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30th IEEE international parallel and distributed Processing symposium (IPDPS)

作者： Di Sanzo, Pierangelo Sannicandro, Marco Ciciani, Bruno Quaglia, Francesco Univ Rome Sapienza DIAG Rome Italy

ISBN: (纸本)9781509021406

software Transactional Memory (STM) may suffer from performance degradation due to excessive conflicts among concurrent transactions. An approach to cope with this issue consists in putting in place smart scheduling policies which temporarily suspend the execution of some transaction in order to reduce the actual conflict rate. In this paper, we present an adaptive transaction scheduling policy relying on a Markov Chain-based model of STM systems. The policy is adaptive in a twofold sense: (i) it schedules transactions depending on throughput predictions by the model as a function of the current system state;(ii) its underlying Markov Chain-based model is periodically re-instantiated at run-time to adapt it to dynamic variations of the workload. We also present an implementation of our adaptive transaction scheduler which has been integrated within the open source TinySTM package. The accuracy of our performance model in predicting the system throughput and the advantages of the adaptive scheduling policy over state-of-the-art approaches have been assessed via an experimental study based on the STAMP benchmark suite.

关键词： transactional memory scheduling performance modeling performance optimization

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Sustained petaflop and beyond: Can parallel computing systems meet the challenges?

Sustained petaflop and beyond: Can parallel computing system...

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19th IEEE international parallel and distributed Processing symposium, IPDPS 2005

作者： Gao, Guang R. Computer Architecture and Parallel System Laboratory Dept. of Electrical and Computer Engineering University of Delaware Department of Electrical and Computer Engineering University of Delaware

ISBN: (纸本)0769523129

Breakthrough-quality scientific discoveries in the new millennium (such as those expected in computation biology and others), along with optimal engineering designs, have created a demand for High-End Computing (HEC) systems with sustained performance requirements at a petaflop scale and beyond. Despite the very pessimistic (if not negative) views on parallel computing systems that have prevailed in 1990s, there seems to be no other viable alternatives for such HEC systems. In this talk, we present a fresh look at the problems facing the design of petascale parallel computing systems. We review several fundamental issues that such HEC parallel computing systems must resolve. These issues include: execution models that support dynamic and adaptive multithreading, fine-grain synchronization, and global name-space and memory consistency. Related issues in parallel programming, dynamic compilation models, and system software design will also be discussed. Present solutions and future direction will be discussed based on (1) application demand (e.g. computation biology and others), (2) the recent trend as demonstrated by the HTMT, HPCS, and the Blue-Gene Cyclops (e.g. Cyclops-64) architectures, and (3) a historical perspective on influential models such as dataflow, along with concepts learned from these models.

关键词： parallel processing systems

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Scaling Irregular Applications through Data Aggregation and software Multithreading

Scaling Irregular Applications through Data Aggregation and ...

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IEEE 28th international parallel & distributed Processing symposium (IPDPS)

作者： Morani, Alessandro Tumeo, Antonino Chavarria-Miranda, Daniel Villa, Oreste Valero, Mateo Pacific NW Natl Lab Richland WA 99352 USA NVIDA Santa Clara CA USA Univ Politecn Catalanya Barcelona Supercomputing Ctr Barcelona Spain

ISBN: (纸本)9780769552071

Emerging applications in areas such as bioinformatics, data analytics, semantic databases and knowledge discovery employ datasets from tens to hundreds of terabytes. Currently, only distributed memory clusters have enough aggregate space to enable in-memory processing of datasets of this size. However, in addition to large sizes, the data structures used by these new application classes are usually characterized by unpredictable and fine-grained accesses: i.e., they present an irregular behavior. Traditional commodity clusters, instead, exploit cache-based processor and high-bandwidth networks optimized for locality, regular computation and bulk communication. For these reasons, irregular applications are inefficient on these systems, and require custom, hand-coded optimizations to provide scaling in both performance and size. Lightweight software multithreading, which enables tolerating data access latencies by overlapping network communication with computation, and aggregation, which allows reducing overheads and increasing bandwidth utilization by coalescing fine-grained network messages, are key techniques that can speed up the performance of large scale irregular applications on commodity clusters. In this paper we describe GMT (Global Memory and Threading), a runtime system library that couples software multithreading and message aggregation together with a Partitioned Global Address Space (PGAS) data model to enable higher performance and scaling of irregular applications on multi-node systems. We present the architecture of the runtime, explaining how it is designed around these two critical techniques. We show that irregular applications written using our runtime can outperform, even by orders of magnitude, the corresponding applications written using other programming models that do not exploit these techniques.

