The decision for conventional parallel wiring or digital fieldbus technology is often arrived at rather early stages of the design process and therefore very often rather seems to be a matter of taste than to be deriv...
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The decision for conventional parallel wiring or digital fieldbus technology is often arrived at rather early stages of the design process and therefore very often rather seems to be a matter of taste than to be derived via an objective goal function. To overcome this situation, we developed a prototypical engineering decision support system that combines an abstract definition of the communications needs with coarse equipment layout information to derive all the necessary figures to support an informed economic decision for a particular technology by automatically generating a fieldbus material take-off. This paper presents and discusses the architecture and features of the work-in-progress prototype which has been integrated in the commercial CAE-system COMOS.
Summary form only given, as follows. While digital device and digital information become immersive, internet computing as a discipline is at a turning point. Modern computing and communication systems are unprecedente...
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Summary form only given, as follows. While digital device and digital information become immersive, internet computing as a discipline is at a turning point. Modern computing and communication systems are unprecedented powerful and, in the meantime, unprecedented complex. On one hand, new computing paradigms, such as cloud computing, internet of things, cyberinfrastructure, and data centric computing, continue emerging to utilize technological advances. On the other hand, timely challenges, such as reliability, security, power consumption, and coordination and consistency, have to be addressed to meet the ever increasing user demand. High performance computing (HPC) is moving from Peta-flops era to Exa-scale era. How the changing will influence data center based distributed computing, and vice visa. We are at a historical point to ask: what are the challenges and opportunities of HPC-based distributedsystems? This is especially true for Far East, where China just historically reached the first place on the HPC top500 list and launched a unique program in Internet of Things. This panel invites outstanding leaders around the world to explore deliberations regarding the strategic value of HPC-based distributedsystems and discuss disruptive technologies and innovations most likely to overturn today’s internet computing landscape. A record of the panel discussion was not made available for publication as part of the conference proceedings.
The special issue of the ScienceDirect Journal contained 7 extended and revised papers that informed about some of the significant advancements in system performance modeling, analysis, and enhancement. These papers w...
The special issue of the ScienceDirect Journal contained 7 extended and revised papers that informed about some of the significant advancements in system performance modeling, analysis, and enhancement. These papers were presented at the International workshop on Performance Modeling, Evaluation, and Optimization of parallel and distributedsystems (PMEO-PDS'07). The workshop was held along with the 21st ieee International parallel and distributed Processing Symposium (IPDPS'07) from March 26 30, 2007 in California, US. It aimed to promote the discussion on the development of innovative tools and techniques to deal with the rapid evolution and increasing complexity of high-performance computing and networking systems. The selected papers also dealt with a wide range of significant aspects of performance modeling, analysis, and enhancement of high-performance computing and networking systems.
SRAM (static random access memory)-based pipelined algorithmic solutions have become competitive alternatives to TCAMs (ternary content addressable memories) for high-throughput IP lookup. Multiple pipelines can be ut...
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SRAM (static random access memory)-based pipelined algorithmic solutions have become competitive alternatives to TCAMs (ternary content addressable memories) for high-throughput IP lookup. Multiple pipelines can be utilized in parallel to improve the throughput further. However, several challenges must be addressed to make such solutions feasible. First, the memory distribution over different pipelines, as well as across different stages of each pipeline, must be balanced. Second, the traffic among these pipelines should be balanced. Third, the intra-flow packet order (i.e. the sequence) must be preserved. In this paper, we propose a parallel SRAM-based multi-pipeline architecture for IP lookup. A two-level mapping scheme is developed to balance the memory requirement among the pipelines as well as across the stages in each pipeline. To balance the traffic, we propose an early caching scheme to exploit the data locality inherent in the architecture. Our technique uses neither a large reorder buffer nor complex reorder logic. Instead, a flow-aware queuing scheme exploiting the flow information is used to maintain the intra-flow sequence. Extensive simulation using real-life traffic traces shows that the proposed architecture with 8 pipelines can achieve a throughput of up to 10 billion packets per second, i.e. 3.2 Tbps for minimum size (40 bytes) packets, while preserving intra-flow packet order. (c) 2009 Elsevier Inc. All rights reserved.
Genomic alignments, as a means to uncover evolutionary relationships among organisms, are a fundamental tool in computational biology. There is considerable recent interest in using the Cell Broadband Engine, a hetero...
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Genomic alignments, as a means to uncover evolutionary relationships among organisms, are a fundamental tool in computational biology. There is considerable recent interest in using the Cell Broadband Engine, a heterogeneous multicore chip that provides high performance, for biological applications. However, work in genomic alignments so far has been limited to computing optimal alignment scores using quadratic space for the basic global/local alignment problem. In this paper, we present a comprehensive study of developing alignment algorithms on the Cell, exploiting its thread and data level parallelism features. First, we develop a parallel implementation on the Cell that computes optimal alignments and adopts Hirschberg's linear space technique. The former is essential, as merely computing optimal alignment scores is not useful, while the latter is needed to permit alignments of longer sequences. We then present Cell implementations of two advanced alignment techniques-spliced alignments and syntenic alignments. Spliced alignments are useful in aligning mRNA sequences with corresponding genomic sequences to uncover the gene structure. Syntenic alignments are used to discover conserved exons and other sequences between long genomic sequences from different organisms. We present experimental results for these three types of alignments on 16 Synergistic Processing Elements of the IBM QS20 dual-Cell blade system.
