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18th International Conference on Algorithms and Architectures for Parallel Processing (ICA3PP)

作者： Sanz, Victoria Pousa, Adrian Naiouf, Marcelo De Giusti, Armando Natl Univ La Plata Sch Comp Sci III LIDI La Plata Argentina CIC Buenos Aires DF Argentina Consejo Nacl Invest Cient & Tecn Buenos Aires DF Argentina

ISBN: (纸本)9783030050511;9783030050504

Pattern matching algorithms are used in several areas such as network security, bioinformatics and text mining. In order to support large data and pattern sets, these algorithms have to be adapted to take advantage of the computing power of emerging parallel architectures. In this paper, we present a parallel algorithm for pattern matching on CPU-GPU heterogeneous systems, which is based on the Parallel Failureless Aho-Corasick algorithm (PFAC) for GPU. We evaluate the performance of the proposed algorithm on a machine with 36 CPU cores and 1 GPU, using data and pattern sets of different size, and compare it with that of PFAC for GPU and the multithreaded version of PFAC for shared-memory machines. The results reveal that our proposal achieves higher performance than the other two approaches for data sets of considerable size, since it uses both CPU and GPU cores.

关键词： Pattern matching CPU-GPU collaborative computing CPU-GPU heterogeneous systems hybrid programming Aho-Corasick

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Multi-level Load Balancing with an Integrated Runtime Approach 18

Multi-level Load Balancing with an Integrated Runtime Approa...

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18th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid)

作者： Bak, Seonmyeong Menon, Harshitha White, Sam Diener, Matthias Kale, Laxmikant Univ Illinois Urbana IL 61801 USA Lawrence Livermore Natl Lab Livermore CA 94550 USA

ISBN: (纸本)9781538658154

The recent trend of increasing numbers of cores per chip has resulted in vast amounts of on-node parallelism. These high core counts result in hardware variability that introduces imbalance. Applications are also becoming more complex, resulting in dynamic load imbalance. Load imbalance of any kind can result in loss of performance and system utilization. We address the challenge of handling both transient and persistent load imbalances while maintaining locality with low overhead. In this paper, we propose an integrated runtime system that combines the Charm++ distributed programming model with concurrent tasks to mitigate load imbalances within and across shared memory address spaces. It utilizes a periodic assignment of work to cores based on load measurement, in combination with user created tasks to handle load imbalance. We integrate OpenMP with Charm++ to enable creation of potential tasks via OpenMP's parallel loop construct. This is also available to MPI applications through the Adaptive MPI implementation. We demonstrate the benefits of our work on three applications. We show improvements of Lassen by 29.6% on Cori and 46.5% on Theta. We also demonstrate the benefits on a Charm++ application, ChaNGa by 25.7% on Theta, as well as an MPI proxy application, Kripke, using Adaptive MPI.

关键词： Charm plus OpenMP Adaptive MPI Load Balancing hybrid programming

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Extending OpenMP and OpenSHMEM for Efficient Heterogeneous Computing 5

Extending OpenMP and OpenSHMEM for Efficient Heterogeneous C...

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5th Annual IEEE/ACM Parallel Applications Workshop - Alternatives to MPI+X (PAW-ATM)

作者： Lu, Wenbin Tian, Shilei Curtis, Tony Chapman, Barbara SUNY Stony Brook Inst Adv Computat Sci Stony Brook NY 11794 USA

ISBN: (纸本)9781665454100

Heterogeneous supercomputing systems are becoming mainstream thanks to their powerful accelerators. However, the accelerators' special memory model and APIs increase the development complexity, and calls for innovative programming model designs. To address this issue, OpenMP has added target offloading for portable accelerator programming, and MPI allows transparent send-receive of accelerator memory buffers. Meanwhile, Partitioned Global Address Space (PGAS) languages like OpenSHMEM are falling behind for heterogeneous computing because their special memory models pose additional challenges. We propose language and runtime interoperability extensions for both OpenMP and OpenSHMEM to enable portable remote access on GPU buffers, with minimal amount of code changes. Our modified runtime systems work in coordination to manage accelerator memory, eliminating the need for staging communication buffers. Compared to the standard implementation, our extensions attain 6x point-to-point latency improvement, 1.3x better collective operation latency, 4.9x random access throughput, and up to 12.5% better performance in strong scaling configurations.

