Ruby on Rails for web applications: start with something that works, and evolve it to the user's purpose.
A Component Approach to Collaborative Scientific Software Development: Tools and Techniques Utilized by the Quantum Chemistry Science Application Partnership
Authors: Kenny Joseph P. , Janssen Curtis L. , Gordon Mark S. , Sosonkina Masha , Windus Theresa L.
Published: January 2015

Cutting-edge scientific computing software is complex, increasingly involving the coupling of multiple packages to combine advanced algorithms or simulations at multiple physical scales. Component-based software engineering (CBSE) has been advanced as a technique for managing this complexity, and complex component applications have been created in the quantum chemistry domain, as well as several other simulation areas, using the component model advocated by the Common Component Architecture (CCA) Forum. While programming models do indeed enable sound software engineering practices, the selection of programming model is just one building block in a comprehensive approach to large-scale collaborative development which must also address interface and data standardization, and language and package interoperability. We provide an overview of the development approach utilized within the Quantum Chemistry Science Application Partnership, identifying design challenges, describing the techniques which we have adopted to address these challenges and highlighting the advantages which the CCA approach offers for collaborative development.
Components for Atomistic-to-Continuum Multiscale Modeling of Flow in Micro- and Nanofluidic Systems
Authors: Adalsteinsson Helgi , Debusschere Bert J. , Long Kevin R. , Najm Habib N.
Published: January 2015

Micro- and nanofluidics pose a series of significant challenges for science-based modeling. Key among those are the wide separation of length- and timescales between interface phenomena and bulk flow and the spatially heterogeneous solution properties near solid-liquid interfaces. It is not uncommon for characteristic scales in these systems to span nine orders of magnitude from the atomic motions in particle dynamics up to evolution of mass transport at the macroscale level, making explicit particle models intractable for all but the simplest systems. Recently, atomistic-to-continuum (A2C) multiscale simulations have gained a lot of interest as an approach to rigorously handle particle-level dynamics while also tracking evolution of large-scale macroscale behavior. While these methods are clearly not applicable to all classes of simulations, they are finding traction in systems in which tight-binding, and physically important, dynamics at system interfaces have complex effects on the slower-evolving large-scale evolution of the surrounding medium. These conditions allow decomposition of the simulation into discrete domains, either spatially or temporally. In this paper, we describe how features of domain decomposed simulation systems can be harnessed to yield flexible and efficient software for multiscale simulations of electric field-driven micro- and nanofluidics.
An Efficient Format for Nearly Constant-Time Access to Arbitrary Time Intervals in Large Trace Files
Authors: Chan Anthony , Gropp William , Lusk Ewing
Published: January 2015

A powerful method to aid in understanding the performance of parallel applications uses log or trace files containing time-stamped events and states (pairs of events). These trace files can be very large, often hundreds or even thousands of megabytes. Because of the cost of accessing and displaying such files, other methods are often used that reduce the size of the tracefiles at the cost of sacrificing detail or other information. This paper describes a hierarchical trace file format that provides for display of an arbitrary time window in a time independent of the total size of the file and roughly proportional to the number of events within the time window. This format eliminates the need to sacrifice data to achieve a smaller trace file size (since storage is inexpensive, it is necessary only to make efficient use of bandwidth to that storage). The format can be used to organize a trace file or to create a separate file ofannotationsthat may be used with conventional trace files. We present an analysis of the time to access all of the events relevant to an interval of time and we describe experiments demonstrating the performance of this file format.
A Performance Tuning Methodology with Compiler Support
Authors: Hernandez Oscar , Chapman Barbara , Jin Haoqiang
Published: January 2015

