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3rd International Workshop on Advanced Computational Intelligence, IWACI 2010

作者： Decraene, James Cheng, Yong Yong Hean Low, Malcolm Yoke Zhou, Suiping Cai, Wentong Choo, Chwee Seng Parallel and Distributed Computing Center School of Computer Engineering Nanyang Technological University Singapore Singapore DSO National Laboratories 20 Science Park Drive Singapore Singapore

ISBN: (纸本)9781424463343

Evolving agent-based simulations enables one to automate the difficult iterative process of modeling complex adaptive systems to exhibit pre-specified/desired behaviors. Nevertheless this emerging technology, combining research advances in agent-based modeling/simulation and evolutionary computation, requires significant computing resources (i.e., high performance computing facilities) to evaluate simulation models across a large search space. Moreover, such experiments are typically conducted in an infrequent fashion and may occur when the computing facilities are not fully available. The user may thus be confronted with a computing budget limiting the use of these "evolvable simulation" techniques. We propose the use of the cloud computing paradigm to address these budget and flexibility issues. To assist this research, we utilize a modular evolutionary framework coined CASE (for complex adaptive system evolver) which is capable of evolving agent-based models using nature-inspired search algorithms. In this paper, we present an adaptation of this framework which supports the cloud computing paradigm. An example evolutionary experiment, which examines a simplified military scenario modeled with the agent-based simulation platform MANA, is presented. This experiment refers to Automated Red Teaming: a vulnerability assessment tool employed by defense analysts to study combat operations (which are regarded here as complex adaptive systems). The experimental results suggest promising research potential in exploiting the cloud computing paradigm to support computing intensive evolvable simulation experiments. Finally, we discuss an additional extension to our cloud computing compliant CASE in which we propose to incorporate a distributed evolutionary approach, e.g., the island-based model to further optimize the evolutionary search.

关键词： Cloud computing

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Precision and error analysis of MATLAB applications during automated hardware synthesis for FPGAs 01

Precision and error analysis of MATLAB applications during a...

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Proceedings of the conference on Design, automation and test in Europe

作者： A. Nayak M. Haldar A. Choudhary P. Banerjee Center for Parallel and Distributed Computing Northwestern University Evanston IL

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A Java graphical user interface for large-scale scientific computations in distributed systems 4

A Java graphical user interface for large-scale scientific c...

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4th International Conference/Exhibition on High Performance computing in the Asia-Pacific Region, HPC-Asia 2000

作者： Shen, X. Thiruvathukal, G. Liao, W. Choudhary, A. Singh, A. Center for Parallel and Distributed Computing Department of Electrical and Computer Engineering Northwestern University EvanstonIL60208 United States School of Computing Telecommunications and Information Sciences JHPC Laboratory DePaul University United States

ISBN: (纸本)0769505902

Large-scale scientific applications present great challenges to computational scientists in terms of obtaining high performance and in managing large datasets. These applications (most of which are simulations) may employ multiple techniques and resources in a heterogeneously distributed environment. Effective working in such an environment is crucial for modern large-scale simulations. In this paper, we present an integrated Java graphical user interface (IJ-GUI) that provides a control platform for managing complex programs and their large datasets easily. As far as performance is concerned, we present and evaluate our initial implementation of two optimization schemes: data replication and data prediction. Data replication can take advantage of 'temporal locality' by caching the remote datasets on local disks;data prediction, on the other hand, provides prefetch hints based on the datasets' past activities that are kept in databases. We first introduce the data contiguity concept in such an environment that guides data prediction. The relationship between the two approaches is discussed. © 2000 IEEE.

关键词： Forecasting

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SOAr-DSGrid: Service-Oriented Architecture for distributed Simulation on the Grid

SOAr-DSGrid: Service-Oriented Architecture for Distributed S...

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Workshop on Principles of Advanced and distributed Simulation (PADS)

作者： Xinjun Chen Wentong Cai S.J. Turner Yong Wang Parallel and Distributed Computing Center Nanyang Technological University Singapore

Simulation is a low cost alternative to experimentation on real-world physical systems. Grid technology enables coordinated use of and secure access to distributed computing resources and data sources. The service-oriented architecture (SOA) is an ideal paradigm for next generation computing. The loose coupling among services in the SOA relieves service consumers from detailed knowledge of implementation, implementation language, and execution platform of the services to be consumed. In this paper, we propose a framework for developing a component-based distributed simulation and executing the simulation in a service-oriented architecture on the Grid. This framework consists of the schemas for developing simulation components and simulation applications, and underlying base component service modules for constructing a simulation component as a service. The use of component interfaces and schemas enables collaborative development of simulation applications, and the deployment of simulation components as services takes advantage of the SOA (e.g., loose coupling, heterogeneity, and transport neutrality). This paper discusses the motivation for developing such a framework and describes the details of its development.

