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A parallel And Scalable Multi-FPGA based Architecture for High Performance Applications (Abstract Only) 15

A Parallel And Scalable Multi-FPGA based Architecture for Hi...

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proceedings of the 2015 ACM/SIGDA international symposium on Field-Programmable Gate Arrays

作者： Venkatasubramanian Viswanathan Rabie Ben Atitallah Jean-Luc Dekeyser Benjamin Nakache Maurice Nakache Nolam Embedded Systems Paris France University of Valenciennes Valenciennes France University of Lille 1 Lille France Nolam Embedded Systems Pariis France

ISBN: (纸本)9781450333153

Several industrial applications are becoming highly sophisticated and distributed as they capture and process real-time data from several sources at the same time. Furthermore, availability of acquisition channels such as I/O interfaces per FPGA, also dictates how applications are partitioned over several devices. Thus computationally intensive, resource consuming functions are implemented on multiple hardware accelerators, making low-latency communication to be a crucial factor. In such applications, communication between multiple devices means using high-speed point-to-point protocols with little flexibility in terms of communication scalability. The problem with the current systems is that, they are usually built to meet the needs of a specific application, i.e., lacks flexibility to change the communication topology or upgrade hardware resources. This leads to obsolescence, hardware redesign cost, and also wastes computing power. Taking this into consideration, we propose a scalable, modular and customizable computing platform, with a parallel full-duplex communication network, that redefines the computation and communication paradigm in such applications. We have implemented a scalable distributed secure H.264 encoding application with 3 channels over 3 customizable FPGA modules. In a distributed architecture, the inter-FPGA communication time is almost completely overshadowed by the overall execution time for bigger data-sets, and is comparable to the overall execution time of a non-distributed architecture, for the same implementation scaled down to 1 channel for 1 FPGA. This makes our architecture highly scalable and suitable for high-performance streaming applications. With 3 detachable FPGA modules, each sending and receive data simultaneously at 3 GB/s each, we measured the total net unidirectional traffic at any given time in the system is 9 GB/s, making the total net bidirectional bandwidth for 6 modules to be 36 GB/s.

关键词： scalable system parallel reconfigurable architecture distributed intensive signal processing

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ACaZoo: A distributed Key-Value Store based on Replicated LSM-Trees 33

ACaZoo: A Distributed Key-Value Store based on Replicated LS...

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IEEE 33rd international symposium on Reliable distributed systems

作者： Garefalakis, Panagiotis Papadopoulos, Panagiotis Magoutis, Kostas Fdn Res & Technol Hellas FORTH Inst Comp Sci GR-70013 Iraklion Greece

ISBN: (纸本)9781479955848

In this paper we describe the design and implementation of ACaZoo(1), a key-value store that combines strong consistency with high performance and high availability. ACaZoo supports the popular column-oriented data model of Apache Cassandra and HBase. It implements strongly-consistent data replication using primary-backup atomic broadcast of a write-ahead log, which records data mutations to a Log-structured Merge Tree (LSM-Tree). ACaZoo scales by horizontally partitioning the key space via consistent primary-key hashing on available replica groups (RGs). LSM-Tree compactions can hamper performance, especially when they take place at RG primaries. ACaZoo addresses this problem by changing RG leadership prior to heavy compactions, a method that can improve throughput by up to 40% in write-intensive workloads. We evaluate ACaZoo using the Yahoo Cloud Serving Benchmark (YCSB) and compare it to Oracle's NoSQL Database and to Cassandra providing serial consistency via an extension of the Paxos algorithm.

关键词： Compaction Data models databases Nominations and elections Proposals Protocols Servers distributed systems key-value stores nosql databases data models Servers distributed systems Database compaction protocols Cassandra key space Data replication shopping mall REGULATORY GUIDE

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parallel Exact Spliced Alignment on GPU 20

Parallel Exact Spliced Alignment on GPU

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20th IEEE international Conference on parallel and distributed systems (ICPADS)

作者： Nolasco, Anisio Moreano, Nahri Univ Fed Mato Grosso do Sul Sch Comp Campo Grande MS Brazil

ISBN: (纸本)9781479976157

Due to the exponential growth of biological DNA sequence databases, some parallel gene prediction solutions on different high performance platforms have been proposed. Nevertheless, few exact parallel solutions to the spliced alignment problem to gene prediction in eukaryotic organisms have been proposed and none of these solutions use GPUs as the target platform. In this paper, we present the development of two GPU accelerators for an exact solution to the spliced alignment problem applied to gene prediction. Our main contributions are: (a) the identification of two forms to exploit parallelism in the spliced alignment algorithm;(b) two GPU accelerators that achieve speedups up to 52.62 and 90.86, respectively, when compared to a sequential implementation. The accelerators performance scales with input data size, outperforming related work results;(c) a particular organization for the data structures of the accelerators in order to optimize their efficiency;(d) a potential parallelism analysis of the biological data set with the goal of measuring the amount of parallelism that would in fact be available to be exploited by a parallel implementation;and (e) an accurate performance estimation model that enabled estimating the accelerators performance, before implementing them.