We have developed an environment, based upon robust, existing, open source software, for tuning applications written using MPI, OpenMP or both. The goal of this effort, which integrates the OpenUH compiler and several popular performance tools, is to increase user productivity by providing an automated, scalable performance measurement and optimization system. In this paper we describe our environment, show how these complementary tools can work together, and illustrate the synergies possible by exploiting their individual strengths and combined interactions. We also present a methodology for performance tuning that is enabled by this environment. One of the benefits of using compiler technology in this context is that it can direct the performance measurements to capture events at different levels of granularity and help assess their importance, which we have shown to significantly reduce the measurement overheads. The compiler can also help when attempting to understand the performance results: it can supply information on how a code was translated and whether optimizations were applied. Our methodology combines two performance views of the application to find bottlenecks. The first is a high level view that focuses on OpenMP/MPI performance problems such as synchronization cost and load imbalances; the second is a low level view that focuses on hardware counter analysis with derived metrics that assess the efficiency of the code. Our experiments have shown that our approach can significantly reduce overheads for both profiling and tracing to acceptable levels and limit the number of times the application needs to be run with selected hardware counters. In this paper, we demonstrate the workings of this methodology by illustrating its use with selected NAS Parallel Benchmarks and a cloud resolving code.
Semi-Supervised Learning for Classification of Protein Sequence Data
Authors: King Brian R. , Guda Chittibabu
Published: January 2015

Protein sequence data continue to become available at an exponential rate. Annotation of functional and structural attributes of these data lags far behind, with only a small fraction of the data understood and labeled by experimental methods. Classification methods that are based on semi-supervised learning can increase the overall accuracy of classifying partly labeled data in many domains, but very few methods exist that have shown their effect on protein sequence classification. We show how proven methods from text classification can be applied to protein sequence data, as we consider both existing and novel extensions to the basic methods, and demonstrate restrictions and differences that must be considered. We demonstrate comparative results against the transductive support vector machine, and show superior results on the most difficult classification problems. Our results show that large repositories of unlabeled protein sequence data can indeed be used to improve predictive performance, particularly in situations where there are fewer labeled protein sequences available, and/or the data are highly unbalanced in nature.
Monitoring of Grid Scientific Workflows
Authors: Balis Bartosz , Bubak Marian , Łabno Bartłomiej
Published: January 2015

Scientific workflows are a means of conducting in silico experiments in modern computing infrastructures for e-Science, often built on top of Grids. Monitoring of Grid scientific workflows is essential not only for performance analysis but also to collect provenance data and gather feedback useful in future decisions, e.g., related to optimization of resource usage. In this paper, basic problems related to monitoring of Grid scientific workflows are discussed. Being highly distributed, loosely coupled in space and time, heterogeneous, and heavily using legacy codes, workflows are exceptionally challenging from the monitoring point of view. We propose a Grid monitoring architecture for scientific workflows. Monitoring data correlation problem is described and an algorithm for on-line distributed collection of monitoring data is proposed. We demonstrate a prototype implementation of the proposed workflow monitoring architecture, the GEMINI monitoring system, and its use for monitoring of a real-life scientific workflow.
Tangible Interfaces for Interactive Multimedia Presentations
Authors: Kanev Kamen
Published: January 2015

This article is devoted to tangible interfaces for steering and control of interactive multimedia presentations. Various methods for digital encoding of physical objects are considered and their applicability in surface encoding for tangible interface components is discussed. Experiments with presentation controls, based on direct interaction with digitally encoded printed handouts are reported. An innovative approach for transferring presentation controls from printed handouts to surfaces of real physical objects is introduced. Consequently labels, digitally enhanced with CLUSPI codes are created and presentation control trials involving real products with digitally encoded surfaces are conducted. USB and wireless cameras are employed as CLUSPI readers for implementing surface based interactions and a portable communication device with an embedded camera is considered as a possible truly mobile solution.
Knowledge Support and Automation for Performance Analysis with PerfExplorer 2.0
Authors: Huck Kevin A. , Malony Allen D. , Shende Sameer , Morris Alan
Published: January 2015

The integration of scalable performance analysis in parallel development tools is difficult. The potential size of data sets and the need to compare results from multiple experiments presents a challenge to manage and process the information. Simply to characterize the performance of parallel applications running on potentially hundreds of thousands of processor cores requires new scalable analysis techniques. Furthermore, many exploratory analysis processes are repeatable and could be automated, but are now implemented as manual procedures. In this paper, we will discuss the current version of PerfExplorer, a performance analysis framework which provides dimension reduction, clustering and correlation analysis of individual trails of large dimensions, and can perform relative performance analysis between multiple application executions. PerfExplorer analysis processes can be captured in the form of Python scripts, automating what would otherwise be time-consuming tasks. We will give examples of large-scale analysis results, and discuss the future development of the framework, including the encoding and processing of expert performance rules, and the increasing use of performance metadata.
Exploiting Fine-Grain Thread Parallelism on Multicore Architectures
Authors: Hadjidoukas P.E. , Philos G.Ch. , Dimakopoulos V.V.
Published: January 2015