关键词： Heterogeneous Computing LLVM OpenMP UCX OpenSHMEM hybrid programming

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The Design of Client Software for Self-contained Turbulence Observation Instrument

The Design of Client Software for Self-contained Turbulence ...

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4th International Conference on Digital Manufacturing and Automation (ICDMA)

作者： Song Dalei Lang Wei Xue Bing Sun Fengmei Ocean Univ China Qingdao 266100 Shandong Peoples R China

ISBN: (纸本)9780769550169

Aiming at the communication between the turbulence observation instrument and PC, the client software is designed for the turbulence observation instrument by using Matlab and VC++ hybrid programming method, in order to provide a solution to the problems for the high sampling frequency, the large amount of data, complex data processing of marine turbulence observation. Under the Windows operating system, VC++ is adopted to complete framework customization and interface development;Mat lab is used to complete large amount of turbulence original signal extraction and splicing with its powerful matrix calculation and data manipulation and numerical analysis function;and Mat lab is also used to calculate the result of turbulent kinetic energy dissipation rate. Testing and sea trial results show that the software is reliable, easy to operate, suitable for self-contained turbulence observation instrument.

关键词： turbulent observation VC plus Matlab GUI hybrid programming

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Multi-threaded openSHMEM: A bad idea? 14

Multi-threaded openSHMEM: A bad idea?

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8th International Conference on Partitioned Global Address Space programming Models, PGAS 2014

作者： Jost, Gabriele Hanebutte, Ulf R. Dinan, James Intel Corporation 3600 Juliette Lane Santa ClaraCA95054 United States Intel Corporation 705 5th Ave S SeattleWA98104 United States Intel Corporation 75 Reed Road HudsonMA1749 United States

ISBN: (纸本)9781450332477

The purpose of this document is to stimulate discussions on support for multi-threaded execution in OpenSHMEM. Why is there a need for any thread support at all for an API that follows a shared global address space paradigm? In our ongoing work, we investigate opportunities and challenges introduced through multi-threading, namely implementation challenges and opportunities and required - as well desirable - extensions to the API. Copyright 2014 ACM 978-1-4503-3247-7/14/10 $15.00.

关键词： hybrid programming OpenSHMEM threading

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Numerical simulation methods for reinforced concrete columns considering parameter stochasticity

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STRUCTURES 2023年 57卷

作者： Zhu, Hanbo Cheng, Jinsheng Zhuang, Mei-Ling Sun, Chuanzhi Gao, Li Wang, Youzhi Shao, Junxiang Han, Lu Fang, Haibo Zhao, Lin Suqian Coll Sch Civil Engn & Architecture Suqian 223800 Peoples R China Suqian Coll Jiangsu Prov Engn Res Ctr Prefabricated Bldg & Int Suqian 223800 Peoples R China Suqian City Urban Construct Investment Grp Co Ltd Suqian 223800 Peoples R China Nantong Univ Sch Transportat & Civil Engn Nantong 226019 Peoples R China Shandong Univ Sch Civil Engn Jinan 250061 Peoples R China Second Construct Ltd Co China Construction Engn Div 8 Jinan 250014 Peoples R China Shandong Expressway Construct Management Grp Co Lt Jinan 250098 Peoples R China

