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Running OpenMP applications efficiently on an everything-shared SDSM

JOURNAL OF parallel AND distributed computing 2006年第5期66卷 647-658页

作者： Costa, JJ Cortes, T Martorell, X Ayguade, E Labarta, J Univ Politecn Catalunya Dept Arquitectura Computadors Barcelona Spain

Traditional software distributed shared memory (SDSM) systems modify the semantics of a real hardware shared memory system by relaxing the coherence semantic and by limiting the memory regions that are actually shared. these semantic modifications are done to improve performance of the applications using it. In this paper. we will show that a SDSM system that behaves like a real shared memory system (without the afore-mentioned relaxations) can also be used to execute OpenMP applications and achieve similar speedups as the ones obtained by traditional SDSM systems. this performance can be achieved by encouraging the cooperation between the SDSM and the OpenMP runtime instead of relaxing the semantics of the shared memory. In addition, techniques like boundaries alignment and page presend are demonstrated as very useful to overcome the limitations of the current SDSM systems. (c) 2005 Elsevier Inc. All rights reserved.

关键词： OpenMP software distributed shared memory scalability adaptability cooperation

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Blazing through Hard Drive Telemetry Data Streams with parallel Processing 18

Blazing through Hard Drive Telemetry Data Streams with Paral...

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18th international conference on distributed and Event-Based systems (DEBS)

作者： Sarbu, Julia Iustina Onica, Emanuel Amariei, Ciprian Alexandru Ioan Cuza Univ Iasi Romania Testable Res Inc Delaware OH USA

ISBN: (纸本)9798400704437

the 2024 DEBS Grand Challenge addresses the topic of hard drive failure predictive maintenance, through analysis of data streams that contain SMART readings, reported by drives located in different groups of storage servers. this paper details the technical implementation of a solution that focuses primarily on parallelizing the data stream processing to obtain vertical scalability. When processing two queries concerning the addressed topic, and setting a threshold of a maximum 16 ms latency for responding, our solution obtained a throughput of about 57% out of the maximum possible when no processing is made on the data stream. We also describe an initial work-in-progress implementation of a distributed extension that relies on Apache Kafka, meant to further scale the throughput of the parallel solution and to address possible failure conditions of retrieving the input stream.

关键词： data stream processing parallel computing Apache Kafka

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Implementing algorithmic skeletons with bulk synchronous parallel ML 18

Implementing algorithmic skeletons with bulk synchronous par...

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18th international conference on parallel and distributed computing, Applications and Technologies, PDCAT 2017

作者： Loulergue, Frederic School of Informatics Computing and Cyber Systems Northern Arizona University FlagstaffAZ United States

ISBN: (纸本)9781538631515

Skeletal parallelism offers a good trade-off between programming productivity and execution efficiency. In this style of parallelism, an application is a composition of algorithmic skeletons. An algorithmic skeleton captures a pattern of parallel algorithm on a distributed data structure, and is also often associated with a sequential algorithm on a sequential data structure that is the counterpart of the parallel data structure. the algorithmic skeleton approach has been inspired by functional programming. It is therefore very natural to embed algorithmic skeletons in a functional programming language. In this paper we present a new algorithmic skeleton library for the statically typed functional language OCaml, and illustrate its use on some applications. this functional skeletal parallel programming library is implemented using the Bulk Synchronous parallel ML parallel programming library for OCaml. © 2017 IEEE.

关键词： parallel programming

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Performance prediction based on hierarchy parallel features captured in multi-processing system 09

Performance prediction based on hierarchy parallel features ...

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18th ACM international Symposium on High Performance distributed computing, HPDC 09, Co-located with the 2009 international Symposium on High Performance distributed computing conference, HPDC'09

作者： Jiaxin, Li Feng, Shi Ning, Deng Qi, Zuo High Performance Embedded Computing Lab. School of Computer Science and Technology Beijing Institute of Technology China

ISBN: (纸本)9781605585871

As the computing ability of high performance computers are improved by increasing the number of computing elements, how to utilize the available computing resources becomes an important issue. Different strategies to solve an problem based on a multi-processing system can bring about distinct performance. In this paper, we propose a method to predict the performance of parallel applications. the method describes the parallel features of the multi-processing systems in a hierarchy way, and evaluates solutions based on the description. In this way, programmers can find the better solution of an application before real programming.