In this work we present a runtime threading system which provides an efficient substrate for fine-grain parallelism, suitable for deployment in multicore platforms. Its architecture encompasses a number of optimizations that make it particularly effective in managing a large number of threads and with low overheads. The runtime system has been integrated into an OpenMP implementation to allow for transparent usage under a high level programming paradigm. We evaluate our implementation on two multicore systems using synthetic microbenchmarks and a real-time face detection application.
Location-Dependent Query Processing Under Soft Real-Time Constraints
Authors: Mammeri Zoubir , Morvan Franck , Hameurlain Abdelkader , Marsit Nadhem
Published: January 2015

In recent years, mobile devices and applications achieved an increasing development. In database field, this development required methods to consider new query types like location-dependent queries (i.e. the query results depend on the query issuer location). Although several researches addressed problems related to location-dependent query processing, a few works considered timing requirements that may be associated with queries (i.e., the query results must be delivered to mobile clients on time). The main objective of this paper is to propose a solution for location-dependent query processing under soft real-time constraints. Hence, we propose methods to take into account client location-dependency and to maximize the percentage of queries respecting their deadlines. We validate our proposal by implementing a prototype based on Oracle DBMS. Performance evaluation results show that the proposed solution optimizes the percentage of queries meeting their deadlines and the communication cost.
3D Seismic Imaging through Reverse-Time Migration on Homogeneous and Heterogeneous Multi-Core Processors
Authors: Araya-Polo Mauricio , Rubio Félix , de la Cruz Raúl , Hanzich Mauricio , Cela José María , Scarpazza Daniele Paolo
Published: January 2015

Reverse-Time Migration (RTM) is a state-of-the-art technique in seismic acoustic imaging, because of the quality and integrity of the images it provides. Oil and gas companies trust RTM with crucial decisions on multi-million-dollar drilling investments. But RTM requires vastly more computational power than its predecessor techniques, and this has somewhat hindered its practical success. On the other hand, despite multi-core architectures promise to deliver unprecedented computational power, little attention has been devoted to mapping efficiently RTM to multi-cores. In this paper, we present a mapping of the RTM computational kernel to the IBM Cell/B.E. processor that reaches close-to-optimal performance. The kernel proves to be memory-bound and it achieves a 98% utilization of the peak memory bandwidth. Our Cell/B.E. implementation outperforms a traditional processor (PowerPC 970MP) in terms of performance (with an 15.0× speedup) and energy-efficiency (with a 10.0× increase in the GFlops/W delivered). Also, it is the fastest RTM implementation available to the best of our knowledge. These results increase the practical usability of RTM. Also, the RTM-Cell/B.E. combination proves to be a strong competitor in the seismic arena.
Virtual Social Networks Online and Mobile Systems
Authors: Safar Maytham , Sawwan Hussain , Taha Mahmoud , Al-Fadhli Talal
Published: January 2015

Location-based applications are one of the most anticipated new segments of the mobile industry. These new applications are enabled by GPS-equipped phones (e.g., emergency applications, buddy finders, games, location-based advertising, etc.). These services are designed to give consumers instant access to personalized, local content of their immediate location. Some applications couple LBS with notification services, automatically alerting users when they are close to a pre-selected destination. With the advances in the Internet and communications/mobile technology, it became vital to analyze the effect of such technologies on human communications. This work studies how humans can construct social networks as a method for group communications using the available technologies. We constructed and analyzed a friends network using different parameters. The parameters that were calculated to analyze the network are the distribution sequence, characteristic path length, clustering coefficient and centrality measures. In addition, we built a PDA application that implements the concept of LBS using two system modules. In the first module, we have developed an application for entertainment purpose; an application program which enables end users to send their birth year and get their horoscope in return. The second part of the project was, to build an application, which helps people to stay in touch with their friends and family members (Find Friend). It helps users to find which of their buddies are within the same area they are in.
CellSs: Scheduling Techniques to Better Exploit Memory Hierarchy
Authors: Bellens Pieter , Perez Josep M. , Cabarcas Felipe , Ramirez Alex , Badia Rosa M. , Labarta Jesus
Published: January 2015