关键词： Multithreading PGAS aggregation semantic graph databases Multithreading unified retrieval models Runtime Scale formation agglomeration Dataset Data structures Scaling Irregular

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A component-based software infrastructure for ubiquitous computing

A component-based software infrastructure for ubiquitous com...

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4th international symposium on parallel and distributed Computing (ISPDC 2005)

作者： Flissi, A Gransart, C Merle, P LIFL CNRS F-59655 Villeneuve Dascq France

ISBN: (纸本)0769524346

Multiplication of mobile devices and generalized use of wireless networks imply changes on the design and execution of distributed software applications targeting ubiquitous computing. Many strong requirements have to be addressed: heterogeneity and limited resources of wireless networks and mobile devices, networked communications between distributed applications, dynamic discovery and automatic deployment on mobile devices. In this paper, we present a component-based software infrastructure to design, discover, deploy, and execute ubiquitous contextual services, i.e. distributed applications providing services to mobile end-users but only available from a particular place. These ubiquitous contextual services are designed as assemblies of distributed software components. These assemblies are dynamically discovered according to end-users' physical location and device capabilities. Then, appropriate assemblies are automatically deployed on users' devices. We have implemented this approach (the software infrastructure and a ubiquitous application example) on top of the OMG CORBA Component Model and the OpenCCM open source platform.

关键词： software engineering

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Performance Analysis of parallel FFT on Large Multi-GPU systems 36

Performance Analysis of Parallel FFT on Large Multi-GPU Syst...

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36th IEEE international parallel and distributed Processing symposium (IEEE IPDPS)

作者： Ayala, Alan Tomov, Stan Stoyanov, Miroslav Haidar, Azzam Dongarra, Jack Univ Tennessee Knoxville TN 37996 USA Oak Ridge Natl Lab Oak Ridge TN USA Nvidia Corp Santa Clara CA USA Univ Manchester Manchester Lancs England

ISBN: (纸本)9781665497473

In this paper we present a performance study of multidimensional Fast Fourier Transforms (FFT) with GPU accelerators on modern hybrid architectures, as those expected for upcoming exascale systems. We assess and leverage features from traditional implementations of parallel FFTs and provide an algorithm that encompasses a wide range of their parameters, and adds novel developments such as FFT grid shrinking and batched transforms. Next, we create a bandwidth model to quantify the computational costs and analyze the well-known communication bottleneck for All-to-All and Point-to-Point MPI exchanges. Then, using a tuning methodology, we are able to accelerate the FFT computation and reduce the communication cost, achieving linear scalability on a large-scale system with GPU accelerators. Finally, our performance analysis is extended to show that carefully tuning the algorithm can further accelerate applications heavily relying on FFTs, such is the case of molecular dynamics software. Our experiments were performed on Summit and Spock supercomputers with IBM Power9 cores, over 3000 NVIDIA V-100 GPUs, and AMD MI-100 GPUs.

关键词： FFT Multi-GPU MPI tuning Scalability

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parallel Graph Partitioning for Complex Networks 29

Parallel Graph Partitioning for Complex Networks

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29th IEEE international parallel and distributed Processing symposium (IPDPS)

作者： Meyerhenke, Henning Sanders, Peter Schulz, Christian Karlsruhe Inst Technol Karlsruhe Germany

ISBN: (纸本)9781479986484

Processing large complex networks like social networks or web graphs has recently attracted considerable interest. To do this in parallel, we need to partition them into pieces of about equal size. Unfortunately, previous parallel graph partitioners originally developed for more regular mesh-like networks do not work well for these networks. This paper addresses this problem by parallelizing and adapting the label propagation technique originally developed for graph clustering. By introducing size constraints, label propagation becomes applicable for both the coarsening and the refinement phase of multilevel graph partitioning. We obtain very high quality by applying a highly parallel evolutionary algorithm to the coarsest graph. The resulting system is both more scalable and achieves higher quality than state-of-the-art systems like ParMetis or PT-Scotch. For large complex networks the performance differences are very big. As an example, our algorithm partitions a web graph with 3.3G edges in 16 seconds using 512 cores of a high-performance cluster while producing a high quality partition none of the competing systems can handle this graph on our system.

关键词： algorithm engineering complex networks graph partitioning parallel algorithms

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Implementing best practices for systems integration and distributed software development in service robotics - The Care-O-bot^®robot family

Implementing best practices for systems integration and dist...

