| Fault-Tolerant Parallel Algorithms for Adaptive Matched-Field Processing on Distributed Array Systems |
24 SEP 2004 |
19 pages |
| Authors:
Kilseok Cho; Alan D. George; Raj Subramaniyan; FLORIDA UNIV GAINESVILLE DEPT OF ELECTRICAL AND COMPUTER ENGINEERING
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 | Continuous innovations in adaptive matched-field processing (MFP) algorithms have presented significant increases in computational complexity and resource requirements that make development and use of advanced parallel processing techniques imperative. In real-time sonar systems operating in severe underwater environments, there is a high likelihood of some part of systems exhibiting defective behavior, resulting in loss of critical network, processor, and sensor elements, and degradation in beam power pattern. Such real-time sonar ... |
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| Evaluation of a Particle Swarm Algorithm for Biomechanical Optimization |
23 SEP 2004 |
41 pages |
| Authors:
Jaco F. Schutte; Byung-Il Koh; Jeffrey A. Reinbolt; Benjamin J. Fregly; Raphael T. Haftka; Alan D. George; FLORIDA UNIV GAINESVILLE MECHANICAL AND AEROSPACE ENGINEERING
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| Optimization is frequently employed in biomechanics research to solve system identification problems, predict human movement, or estimate muscle or other internal forces that cannot be measured directly. Unfortunately, biomechanical optimization problems often possess multiple local minima, making it difficult to find the best solution. Furthermore, convergence in gradient based algorithms can be affected by scaling to account for design variables with different length scales or units. This study evaluates a ... |
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| Parallel Algorithms for Adaptive Matched-Field Processing in Distributed Array Systems |
2003 |
24 pages |
| Authors:
Kilseok Cho; Alan D. George; Raj Subramaniyan; Keonwook Kim; FLORIDA UNIV GAINESVILLE DEPT OF ELECTRICAL AND COMPUTER ENGINEERING
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| Matched-field processing (MFP) localizes sources more accurately than plane-wave beamforming by employing full-wave acoustic propagation models for the cluttered ocean environment. The minimum variance distortionless response MFP (MVDR-MFP) algorithm incorporates the MVDR technique into the MFP algorithm to enhance beamforming performance. Such an adaptive MFP algorithm involves intensive computational and memory requirements due to its complex acoustic model and environmental adaptation. The real-time implementation of adaptive MFP algorithms for large ... |
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| Parallel Simulation of Chip-Multiprocessor Architectures |
2002 |
37 pages |
| Authors:
Matthew C. Chidester; Alan D. George; FLORIDA UNIV GAINESVILLE HIGH-PERFORMANCE COMPUTING AND SIMULATION RESEARCH LAB
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| Chip-multiprocessor (CMP) architectures present a challenge for efficient simulation, combining the requirements of a detailed microprocessor simulator with that of a tightly-coupled parallel system. In this paper, a distributed simulator for target CMPs is presented based on the Message Passing Interface (MPI) designed to run on a host cluster of workstations. Microbenchmark-based evaluation is used to narrow the parallelization design space concerning the performance impact of distributed vs. centralized target ... |
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| Performance Modeling and Evaluation of Topologies for Low-Latency SCI Systems |
2001 |
22 pages |
| Authors:
Damian M. Gonzalez; Alan D. George; Matthew C. Chidester; FLORIDA UNIV GAINESVILLE HIGH-PERFORMANCE COMPUTING AND SIMULATION RESEARCH LAB
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| This paper presents an analytical performance characterization and topology comparison from a latency perspective for the Scalable Coherent Interface (SCI). Experimental methods are used to determine constituent latency components and to verify the results obtained by these analytical models as close approximations of reality. In contrast with simulative models, analytical SCI models are faster to solve, yielding accurate performance estimates very quickly, and thereby broadening the design space that can ... |
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| Comparative Performance Analysis of Directed Flow Control for Real-Time SCI |
2001 |
23 pages |
| Authors:
Robert W. Todd; Matthew C. Chidester; Alan D. George; FLORIDA UNIV GAINESVILLE HIGH-PERFORMANCE COMPUTING AND SIMULATION RESEARCH LAB