Cell Superscalar's (CellSs) main goal is to provide a simple, flexible and easy programming approach for the Cell Broadband Engine (Cell/B.E.) that automatically exploits the inherent concurrency of the applications at a task level. The CellSs environment is based on a source-to-source compiler that translates annotated C or Fortran code and a runtime library tailored for the Cell/B.E. that takes care of the concurrent execution of the application. The first efforts for task scheduling in CellSs derived from very simple heuristics. This paper presents new scheduling techniques that have been developed for CellSs for the purpose of improving an application's performance. Additionally, the design of a new scheduling algorithm is detailed and the algorithm evaluated. The CellSs scheduler takes an extension of the memory hierarchy for Cell/B.E. into account, with a cache memory shared between the SPEs. All new scheduling practices have been evaluated showing better behavior of our system.
Implementation of Scientific Computing Applications on the Cell Broadband Engine
Authors: Shi Guochun , Kindratenko Volodymyr V. , Ufimtsev Ivan S. , Martinez Todd J. , Phillips James C. , Gottlieb Steven A.
Published: January 2015

The Cell Broadband Engine architecture is a revolutionary processor architecture well suited for many scientific codes. This paper reports on an effort to implement several traditional high-performance scientific computing applications on the Cell Broadband Engine processor, including molecular dynamics, quantum chromodynamics and quantum chemistry codes. The paper discusses data and code restructuring strategies necessary to adapt the applications to the intrinsic properties of the Cell processor and demonstrates performance improvements achieved on the Cell architecture. It concludes with the lessons learned and provides practical recommendations on optimization techniques that are believed to be most appropriate.
High Performance Protein Sequence Database Scanning on the Cell Broadband Engine
Authors: Wirawan Adrianto , Schmidt Bertil , Zhang Huiliang , Kwoh Chee Keong
Published: January 2015

The enormous growth of biological sequence databases has caused bioinformatics to be rapidly moving towards a data-intensive, computational science. As a result, the computational power needed by bioinformatics applications is growing rapidly as well. The recent emergence of low cost parallel multicore accelerator technologies has made it possible to reduce execution times of many bioinformatics applications. In this paper, we demonstrate how the Cell Broadband Engine can be used as a computational platform to accelerate two approaches for protein sequence database scanning: exhaustive and heuristic. We present efficient parallelization techniques for two representative algorithms: the dynamic programming based Smith–Waterman algorithm and the popular BLASTP heuristic. Their implementation on a Playstation®3 leads to significant runtime savings compared to corresponding sequential implementations.
Routing of Internal MANET Traffic over External Networks
Authors: Pham Vinh , Larsen Erlend , Kure Øivind , Engelstad Paal
Published: January 2015

Many have proposed to connect Mobile Ad Hoc Networks (MANETs) to a wired backbone Internet access network. This paper demonstrates that a wired backbone network can be utilized for more than just providing access to the global Internet. Traffic between mobile nodes in the ad hoc network may also be routed via this backbone network to achieve higher throughput, and to reduce the load in the ad hoc network. This is referred to as transit routing. This paper proposes a cost metric algorithm that facilitates transit routing for some of the traffic flows between nodes in the MANET. The algorithm aims at carrying out transit routing for a flow only when it leads to improvements of the performance. The proposal is implemented and tested in the ns-2 network simulator, and the simulation results are promising.
Range Assignment Problem on the Steiner Tree Based Topology in Ad Hoc Wireless Networks
Authors: Muhammad Rashid Bin
Published: January 2015

This paper describes an efficient method for introducing relay nodes in the given communication graph. Our algorithm assigns transmitting ranges to the nodes such that the cost of range assignment function is minimal over all connecting range assignments in the graph. The main contribution of this paper is the O(N log N) algorithm to add relay nodes to the wireless communication network and 2-approximation to assign transmitting ranges to nodes (original and relay). It does not assume that communication graph to be a unit disk graph. The output of the algorithm is the minimal Steiner tree on the graph consists of terminal (original) nodes and relay (additional) nodes. The output of approximation is the range assignments to the nodes.
Implementing a Parallel Matrix Factorization Library on the Cell Broadband Engine
Authors: Vishwas B.C. , Gadia Abhishek , Chaudhuri Mainak
Published: January 2015

