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International Conference on Advanced Information Networking and Applications (AINA)

作者： Lingfang Zeng Bharadwaj Veeravalli Xiaorong Li Department of Electrical and Computer Engineering National University of Singapore Singapore Institute of High Performance Computing Agency for Science Technology and Research Singapore

Traditionally, the "best effort, cost free" model of Supercomputers/Grids does not consider pricing. Clouds have progressed towards a service-oriented paradigm that enables a new way of service provisioning based on "pay-as-you-go" model. Large scale many-task workflow (MTW) may be suited for execution on Clouds due to its scale-* requirement (scale up, scale out, and scale down). In the context of scheduling, MTW execution cost must be considered based on users' budget constraints. In this paper, we address the problem of scheduling MTW on Clouds and present a budget-conscious scheduling algorithm, referred to as ScaleStar (or Scale-*). ScaleStar assigns the selected task to a virtual machine with higher comparative advantage which effectively balances the execution time-and-monetary cost goals. In addition, according to the actual charging model, an adjustment policy, refer to as DeSlack, is proposed to remove part of slack without adversely affecting the overall makespan and the total monetary cost. We evaluate ScaleStar with an extensive set of simulations and compare with the most popular HEFT-based LOSS3 algorithm and demonstrate the superior performance of ScaleStar.

关键词： Schedules Computational modeling Scheduling algorithms Scheduling Pricing Cloud computing

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Photonic crystals in proton-exchanged LiNbO3 waveguides for photonic applications

Photonic crystals in proton-exchanged LiNbO3 waveguides for ...

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2012 Photonics Global Conference, PGC 2012

作者： Jun, Deng Jia Wei Kumar, Vanga Sudheer Png, Ching Eng Bettiol, Andrew A. Danner, Aaron J. Department of Electrical and Computer Engineering National University of Singapore Singapore 117576 Singapore Institute of High Performance Computing Agency for Science Technology and Research 1 Fusionopolis Way #16-16 Connexis Singapore 138632 Singapore Henan Key Laboratory of Laser and Opto-electric Information Technology Zhengzhou University Henan 450052 China Department of Physics National University of Singapore Singapore 117542 Singapore

ISBN: (纸本)9781467325165

Photonic crystals realized in LiNbO3 have a great potential to reduce the size and increase the functionality of integrated optical devices. In order to accomplish these aims, fabrication know-how must be mastered yet it remains relatively uncharted. In this work we report the fabrication and optical characterization of photonic crystal structures in annealed proton exchanged (APE) LiNbO3 waveguides. In our work, channel waveguides were fabricated by photolithography patterning followed by immersing LiNbO 3 wafers in molten benzoic acid at 235°C for 5 h. The thickness and the composition profiles of the APE waveguides were measured using the secondary ion mass spectroscopy (SIMS) method. The experimental characterization of the photonic crystal waveguides was performed and a photonic stop band with good sharpness can be observed from the transmission spectra. © 2012 IEEE.

关键词： Niobium compounds

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A multiple-objective workflow scheduling framework for cloud data analytics

A multiple-objective workflow scheduling framework for cloud...

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International Joint Conference on computer science and Software engineering (JCSSE)

作者： Orachun Udomkasemsub Li Xiaorong Tiranee Achalakul Computer Engineering Department King Mongkut's University of Technology Bangkok Thailand Institute of High Performance Computing (IHPC) Agency for Science Technology and Research Singapore

One of the most important characteristics of a cloud system is elasticity in resources provisioning. Cloud fabric often composes of massive and heterogeneous types of resources allowing the sciences and engineering applications in many domains to collaboratively utilize the infrastructure. As the cloud systems are designed for a large number of users, a large volume of data, and various types of applications, efficient task management is needed for cloud data analytics. One of the popular methods used in task management is to represent a set of tasks with a workflow diagram, which can capture task decomposition, communication between subtasks, and cost of computation and communication. In this paper, we proposed a workflow scheduling framework that can efficiently schedule series workflows with multiple objectives onto a cloud system. Our designed framework uses a meta-heuristics method, called Artificial Bee Colony (ABC), to create an optimized scheduling plan. The framework allows multiple constraints and objectives to be set. Conflicts among objectives can also be resolved using Pareto-based technique. A series of experiments are then conducted to investigate the performance in comparison to the algorithms often used in cloud scheduling. Results show that our proposed method is able to reduce 57% cost and 50% scheduling time within a similar makespan of HEFT/LOSS for a typical scientific workflow like Chimera-2.