The International parallel and distributed Processing Symposium (IPDPS) 2008 panel with the title "How to avoid making the same Mistakes all over again: What the parallel-processing Community has (failed) to offe...
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The International parallel and distributed Processing Symposium (IPDPS) 2008 panel with the title "How to avoid making the same Mistakes all over again: What the parallel-processing Community has (failed) to offer the multi/many-core Generation" sought to provoke discussion on current and recent computer science education in relation to the emergence of fundamentally parallel multi/many-core systems. Is today's/tomorrow's/yesterday's computer science graduate equipped to deal with the challenges of parallel software development for such systems? Are mistakes from the past being unnecessarily repeated? What are the fundamental contributions of the parallel processing research community to the current state of affairs that are possibly being ignored? What are the new challenges that have not been addressed in past parallel processing research? How should computer-science education in parallel processing look like? Should it be taught at all? To the extent that there was consensus among the panelists, they agreed on the premise for the panel, namely that there is a mismatch in computer-science education concerning parallelism, and that there may be reasons to be concerned. They agreed on stressing the importance of (a) applications as a driving factor in research and education, (b) parallel algorithms, and of (c) focusing on the ease of parallel programming and not exclusively on parallel performance, and cited for instance heterogeneous parallelism and power awareness as new issues for the multi-core generation. The panelists were Hideharu Amano (Keio University), John Gustafson (Clearspeed Technologies), Keshav Pingali (University of Austin, Texas), Vivek Sarkar (Rice University), Uzi Vishkin (University of Maryland), and Katherine Yelick (University of California at Berkeley). The panel was organized and moderated by the author. (c) 2009 Elsevier Inc. All rights reserved.
The master/worker (MW) paradigm can be used to implement parallel discrete event simulations (PDES) on metacomputing systems. MW PDES applications incur overheads not found in conventional PDES executions executing on...
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ISBN:
(纸本)9780769537139
The master/worker (MW) paradigm can be used to implement parallel discrete event simulations (PDES) on metacomputing systems. MW PDES applications incur overheads not found in conventional PDES executions executing on tightly coupled machines. We introduce four techniques for reducing these overheads on public resource and desktop grid infrastructures Work unit caching, pipelined state updates, expedited message delivery, and adaptive work unit scheduling mechanisms are described that provide significant reduction in overall overhead when used in tandem. We present performance results showing that an optimized MW PDES system can exhibit performance comparable to a traditional PDES system for a queueing network and a particle physics simulation.
The proceedings contain 146 papers. The topics discussed include: diversity order of linear equalizers for doubly selective channels;decentralized asymptotic detection by running consensus;a new distributed algorithm ...
ISBN:
(纸本)9781424436965
The proceedings contain 146 papers. The topics discussed include: diversity order of linear equalizers for doubly selective channels;decentralized asymptotic detection by running consensus;a new distributed algorithm for parametric data modeling in wireless sensor networks;channel aware sensor selection in distributed detection systems;an SMF approach to distributed average consensus in clustered sensor networks;robust precoding for orthogonal space-time block coded MIMO cognitive radio networks;truth reveling opportunistic scheduling in cognitive radio systems;wideband spectrum sensing in cognitive radio: joint estimation of noise variance and multiple signal levels;a nonparametric sequential Kolmogorov-Smirnov test for transmit opportunity detection at the MAC layer;and outage margin and power constraints in cognitive radio with multiple antennas.
The proceedings contain 4 papers. The topics discussed include: data-driven batch scheduling;a distributed architecture for data mining and integration;balancing TCP buffer vs parallel streams in application level thr...
ISBN:
(纸本)9781605585895
The proceedings contain 4 papers. The topics discussed include: data-driven batch scheduling;a distributed architecture for data mining and integration;balancing TCP buffer vs parallel streams in application level throughput optimization;and abstract storage: moving file format-specific abstractions into petabyte-scale storage systems.
The proceedings contain 103 papers. The topics discussed include: directed gossiping for distributed data aggregation;robust semiparametric amplitude estimation of sinusoidal signals: the multi-sensor case;robust shor...
ISBN:
(纸本)9781424451807
The proceedings contain 103 papers. The topics discussed include: directed gossiping for distributed data aggregation;robust semiparametric amplitude estimation of sinusoidal signals: the multi-sensor case;robust short-term load forecasting using projection statistics;optimal scheduling and QoS power control for cognitive underlay networks;energy-efficient distributed spectrum sensing with convex optimization;time delay estimation in cognitive radio systems;comparison of precoding methods for broadband MIMO systems;MSE uplink-downlink duality of MIMO systems under imperfect CSI;hybrid probabilistic data association and variational filtering for multi-target tracking in wireless sensor networks;subspace-based Bayesian blind source separation for hyperspectral imagery;on MCMC-based particle methods for Bayesian;and a transceive strategy for regenerative multi-antenna multi-way relaying filtering: application to multitarget tracking.
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