Matrix factorization (or often called decomposition) is a frequently used kernel in a large number of applications ranging from linear solvers to data clustering and machine learning. The central contribution of this paper is a thorough performance study of four popular matrix factorization techniques, namely, LU, Cholesky, QR and SVD on the STI Cell broadband engine. The paper explores algorithmic as well as implementation challenges related to the Cell chip-multiprocessor and explains how we achieve near-linear speedup on most of the factorization techniques for a range of matrix sizes. For each of the factorization routines, we identify the bottleneck kernels and explain how we have attempted to resolve the bottleneck and to what extent we have been successful. Our implementations, for the largest data sets that we use, running on a two-node 3.2 GHz Cell BladeCenter (exercising a total of sixteen SPEs), on average, deliver 203.9, 284.6, 81.5, 243.9 and 54.0 GFLOPS for dense LU, dense Cholesky, sparse Cholesky, QR and SVD, respectively. The implementations achieve speedup of 11.2, 12.8, 10.6, 13.0 and 6.2, respectively for dense LU, dense Cholesky, sparse Cholesky, QR and SVD, when running on sixteen SPEs. We discuss the interesting interactions that result from parallelization of the factorization routines on a two-node non-uniform memory access (NUMA) Cell Blade cluster.
The Impact of Dynamic RTS Threshold Adjustment for IEEE 802.11 MAC Protocol
Authors: Mjidi Mostafa , Chakraborty Debasish , Nakamura Naoki , Shiratori Norio
Published: January 2015

In recent years, wireless technologies and application received great attention. The Medium Access Control (MAC) protocol is the main element that determines the efficiency in sharing the limited communication bandwidth of the wireless channel in wireless local area networks (WLANs). IEEE 802.11 introduced the optional RTS/CTS handshaking mechanism to address the hidden terminal problem as well as to reduces the chance of collision in case of higher node density and traffic. RTS Threshold (RT) determines when RTS/CTS mechanism should be used and proved to be an important parameter for performance characteristics in data transmission. We first investigate to find a meaningful threshold value according to the network situation and determine the impact of using or disengaging the RTS/CTS optional mechanism and dynamically adjust the RTS Threshold to maximize data transmission. The results show a significant improvement over existing CSMA/CA and RTS/CTS schemes. Our adaptive scheme performed even better when data rate increases. We verify our proposed scheme both analytically and with extensive network simulation using ns-2.
Available Task-Level Parallelism on the Cell BE
Authors: Rico Alejandro , Ramirez Alex , Valero Mateo
Published: January 2015

There is a clear industrial trend towards chip multiprocessors (CMP) as the most power efficient way of further increasing performance. Heterogeneous CMP architectures take one more step along this power efficiency trend by using multiple types of processors, tailored to the workloads they will execute. Programming these CMP architectures has been identified as one of the main challenges in the near future, and programming heterogeneous systems is even more challenging. High-level programming models which allow the programmer to identify parallel tasks, and the runtime management of the inter-task dependencies, have been identified as a suitable model for programming such heterogeneous CMP architectures. In this paper we analyze the performance of Cell Superscalar, a task-based programming model for the Cell Broadband Engine Architecture, in terms of its scalability to higher number of on-chip processors. Our results show that the low performance of the PPE component limits the scalability of some applications to less than 16 processors. Since the PPE has been identified as the limiting element, we perform a set of simulation studies evaluating the impact of out-of-order execution, branch prediction and larger caches on the task management overhead. We conclude that out-of-order execution is a very desirable feature, since it increases task management performance by 50%. We also identify memory latency as a fundamental aspect in performance, while the working set is not that large. We expect a significant performance impact if task management would run using a fast private memory to store the task dependency graph instead of relying on the cache hierarchy.
Heterogeneous Multicore Parallel Programming for Graphics Processing Units
Authors: Bodin Francois , Bihan Stephane
Published: January 2015

Hybrid parallel multicore architectures based on graphics processing units (GPUs) can provide tremendous computing power. Current NVIDIA and AMD Graphics Product Group hardware display a peak performance of hundreds of gigaflops. However, exploiting GPUs from existing applications is a difficult task that requires non-portable rewriting of the code. In this paper, we present HMPP, a Heterogeneous Multicore Parallel Programming workbench with compilers, developed by CAPS entreprise, that allows the integration of heterogeneous hardware accelerators in a unintrusive manner while preserving the legacy code.
Mesh Algorithms for PDE with Sieve I: Mesh Distribution
Authors: Knepley Matthew G. , Karpeev Dmitry A.
Published: January 2015