关键词： Processor scheduling Schedules Scheduling Algorithm design and analysis Optimization Genetic algorithms Equations

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Automatic VM Allocation for Scientific Application

Automatic VM Allocation for Scientific Application

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International Conference on Parallel and Distributed Systems (ICPADS)

作者： Sarunya Pumma Tiranee Achalakul Li Xiaorong Department of Computer Engineering King Mongkut's University of Technology Thonburi Bangkok Thailand Technology and Research Institute of High Performance Computing Agency for Science Singapore

Cloud has been the main technology utilized as a high performance computing (HPC) platform. The characteristics of cloud can satisfy a large scale processing required by scientific applications, which are mostly compute-intensive with big data. Cloud can also reduce the computing cost through sharing and virtualizing of resources. In the cloud, a large number of virtual machines (VM) can be generated on demands. In order to obtain the optimal cost and high efficiency in the task execution on the public cloud, the suitable amount of virtual machines should be properly determined prior to the start of the computation. Moreover, the application should be effectively partitioned and distributed onto the virtual machines. In this paper, we propose an automatic mechanism to allocate the optimal numbers of resources in the cloud. The novel resource estimation model and scheduling algorithm are presented. We select an analytic application with high level of computations in the field of epidemic forecast to demonstrate the use of the designed mechanism. Experimental studies have been conducted to examine the resource prediction accuracy and the scalability of running the application on the cloud.

关键词： Parameter estimation Predictive models Cloud computing Mathematical model Resource management Virtual machining Computational modeling

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Characteristic control of long period fiber grating （LPFG） fabricated by infrared femtosecond laser

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Frontiers of Optoelectronics 2012年第3期5卷 334-340页

作者： Xiaoyan SUN Peng HUANG Jiefeng ZHAO Li WEI Nan ZHANG Dengfeng KUANG Xiaonong ZHU Institute of Modem Optics Nankai UniversityKey Laboratory of Optical Information Science and Technology Ministry of Education Tianjin 300071 China College of Mechanical and Electrical Engineering Central South Universi~State Key Laboratory of High Performance Complex Manufacturing Changsha 410083 China Department of Physics & Computer Science Wilfrid Laurier University Waterloo Ontario N2L 3C5 Canada

Long period fiber gratings （LPFGs） with different spectral characteristics were fabricated with 1 kHz, 50 fs laser pulses. The contrast of resonant rejection band can be significantly increased by a proper amount of axial stress along a fiber during laser writing or post- processing with lower energy density laser irradiation. Variations of focal condition, pulse energy of laser irradiation and the number of grating periods lead to the generation of resonance rejection band of LPFGs from single-peak to multi-peak plus larger out-of-band loss. The out-of-band loss is primarily caused by Mie scattering from the laser processed cites, and it can be reduced by decreasing the duty cycle of grating pitch instead of lowing down the actual power of laser irradiation.

关键词： long-period fiber grating （LPFG） infraredfemtosecond laser out-of-band loss Mie scattering micro-nano-fabrication

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A network clustering algorithm for detection of protein families

A network clustering algorithm for detection of protein fami...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Jiang Xie Minchao Wang Dongbo Dai Huiran Zhang Wu Zhang School of Computer Engineering and Science Shanghai University Shanghai China Department of Mathematics University of California Irvine Irvine CA USA School of Computer Engineering and Science High Performance Computing Center Shanghai University Shanghai China

Detection of protein families in large scale database is a difficult but important biological problem. Computational clustering methods can effectively address the problem. Although there exist many clustering algorithms, most of them are just based on the threshold. Their computational performances are affected by the weight distribution greatly, and they are only valid for some special networks. A new network clustering algorithm, Markov Finding and Clustering (MFC), is proposed to cluster the proteins into their functionally specific families accurately in this paper. The MFC algorithm makes an improvement in the random walk process and reduces the affection of the noise on the clustering result. It has a good performance on these networks which are not well addressed by existing algorithms sensitive to the noise. Finally, experiments on the protein sequence datasets demonstrate that the algorithm is effective in the detection of protein families and has a better performance than the current algorithms.

关键词： Clustering algorithms Proteins Educational institutions Noise Accuracy Bioinformatics Legged locomotion

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A Static Binary Instrumentation Threading Model for Fast Memory Trace Collection

A Static Binary Instrumentation Threading Model for Fast Mem...

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high performance computing, Networking, Storage and Analysis (SCC), SC Companion:

作者： Michael A. Laurenzano Joshua Peraza Laura Carrington Ananta Tiwari William A. Ward Roy Campbell Performance Modeling and Characterization Laboratory San Diego Supercomputer Center University of California San Diego USA Department of Computer Science and Engineering University of California San Diego USA High Performance Computing Modernization Program United States Department of Defense USA