关键词： Service oriented architecture Computational modeling Computer simulation distributed computing Grid computing Resource management Middleware Web services Costs Computer networks

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Application Layer Multicast in P2P distributed Interactive Applications

Application Layer Multicast in P2P Distributed Interactive A...

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International Conference on parallel and distributed Systems (ICPADS)

作者： Yusen Li Wentong Cai Xueyan Tang Parallel and Distributed Computing Center Nanyang Technological University Singapore

By sharing resources among peers in peer-to-peer network, application layer multicast (ALM) has been shown an efficient way to improve the scalability and reduce the latency of communication. To deploy ALM in peer-to-peer distributed interactive applications (DIAs), the property of many-to-many communication of DIA demands multiple multicast trees to be constructed in the overlay. Therefore, how to efficiently allocate resources among multiple trees to maximize the benefit is an important and challenging issue. In this paper, we study the problem of building ALM trees with minimum total end-to-end delay to receivers in peer-to-peer DIAs with resource constraints on network bandwidth. The end-to-end delay from a sender to receivers in a multicast tree consists of the link delay as well as the packet queuing delay at intermediate peers, while the latter is often ignored or not well studied in the previous work. In this paper, we explicitly establish the relationship between the queuing delay at peers and the topology of multicast trees in peer-to-peer DIAs. Based on the relationship, the above mentioned problem is defined and we prove that it is NP-complete. We present a centralized heuristic algorithm to obtain an approximate solution. Moreover, distributed algorithms are also investigated to refine the topology in practical systems with dynamic changes. Extensive experiments were conducted by simulations to evaluate the proposed algorithms and results are reported in the paper.

关键词： Peer-to-peer computing Bandwidth Delays Receivers Heuristic algorithms Vegetation Buildings

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parallelization of MATLAB Applications for a Multi-FPGA System

Parallelization of MATLAB Applications for a Multi-FPGA Syst...

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Annual IEEE Symposium on Field-Programmable Custom computing Machines (FCCM)

作者： A. Nayak M. Haldar A. Choudhary P. Banerjee Center for Parallel and Distributed Computing Northwestern University Evanston IL USA

We present a compiler that takes high level signal and image processing algorithms described in MATLAB and generates an optimized hardware for the WildChild™ board having nine FPGAs and external memory. We propose a Single Program Multiple Data (SPMD) style parallelization framework to automatically generate hardware for all the nine FPGAs. We propose a data alignment and data distribution scheme for minimizing communication across the different FPGAs and present a communication framework based on the WildChild interconnection network for sending and receiving data. Our results show that we get a speedup of around 6 to 7 on eight FPGAs. Further, we propose a prediction mechanism to extract parallelism within a single FPGA. We show that this results in much improved speedups of around 28 on eight FPGAs for the Image Thresholding benchmark. We show that such a framework generates hardwares which are three times slower than the most optimized manual designs, but which can be generated in seconds as compared to days taken by a manual designer.

关键词： MATLAB Field programmable gate arrays Hardware Signal processing Image processing Signal generators Optimizing compilers Multiprocessor interconnection networks Data mining Design optimization

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Precision and error analysis of MATLAB applications during automated hardware synthesis for FPGAs

Precision and error analysis of MATLAB applications during a...

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Design, Automation and Test in Europe Conference and Exhibition

作者： A. Nayak M. Haldar A. Choudhary P. Banerjee Center for Parallel and Distributed Computing Northwestern University Evanston IL USA

ISBN: (纸本)0769509932

We present a compiler that takes high level signal and image processing algorithms described in MATLAB and generates an optimized hardware for an FPGA with external memory. We propose a precision analysis algorithm to determine the minimum number of bits required by an integer variable and a combined precision and error analysis algorithm to infer the minimum number of bits required by a floating point variable. Our results show that on average, our algorithms generate hardware requiring a factor of 5 less FPGA resources in terms of the configurable logic blocks (CLBs) consumed as compared to the hardware generated without these optimizations. We show that our analysis results in the reduction in the size of lookup tables for functions like sin, cos, sqrt, exp etc. Our precision analysis also enables us to pack various array elements into a single memory location to reduce the number external memory accesses. We show that such a technique improves the performance of the generated hardware by an average of 35%.