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| The distributed nature of routing and flow control in a register-insertion ring topology complicates priority enforcement for real-time systems. Two divergent approaches for priority enforcement for ring-based networks are reviewed: a node-oriented scheme called Preemptive Priority Queue and a ring-wide arbitration approach dubbed TRAIN. This paper introduces a hybrid protocol named Directed Flow Control that combines node- and ring-oriented flow control to yield greater performance. A functional comparison of the ... |
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| Parallel Matched-Field Tracking (MFT) for Distributed Deployable Systems |
2001 |
4 pages |
| Authors:
J. Han; B. Koh; Alan D. George; K. Kim; FLORIDA UNIV GAINESVILLE HIGH-PERFORMANCE COMPUTING AND SIMULATION RESEARCH LAB
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| Quiet submarine threats and high clutter in the littoral undersea environment demand the development and use of enhanced and new acoustic processing algorithms with increased sophistication. These algorithms exhibit high levels of computational complexity and memory utilization, making implementation in real-time sonar array systems a significant challenge. Concomitant with the increase in demand for computing resources implied by new acoustic processing algorithms, mission requirements continue to transition toward the goal ... |
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| Adaptive Sampling for Network Management |
2000 |
24 pages |
| Authors:
Edwin A. Hernandez; Matthew C. Chidester; Alan D. George; FLORIDA UNIV GAINESVILLE DEPT OF ELECTRICAL AND COMPUTER ENGINEERING
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| High-performance networks require sophisticated management systems to identify sources of bottlenecks and detect faults. At the same time, the impact of network queries on the latency and bandwidth available to the applications must be minimized. Adaptive techniques can be used to control and reduce the rate of sampling of network information, reducing the amount of processed data and lessening the overhead on the network. Two adaptive sampling methods are proposed ... |
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| Real-Time Sonar Beamforming on High-Performance Distributed Computers |
2000 |
23 pages |
| Authors:
Alan D. George; Jeff Markwell; Ryan Fogarty; FLORIDA UNIV GAINESVILLE DEPT OF ELECTRICAL AND COMPUTER ENGINEERING
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| Rapid advancements in acoustical beamforming techniques for array signal processing are producing algorithms with increased levels of computational complexity. Concomitantly, autonomous arrays capable of performing most or all of the processing in situ have become a focus for mission-critical applications. To address these changes, future sonar systems will take advantage of parallel in-array processing by coupling transducer nodes with low-power processing devices to achieve higher performance and fault tolerance at ... |
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| Fault Tolerance in Autonomous Acoustic Arrays |
1999 |
15 pages |
| Authors:
Warren A. Rosen; Alan D. George; DREXEL UNIV PHILADELPHIA PA DEPT OF ELECTRICAL AND COMPUTER ENGINEERING
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| The problem of fault tolerance in autonomous disposable fiber-optic based acoustic arrays is considered. The principal source of failures over relatively short mission times is node outage due to battery run-down resulting in possible network failure, degradation in the beam power pattern, and possible loss of critical processing elements[ Network integrity in the presence of node failures requires an optical bypass capable of bypassing several adjacent failed nodes. The effect ... |
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| Comparative Performance Analysis of Parallel Beamformers |
1999 |
6 pages |
| Authors:
Keonwook Kim; Alan D. George; Priyabrata Sinha; FLORIDA UNIV GAINESVILLE DEPT OF ELECTRICAL AND COMPUTER ENGINEERING
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| Advancements in beamforming algorithms are exceeding the computation and communication capabilities of traditional sonar array systems. Implementing parallel beamforming algorithms in situ on distributed array systems holds the potential to provide increased performance and fault tolerance at a lower cost. This paper compares three parallel algorithms for distributed arrays in terms of execution throughput, result latency, scaled speedup, and parallel efficiency. |
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