Reinforced concrete column specimens with the same parameters often show differences in bearing capacity and deformation under the same loading path. Most of the existing studies attribute the causes to recording instrumentation errors or randomness in material and bond dimensions, but the method to improve the accuracy of numerical simulation of the reinforced concrete components is still unclear. For a given member, the randomness of material and geometry is an important cause of simulation error, which should be taken into account to improve the simulation accuracy. A weighted least squares estimation (WLS) method is used to fuse the test samples of reinforced concrete member section sizes, reinforcement and concrete with confidence factors as weights. The probability distribution functions of reinforced concrete member section sizes, reinforcement and concrete are calculated by a genetic algorithm method. Based on the existing seismic performance test data of reinforced concrete columns, a stochastic finite element model of reinforced concrete columns is developed for seismic performance analysis using Monte Carlo method through a mixture of two software programs, MATLAB and OpenSees. The numerical seismic performance indexes of eight types of reinforced concrete columns were compared with the test results to verify the importance of introducing stochastic parameters into the model. The results demonstrate the simulation accuracy of the finite element model considering parameter randomness is 88% higher than that of the finite element model without considering parameter randomness, which proves the effectiveness of the numerical simulation method for reinforced concrete columns considering parameter randomness.

关键词： Stochastic finite elements hybrid programming weighted least squares (WLS) method Monte Carlo method

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Collectives in hybrid MPI plus MPI code: Design, practice and performance

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PARALLEL COMPUTING 2020年 99卷 102669-102669页

作者： Zhou, Huan Gracia, Jose Zhou, Naweiluo Schneider, Ralf Univ Stuttgart High Performance Comp Ctr Stuttgart HLRS D-70569 Stuttgart Germany

The use of hybrid scheme combining the message passing programming models for inter-node parallelism and the shared memory programming models for node-level parallelism is widely spread. Existing extensive practices on hybrid Message Passing Interface (MPI) plus Open Multi-Processing (OpenMP) programming account for its popularity. Nevertheless, strong programming efforts are required to gain performance benefits from the MPI+OpenMP code. An emerging hybrid method that combines MPI and the MPI shared memory model (MPI+MPI) is promising. However, writing an efficient hybrid MPI+MPI program - especially when the collective communication operations are involved - is not to be taken for granted. In this paper, we propose a new design method to implement hybrid MPI+MPI context-based collective communication operations. Our method avoids on-node memory replications (on-node communication overheads) that are required by semantics in pure MPI. We also offer wrapper primitives hiding all the design details from users, which comes with practices on how to structure hybrid MPI+MPI code with these primitives. Further, the on-node synchronization scheme required by our method/collectives gets optimized. The micro-benchmarks show that our collectives are comparable or superior to those in pure MPI context. We have further validated the effectiveness of the hybrid MPI+MPI model (which uses our wrapper primitives) in three computational kernels, by comparison to the pure MPI and hybrid MPI+OpenMP models.

关键词： MPI MPI shared memory model Collective communication hybrid programming

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A novel hybrid approach for synchronized development of sustainability and resiliency in the wheat network

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COMPUTERS AND ELECTRONICS IN AGRICULTURE 2020年 168卷 1页

作者： Hosseini-Motlagh, Seyyed-Mahdi Samani, Mohammad Reza Ghatreh Saadi, Firoozeh Abbasi Iran Univ Sci & Technol Sch Ind Engn Univ Ave Tehran 16846 Iran

In addition to the great importance of minimizing total cost, resiliency and social indicators have a special place in the agricultural food supply chain. In this respect, a novel multi-objective model is developed that addresses the design/redesign wheat supply chain network, which comprises several suppliers, existing silos, candidate locations for establishing silos, flour factories, and demand zones in an uncertain environment. To develop the mathematical model, two additional and essential dimensions of the supply chain including social impact and resiliency are simultaneously considered. This model is the integration of several proper indicators of resiliency, social responsibility dimensions through considering three objective functions to minimize the cost, non-resiliency, and negative impacts of social responsibility. Due to the fact that input parameters taint with inherent uncertainty, a hybrid stochastic fuzzy-robust programming is introduced, and four different hybrid approaches are developed. Finally, to demonstrate the superiority of the proposed model as well as solution methodology, a real case study is provided. The obtained results show that simultaneously considering cost, resiliency, and social impacts can significantly assist to improve the performance of the wheat supply chain. Moreover, making trade-off between mentioned measures can help the decision-makers to have the principled preference.