关键词： Error analysis MATLAB Hardware Field programmable gate arrays Signal processing Image processing Signal generators Optimizing compilers Algorithm design and analysis Logic

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Power optimization of delay constrained circuits

Power optimization of delay constrained circuits

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Annual IEEE International ASIC/SOC Conference

作者： A. Nayak M. Haldar P. Banerjee Chunhong Chen M. Sarrafzadeh Center for Parallel and Distributed Computing Northwestern University Evanston IL USA

We present a framework for combining Voltage Scaling (VS) and Gate Sizing (GS) techniques for power optimizations. We introduce a fast algorithm for choosing gates for sizing and voltage scaling such that the total power is minimized under delay constraints. We also use a more accurate estimate for determining the power dissipation of the circuit by taking into account the short circuit power along with the dynamic power. A better model of the short circuit power is used which takes into account the loading capacitance of the gates. Our results show that the combination of VS and GS perform better than the techniques applied in isolation. An average power reduction of 73% is obtained when decisions are taken assuming dynamic power only. In contrast, average power reduction is 77% when decisions include the short circuit power dissipation.

关键词： Constraint optimization Capacitance Power dissipation Threshold voltage Portable computers CMOS logic circuits Delay effects distributed computing Isolation technology Transistors

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Match virtual machine: an adaptive runtime system to execute MATLAB in parallel

Match virtual machine: an adaptive runtime system to execute...

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International Conference on parallel Processing (ICPP)

作者： M. Haldar A. Nayak A. Kanhere P. Joisha N. Shenoy A. Choudhary P. Banerjee Center for Parallel and Distributed Computing Northwestern University Evanston IL USA

MATLAB is one of the most popular languages for desktop numerical computations as well as for signal and image processing applications. Applying parallel processing techniques to improve performance of MATLAB codes has been the goal of many recent works. Most current frameworks require the user to specify parallelism and/or information regarding type/shape of the variables, thereby sacrificing the user friendliness which is one of the most popular MATLAB features. Other systems work on a restricted subset of MATLAB, thereby limiting the class of applications MATLAB can support. We present a runtime system capable of executing MATLAB code in parallel without any user intervention. The runtime system performs automatic parallelization and type/shape inference of the code at runtime. A unique feature of the runtime system is its capability to automatically adapt to changes in the underlying architecture, making it particularly useful for systems where predicting performance statically is difficult. We present experimental results obtained for the runtime system running on SGI Origin2000 shared memory multiprocessor.

关键词： Virtual machining Adaptive systems MATLAB parallel processing Shape Signal processing Image processing Human computer interaction Limiting Runtime

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An efficient algorithm for managing a parallel heap

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parallel Algorithms and Applications 1994年第3-4期4卷 281-299页

作者： Das, Sajal K. Horng, Wen-Bing Moon, Gyo S. Center for Research in Parallel and Distributed Computing Department of Computer Science University of North Texas Denton TX 76203-6886 United States Dept. of Computer Science and Information Engineering Tamkang Univ Tamsui Taipei Taiwan

We design a cost-optimal algorithm for managing a parallel heap on an exclusive-read exclusive-write (EREW), parallel random access machine (PRAM) model. We also analyze the time and space complexities of our algorithm, which efficiently employs p processors in the range 1 ≤ p ≤ n, where n is the maximum number of items in the parallel heap. It is assumed that a delete-think-insert cycle is repeatedly performed, and each processor requires an arbitrary but the same amount of time (called the think time) for processing an item which in turn generates at most two new items. The use of a global data structure for each level of the heap helps reduce the working memory space required. The time complexity for deleting p items of the highest priority from the parallel heap is O(log p), while that for inserting at most 2p new items is O(log n). With or without incorporating the think time, the speedup of our algorithm is shown to be linear, i.e. O(p). Hence this algorithm is an improvement in time over the one proposed by Deo and Prasad [5, 6]. © 1994, Taylor & Francis Group, LLC. All rights reserved.

关键词： Data structure EREW PRAM Heap Linear speedup parallel algorithm Priority queue

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