In order to achieve a high level of performance, data intensive applications such as the real-time processing of surveillance feeds from unmanned aerial vehicles will require the strategic application of multi/many-core processors and coprocessors using a hybrid of inter-process message passing (e.g. MPI and SHMEM) and intra-process threading (e.g. pthreads and OpenMP). To facilitate program design decisions, memory traces gathered through binary instrumentation can be used to understand the low-level interactions between a data intensive code and the memory subsystem of a multi-core processor or many-core co-processor. Toward this end, this paper introduces the addition of threading support for PMaCs Efficient Binary Instrumentation Toolkit for Linux/x86 (PEBIL) and compares PEBILs threading model to the threading models of two other popular Linux/x86 binary instrumentation platforms - Pin and Dyninst - on both theoretical and empirical grounds. The empirical comparisons are based on experiments which collect memory address traces for the OpenMP-threaded implementations of the NASA Advanced Supercomputing Parallel Benchmarks (NPBs). This work shows that the overhead of collecting full memory address traces for multithreaded programs is higher in PEBIL (7.7x) than in Pin (4.7x), both of which are significantly lower than Dyninst (897x). This work also shows that PEBIL, uniquely, is able to take advantage of interval-based sampling of a memory address trace by rapidly disabling and re-enabling instrumentation at the transitions into and out of sampling periods in order to achieve significant decreases in the overhead of memory address trace collection. For collecting the memory address streams of each of the NPBs at a 10% sampling rate, PEBIL incurs an average slowdown of 2.9x compared to 4.4x with Pin and 897x with Dyninst.

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Automatic Refactoring of Legacy Fortran Code to the Array Slicing Notation

Automatic Refactoring of Legacy Fortran Code to the Array Sl...

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International Conference on Parallel and Distributed Systems (ICPADS)

作者： Chandrasehar Rajaseharan Wen Jun Tan Wai Teng Tang Stephen John Turner Shyh-Hao Kuo Rick Siow Mong Goh Weng-Fai Wong School of Computer Engineering Nanyang Technological University Singapore Agency for Science Technology and Research Institute of High Performance Computing Singapore Agency for Science Technology and Research Singapore SG Department of Computer Science National University of Singapore Singapore

There are many legacy Fortran programs still in use today, especially scientific codes which were written decades ago. Many of these codes use explicit DO-loops in programs that tend to clutter the code and make it harder to understand and maintain. Modern features of the Fortran language, such as the array slicing notation and introduction of commonly used intrinsic functions, go a long way in helping programmers write code that is easier to read and maintain. We introduce a refactoring tool that can help to transform code to make use of the array slicing notation and related intrinsic functions.

关键词： Arrays Educational institutions Jacobian matrices Optimization Java Clutter Transforms

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Nanoalloy composition-temperature phase diagram for catalyst design: Case study of Ag-Au

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Physical Review B 2012年第3期86卷 035438-035438页

作者： Lin-Lin Wang Teck L. Tan Duane D. Johnson Ames Laboratory U.S. Department of Energy Ames Iowa 50011 USA Institute of High Performance Computing Agency for Science Technology and Research Singapore 138632 Singapore Department of Materials Science and Engineering Iowa State University Ames Iowa 50011 USA

By coupling a cluster expansion with density functional theory (DFT) calculations, we determine the configurational thermodynamics (site preferences and occupations) for alloyed nanoparticles (NPs) as functions of composition (c) and temperature (T), exemplified using a 55-atom Ag-Au truncated cuboctahedron NP. The c−T phase diagram for site occupations gives detailed design information for alloyed NP, especially the thermodynamically stable active sites for catalysis and how they change with stoichiometry and processing temperature. Generally, Ag prefers core and Au prefers shell, agreeing with our universal core-shell preference assessed from DFT impurity segregation energies but with interesting multishell configurations having specific active sites.

关键词： NANOSTRUCTURED materials TEMPERATURE effect PHASE diagrams METAL catalysts METAL clusters DENSITY functionals

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A Combined Dual-stage Framework for Robust Scheduling of Scientific Applications in Heterogeneous Environments with Uncertain Availability

A Combined Dual-stage Framework for Robust Scheduling of Sci...

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IEEE International Symposium on Parallel and Distributed Processing Workshops and Phd Forum (IPDPSW)

作者： Florina M. Ciorba Timothy Hansen Srishti Srivastava Ioana Banicescu Anthony A. Maciejewski Howard Jay Siegel Center for Information Services and High Performance Computing Technische Universität Dresden Dresden Germany Department of Electrical and Computer Engineering Colorado State University Fort Collins CO USA Department of Computer Science and Engineering Mississippi State University Mississippi MS USA Department of Electrical and Computer Engineering Department of Computer Science Colorado State University Fort Collins CO USA

Scheduling parallel applications on existing or emerging computing platforms is challenging, and, among other attributes, must be efficient and robust. A dual-stage framework is proposed in this paper to evaluate the robustness of efficient resource allocation and dynamic load balancing of scientific applications in heterogeneous computing environments with uncertain availability. The first stage employs robust resource allocation heuristics, while the second stage incorporates robust dynamic loop scheduling techniques. The combined dual-stage framework constitutes a comprehensive framework that enables and provides guarantees for the robust execution of scientific applications in computing systems where uncertainty is caused by various unpredictable perturbations. The paper reports on studies for determining the best techniques to be used for each stage that: (a) maximize the probability that the system make span satisfies a deadline, and (b) minimize the system make span for every given availability level in the system. The usefulness and benefits of the proposed framework are demonstrated via a small scale example.

关键词： Availability Robustness Resource management Uncertainty Runtime Dynamic scheduling Program processors

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