关键词： Forecasting

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parallelNAS: A parallel and distributed System for Neural Architecture Search 22

ParallelNAS: A Parallel and Distributed System for Neural Ar...

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22nd IEEE international conference on High Performance computing and Communications, 18th IEEE international conference on Smart City and 6th IEEE international conference on Data Science and systems, HPCC-SmartCity-DSS 2020

作者： Qu, Xiaoyang Wang, Jianzong Xiao, Jing Co Ltd Shenzhen China

ISBN: (纸本)9781728176499

Although deep learning takes researchers out of complicated feature engineering, designing practical deep learning models is still a complicated process. Neural Architecture Search (NAS) is famous for automating the design of deep learning models. While the fundamental problem of NAS methods is time-consuming, parallel computing is an encouraging way to relieve this problem. We designed a two-level hierarchical parallel system called parallelNAS, comprising a parallel explorer and parallel evaluators. For the parallel explorer, a general-purposed distributed search framework is built on virtualized, massively-parallel, asynchronous infrastructure. For parallel evaluators, we integrate a segment-balanced sparsity scheme into a mainstream data-parallel architecture. the overall experiment results demonstrate that our distributed and parallel system can reach near-linear speedups on a cluster of 64 GPUs. © 2020 IEEE.

关键词： Deep learning

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PlugCloud - Scaling by Plugging a Personal Cloud Infrastructure

PlugCloud - Scaling by Plugging a Personal Cloud Infrastruct...

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IEEE 18th international conference on parallel and distributed systems (ICPADS)

作者： Wee Siong Ng See-Kiong Ng Wu, Wei ASTAR Data Min Dept Inst Infocomm Res Singapore Singapore

ISBN: (纸本)9781467345651

We present a novel elastic system architecture called PlugCloud, which aims to increase the power of low-compute (and possibly mobile) devices, such as tablets, through distributing high-compute tasks, such as rendering, data analysis and visualization, to a set of Plug Computers [1, 2] that can be added or removed from the system incrementally. these devices are connected through a wired/wireless connection and the network is formed seamlessly with zero configurations. PlugCloud allows users of low-compute devices to acquire more processing power externally on demand by plugging one or more plug-computers as needed. Furthermore, it allows a user to remove the plug-computer safely at any time without bringing down the whole system. this makes an elastic network where it can expand and shrink automatically with one or more plug-computers being added or removed from the system. this innovative architecture forms a personal cloud infrastructure on demand to support users' computational needs. We have implemented a computer graphics rendering application using PlugCloud architecture. We will demo our architecture and prototype system using a tablet and several plug-computers.

关键词： component PlugCloud Personal Cloud Plug computing Tablet Computer Processing power on-demand

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MobUser: publish-subscribe communication for mobile nodes

MobUser: publish-subscribe communication for mobile nodes

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IEEE 18th international conference on parallel and distributed systems (ICPADS)

作者： Silva, Mauro Leitao, Joao Ribeiro, Carlos Inst Super Tecn INESC ID Lisbon Portugal

ISBN: (纸本)9781467345651;9780769549033

Mobile devices with wireless communication capabilities are a constant in our daily lives. this offers the possibility for such devices to exchange information for their users to assist in their daily lives. Consider for instance the exchange of information about points of interest in the locations that the user usually frequents. One should expect those devices to support such an application in a decentralized fashion, through pairwise interactions, without the interaction of the user, and avoiding to disclose information that might be sensitive to a central entity. Current solutions are not suitable for supporting such applications since most rely on some kind of centralized architecture (either brokers or rendezvous nodes), other solutions that don't rely on centralized solutions present a high overhead. To address this challenge, in this paper we propose MobUser, a novel topic-based publish-subscribe service specially tailored for supporting location-aware operation for mobile devices in a decentralized fashion. Extensive experimental work shows that MobUser offers not only better performance but also superior delivery rates when compared with a state-of-the-art mobile publish subscribe solution. We also show through a prototype implementation deployed on Android 4.0 devices, that the overhead and energy consumption of MobUser is acceptably low.

关键词： network mobile computing publish-subscribe location aware wireless networks gossip protocols

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On the short-term feasibility of using RFID in realizing ambient-intelligence in Indian homes

On the short-term feasibility of using RFID in realizing amb...