We have developed a new programming framework, called Sieve, to support parallel numerical partial differential equation(s) (PDE) algorithms operating over distributed meshes. We have also developed a reference implementation of Sieve in C++ as a library of generic algorithms operating on distributed containers conforming to the Sieve interface. Sieve makes instances of the incidence relation, or arrows, the conceptual first-class objects represented in the containers. Further, generic algorithms acting on this arrow container are systematically used to provide natural geometric operations on the topology and also, through duality, on the data. Finally, coverings and duality are used to encode not only individual meshes, but all types of hierarchies underlying PDE data structures, including multigrid and mesh partitions. In order to demonstrate the usefulness of the framework, we show how the mesh partition data can be represented and manipulated using the same fundamental mechanisms used to represent meshes. We present the complete description of an algorithm to encode a mesh partition and then distribute a mesh, which is independent of the mesh dimension, element shape, or embedding. Moreover, data associated with the mesh can be similarly distributed with exactly the same algorithm. The use of a high level of abstraction within the Sieve leads to several benefits in terms of code reuse, simplicity, and extensibility. We discuss these benefits and compare our approach to other existing mesh libraries.
Accurate Mobility Modeling and Location Prediction Based on Pattern Analysis of Handover Series in Mobile Networks
Authors: Fülöp Péter , Imre Sándor , Szabó Sándor , Szálka Tamás
Published: January 2015

The efficient dimensioning of cellular wireless access networks depends highly on the accuracy of the underlying mathematical models of user distribution and traffic estimations. Mobility prediction also considered as an effective method contributing to the accuracy of IP multicast based multimedia transmissions, and ad hoc routing algorithms. In this paper we focus on the tradeoff between the accuracy and the complexity of the mathematical models used to describe user movements in the network. We propose mobility model extension, in order to utilize user's movement history thus providing more accurate results than other widely used models in the literature. The new models are applicable in real-life scenarios, because these rely on additional information effectively available in cellular networks (e.g. handover history), too. The complexity of the proposed models is analyzed, and the accuracy is justified by means of simulation.
Deletion of Chromosome 4q Predicts Outcome in Stage II Colon Cancer Patients
Authors: Brosens R. P. M. , Belt E. J. T. H. , Haan J. C. , Buffart T. E. , Carvalho B. , Grabsch H. , Quirke P. , Cuesta M. A. , Engel A. F. , Ylstra B. , Meijer G. A.
Published: January 2015

Background: Around 30% of all stage II colon cancer patients will relapse and die of their disease. At present no objective parameters to identify high-risk stage II colon cancer patients, who will benefit from adjuvant chemotherapy, have been established. With traditional histopathological features definition of high-risk stage II colon cancer patients is inaccurate. Therefore more objective and robust markers for prediction of relapse are needed. DNA copy number aberrations have proven to be robust prognostic markers, but have not yet been investigated for this specific group of patients. The aim of the present study was to identify chromosomal aberrations that can predict relapse of tumor in patients with stage II colon cancer.

Materials and Methods: DNA was isolated from 40 formaldehyde fixed paraffin embedded stage II colon cancer samples with extensive clinicopathological data. Samples were hybridized using Comparative Genomic Hybridization (CGH) arrays to determine DNA copy number changes and microsatellite stability was determined by PCR. To analyze differences between stage II colon cancer patients with and without relapse of tumor a Wilcoxon rank-sum test was implemented with multiple testing correction.

Results: Stage II colon cancers of patients who had relapse of disease showed significantly more losses on chromosomes 4, 5, 15q, 17q and 18q. In the microsatellite stable (MSS) subgroup (n=28), only loss of chromosome 4q22.1–4q35.2 was significantly associated with disease relapse (p < 0.05, FDR < 0.15). No differences in clinicopathological characteristics between patients with and without relapse were observed.

Conclusion: In the present series of MSS stage II colon cancer patients losses on 4q22.1–4q35.2 were associated with worse outcome and these genomic alterations may aid in selecting patients for adjuvant therapy.