关键词： Wheat supply chain Corporate social responsibility Resiliency Multi-objective optimization hybrid programming

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Multimethod optimization in the cloud: A case-study in systems biology modelling

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CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE 2018年第12期30卷

作者： Gonzalez, Patricia Penas, David R. Pardo, Xoan C. Banga, Julio R. Doallo, Ramon Univ A Coruna Comp Architecture Grp La Coruna Spain Univ Santiago de Compostela MODESTYA Res Grp Dept Stat Math Anal & Optimizat Santiago De Compostela Spain Univ Santiago de Compostela Inst Math IMAT Santiago De Compostela Spain IIM CSIC BioProc Engn Grp Vigo Spain

Optimization problems appear in many different applications in science and engineering. A large number of different algorithms have been proposed for solving them;however, there is no unique general optimization method that performs efficiently across a diverse set of problems. Thus, a multimethod optimization, in which different algorithms cooperate to outperform the results obtained by any of them in isolation, is a very appealing alternative. Besides, as real-life optimization problems are becoming more and more challenging, the use of HPC techniques to implement these algorithms represents an effective strategy to speed up the time-to-solution. In addition, a parallel multimethod approach can benefit from the effortless access to q large number of distributed resources facilitated by cloud computing. In this paper, we propose a self-adaptive cooperative parallel multimethod for global optimization. This proposal aims to perform a thorough exploration of the solution space by means of multiple concurrent executions of a broad range of search strategies. For its evaluation, we consider an extremely challenging case-study from the field of computational systems biology. We also assess the performance of the proposal on a public cloud, demonstrating both the potential of the multimethod approach and the opportunity that the cloud provides for these problems.

关键词： cloud computing hybrid programming Microsoft Azure multimethod optimization parallel metaheuristics

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Evaluation of anaerobic biodegradability potential and comparative kinetics of different agro-industrial substrates using a new hybrid computational coding scheme

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JOURNAL OF CLEANER PRODUCTION 2019年 238卷 117921-000页

作者： Cetinkaya, Afsin Yusuf Yetilmezsoy, Kaan Aksaray Univ Tech Sci Vocat Sch Dept Environm Protect Technol TR-68100 Aksaray Turkey Yildiz Tech Univ Fac Civil Engn Dept Environm Engn Davutpasa Campus TR-34220 Istanbul Turkey

The present analysis was conducted as the first study to investigate the biochemical methane potential of four different agro-industrial wastewaters originating from chocolate, slaughterhouse, gum, and beet sugar industries under the same anaerobic fermentation conditions. To the best of our knowledge, no previous study has specifically attempted to pinpoint a hybrid programming strategy for making a quantitative description of the anaerobic biodegradability of these waste streams. Thus, considering the scarcity of the literature in this field, a comprehensive study was conducted to evaluate the amount of bio-methane obtainable from the investigated organic wastes and to predict their kinetics using three different sigmoidal microbial growth curve models (modified Gompertz equation, transference function (reaction curve-type model), and logistic function) within the framework an original MATLAB (R)-based coding scheme. The results showed that methane productions started immediately after 4 h of incubation for all substrates and reached their maximum rates of 118, 116, 108, 34 mL CH4/g VS/day, respectively, for wastewaters from chocolate, slaughterhouse, gum, and beet sugar industries. The corrected mean steady state methane contents were 61.7%, 73.4%, 62.8%, and 62.1% in the respective order. The highest methane yield (943 mL CH4/g VS) was obtained from the slaughterhouse wastewater, and this value was 1.32, 1.58, and 4.56 times higher than those obtained in the anaerobic digestion of chocolate, gum, and beet sugar wastewaters, respectively. Among the three kinetic models tested, the logistic function best explained the behavior of the observed data of all substrates using a Quasi-Newton cubic line search procedure (R-2 = 0.987-0.996) with minimum number of non-linear iterations and function counts. Deviations between the measured and the outputs of the best-fit kinetic model were less than 4.3% in prediction of methane production potentials, suggesting that the pro

关键词： Agro-industrial waste Anaerobic digestion Biochemical methane potential hybrid programming Kinetic modeling

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