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18th IASTED international conference on parallel and distributed computing and systems

作者： Mahesh, Babu M. Meenakshi, Sundaram A. S. Manikandan, C. Rhymend, Uthariaraj, V Anna Univ Madras Inst Technol Dept Informat Technol Madras 600044 Tamil Nadu India

ISBN: (纸本)9780889866386

We present our research findings on the practicality of using RFID for building context-aware homes in India. Our research is the result of an endeavor to bring this global trend of smart homes to India. Rather than studying the effects of such an influence in its original form-building smart homes equipped with such high-end sensors as real-time, audio-video sensing, and sophisticated, environmental sensors as are popular in a typical smart home-we studied the viability of realizing ambient-intelligence using simple, low-cost, and robust RFID sensors, which we believe would be suitable to Indian dwellings in the near future. We describe the learning and prediction algorithm used in our study;we modeled time as fuzzy-sets and used Markov model for predicting the future locations of inhabitants wearing RFID bracelets. Our system provides context-aware reactive and proactive services. We modeled the uncertainties-involved in inferring users' activities from their location information-using Bayesian Belief Networks or BBNs. this improved the accuracy of prediction considerably. Our experience showed that it is possible to develop cost-effective, easily deployable, context-aware homes using only RFID in India in the short-term before high-end sensing technologies mature and become commercially affordable in the longer run.

关键词： ambient-intelligence probabilistic fuzzy-logic RFID sensing home networks ubiquitous computing

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A fast, Scalable SLINK Algorithm for Commodity Cluster computing Exploiting Spatial Locality

A fast, Scalable SLINK Algorithm for Commodity Cluster Compu...

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18th IEEE international conference on High Performance computing and Communications (HPCC) / 14th IEEE international conference on Smart City (Smart City) / 2nd IEEE international conference on Data Science and systems (DSS)

作者： Goyal, Poonam Kumari, Sonal Sharma, Sumit Kumar, Dhruv Kishore, Vivek Balasubramaniam, Sundar Goyal, Navneet BITS Pilani Dept Comp Sci & Informat Syst Adv Data Analyt & Parallel Technol Lab Pilani Campus Pilani Rajasthan India

ISBN: (纸本)9781509042975

Single linkage (SLINK) hierarchical clustering algorithm is a preferred clustering algorithm over traditional partitioning-based clustering as it does not require the number of clusters as input. But, due to its high time complexity and inherent data dependencies, it does not scale well for large datasets. To the best of our knowledge, all existing parallel SLINK algorithms are based on the traditional SLINK algorithm and thus require large number of computing resources. In this paper, we present a novel optimization of SLINK algorithm, GridSLINK, which is an order of magnitude faster than the existing state-of-the-art implementation. the optimization in GridSLINK comes from reduction in number of distance calculations required by SLINK. this reduction is achieved by exploiting spatial locality of data points and using an adaptive gridding technique. GridSLINK is parallelized for distributed memory systems. Scalable performance is achieved for increasing number of compute nodes. the proposed parallel algorithm, dGridSLINK, is benchmarked against the best existing parallel algorithm in literature and found to outperform the latter for all the real datasets considered. dGridSLINK can cluster millions of data points in few seconds/minutes using a small number of processing elements, without compromising the quality of clustering.

关键词： parallel computing multi-core multi-node clustering SLINK adaptive gridding

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A Java framework for high level parallel programming using powerlists 18

A Java framework for high level parallel programming using p...

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18th international conference on parallel and distributed computing, Applications and Technologies, PDCAT 2017

作者： Niculescu, Virginia Loulergue, Frederic Bufnea, Darius Sterca, Adrian Faculty of Mathematics and Computer Science Babeş-Bolyai University Cluj-Napoca Romania School of Informatics Computing and Cyber Systems Northern Arizona University United States

ISBN: (纸本)9781538631515

parallel programs based on the Divide & Conquer paradigm could be successfully defined in a simple way using powerlists. these parallel recursive data structures and their algebraic theories offer both a methodology to design parallel algorithms and parallel programming abstractions to ease the development of parallel applications. the paper presents how programs based on powerlists can be implemented in Java using the JPLF framework we developed. the design of this framework is based on powerlists theory, but in the same time follows the object-oriented design principles that provide flexibility and maintainability. Examples are given and performance experiments are conducted. the results emphasize the utility and the efficiency of the framework. © 2017 IEEE.

关键词： parallel programming

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