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IEEE/SICE international symposium on System Integration (SII)

作者： Bubeck, Alexander Weisshardt, Florian Sing, Tobias Reiser, Ulrich Haegele, Martin Verl, Alexander Fraunhofer Inst Mfg Engn & Automat IPA Stuttgart Germany

ISBN: (纸本)9781467314978

To date, the complex and diverse demands on robotic software can only be handled by large teams which are often distributed geographically, with each team working on a specific aspect of the robot's functionality. The distributed nature of development and differences in the configuration of standard robot platforms impose particular challenges on the process of system integration. To address these challenges, this paper describes the application of best practices in software engineering to the developer community of the Care-O-bot (R) robot family: strictly defined developer roles, management of platform dependencies by Separation of Concerns, and automated testing. The concrete implementation of these concepts in the development process is demonstrated. By analyzing development activities over the last months we can validate the impact of the concepts in the distributed community.

关键词： automatic test software control engineering computing distributed programming program testing service robots software development management systems software team working

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DADS: Dynamic Slicing Continuously-Running distributed Programs with Budget Constraints 2020

DADS: Dynamic Slicing Continuously-Running Distributed Progr...

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28th ACM Joint Meeting on European software engineering Conference and symposium on the Foundations of software engineering (ESEC/FSE)

作者： Fu, Xiaoqin Cai, Haipeng Li, Li Washington State Univ Pullman WA 99164 USA Monash Univ Clayton Vic Australia

ISBN: (纸本)9781450370431

We present DADS, the first distributed, online, scalable, and cost-effective dynamic slicer for continuously-running distributed programs with respect to user-specified budget constraints. DADS is distributed by design to exploit distributed and parallel computing resources. With an online analysis, it avoids tracing hence the associated time and space costs. Most importantly, DADS achieves and maintains practical scalability and cost-effectiveness tradeoffs according to a given budget on analysis time by continually and automatically adjusting the configuration of its analysis algorithm on the fly via reinforcement learning. Against eight real-world Java distributed systems, we empirically demonstrated the scalability and cost-effectiveness merits of DADS. The open-source tool package of DADS with a demo video is publicly available.

关键词： distributed system dynamic slicing reinforcement learning

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Decentralized in-order execution of a sequential task-based code for shared-memory architectures 36

Decentralized in-order execution of a sequential task-based ...

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36th IEEE international parallel and distributed Processing symposium (IEEE IPDPS)

作者： Castes, Charly Agullo, Emmanuel Aumage, Olivier Saillard, Emmanuelle Inria LaBRI Bordeaux France Ecole Polytech Fed Lausanne Lausanne Switzerland

ISBN: (纸本)9781665497473

The hardware complexity of modern machines makes the design of adequate programming models crucial for jointly ensuring performance, portability, and productivity in high-performance computing (HPC). Sequential task-based programming models paired with advanced runtime systems allow the programmer to write a sequential algorithm independently of the hardware architecture in a productive and portable manner, and let a third party software layer -the runtime system- deal with the burden of scheduling a correct, parallel execution of that algorithm to ensure performance. Many HPC algorithms have successfully been implemented following this paradigm, as a testimony of its effectiveness. Developing algorithms that specifically require fine-grained tasks along this model is still considered prohibitive, however, due to per-task management overhead [1], forcing the programmer to resort to a less abstract, and hence more complex "task+X" model. We thus investigate the possibility to offer a tailored execution model, trading dynamic mapping for efficiency by using a decentralized, conservative in-order execution of the task flow, while preserving the benefits of relying on the sequential taskbased programming model. We propose a formal specification of the execution model as well as a prototype implementation, which we assess on a shared-memory multicore architecture with several synthetic workloads. The results show that under the condition of a proper task mapping supplied by the programmer, the pressure on the runtime system is significantly reduced and the execution of fine-grained task flows is much more efficient.

关键词： Runtime Computational modeling software algorithms Computer architecture Programming Hardware software

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Predictive performance modelling of parallel component compositions

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CLUSTER COMPUTING-THE JOURNAL OF NETWORKS software TOOLS AND APPLICATIONS 2007年第2期10卷 155-166页

作者： Zhao, Lei Jarvis, Stephen A. Univ Warwick Dept Comp Sci High Performance Syst Grp Coventry CV4 7AL W Midlands England

Large-scale scientific computing applications frequently make use of closely-coupled distributed parallel components. The performance of such applications is therefore dependent on the component parts and their interaction at run-time. This paper describes a methodology for predictive performance modelling and evaluation of parallel applications composed of multiple interacting components. In this paper, the fundamental steps and required operations involved in the modelling and evaluation process are identified - including component decomposition, component model combination, M x N communication modelling, dataflow analysis and overall performance evaluation. A case study is presented to illustrate the modelling process and the methodology is verified through experimental analysis.

关键词： performance modelling parallel component composition M x N communication

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