关键词： Spliced alignment Gelfand algorithm parallelism accelerator GPU

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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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The Importance and Characteristics of Communication in High Performance Data Analytics

The Importance and Characteristics of Communication in High ...

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IEEE international symposium on Workload Characterization (IISWC)

作者： Anghel, Andreea Rodriguez, German Prisacari, Bogdan IBM Res Zurich Zurich Switzerland

ISBN: (纸本)9781479964536

Social networks and business analytics typically need to process vast amounts of data that are often modeled as graphs. The scale of the data that such applications have to handle requires large-scale distributed computing systems, together with scalable parallel algorithms, to efficiently process the graphs. Representative of the graph-based analytics class of applications is the Graph 500 benchmark (Murphy, ***., 2010), which is designed to assess the performance of supercomputing systems by solving the Breadth-First Search (BFS) graph traversal problem. In this work, we analyze the network data motion of a Graph 500 MPI version of the graph traversal problem, using a large-scale high-performance computing system, i.e., the MareNostrum III supercomputer (http://***/marenostrum-support-services/mn3). We focus our analysis on the node-to-node communication and show that the application runtime is communication-bound, the communication making up as much as 80 % of the execution time of each BFS iteration. We also show that the dominating communication pattern is an overall all-to-all exchange (every process communicates to every other process and roughly the same amount of data is exchanged between any two processes), thus providing preliminary guidance for future application or network design optimization efforts.

关键词： Benchmark testing Computational modeling Data analysis distributed databases Electric breakdown Instruments Runtime Benchmark testing distributed databases Runtime Electric breakdown Computational modeling Communication Research Data analysis execution time Line graph

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parallel Computing for the Radix-2 Fast Fourier Transform 13

Parallel Computing for the Radix-2 Fast Fourier Transform

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13th international symposium on distributed Computing and Applications to Business, Engineering and Science (DCABES)

作者： Xie, Gang Li, Yang-chun China Acad Engn Phys Inst Comp Applicat Mianyang Peoples R China

ISBN: (纸本)9781479941698

The fast Fourier transform (FFT) is a speed-up technique for calculating the discrete Fourier transform (DFT), which in turn is a discrete version of the continuous Fourier transform. The Fast Fourier Transform is used in linear systems analysis, antenna studies, optics, random process modeling, probability theory, quantum physics, and boundary-value problems, and has been very successfully applied to restoration of astronomical data. This paper formulates the one dimensional and two dimensional continuous and discrete Fourier transform, especially the fast Fourier transform, considers their parallel algorithms and reports the speed up of parallel computing in both shared memory and distributed memory modes.

关键词： Discrete Fourier Transform Fast Fourier Transform parallel computing Message Passing Interface OpenMP

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Teaching HDFS/MapReduce systems Concepts to Undergraduates 28

Teaching HDFS/MapReduce Systems Concepts to Undergraduates

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28th IEEE international parallel & distributed Processing symposium Workshops (IPDPSW)

作者： Ngo, Linh B. Duffy, Edward B. Apon, Amy W. Clemson Univ Sch Comp Clemson SC 29634 USA Clemson Univ Clemson Comp & Informat Technol Clemson SC USA

ISBN: (纸本)9781479941162

This paper presents the development of a Hadoop MapReduce module that has been taught in a course in distributed computing to upper undergraduate computer science students at Clemson University. The paper describes our teaching experiences and the feedback from the students over several semesters that have helped to shape the course. We provide suggested best practices for lecture materials, the computing platform, and the teaching methods. In addition, the computing platform and teaching methods can be extended to accommodate emerging technologies and modules for related courses.

关键词： HDFS MapReduce distributed systems parallel computing education

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Efficiently Handling Skew in Outer Joins on distributed systems 14

Efficiently Handling Skew in Outer Joins on Distributed Syst...

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14th IEEE/ACM international symposium on Cluster, Cloud and Grid Computing (CCGrid)

作者： Cheng, Long Kotoulas, Spyros Ward, Tomas E. Theodoropoulos, Georgios Natl Univ Ireland Maynooth Maynooth Kildare Ireland IBM Res Dublin Ireland Univ Durham Durham DH1 3HP England

ISBN: (纸本)9781479927845

Outer joins are ubiquitous in databases and big data systems. The question of how best to execute outer joins in large parallel systems is particularly challenging as real world datasets are characterized by data skew leading to performance issues. Although skew handling techniques have been extensively studied for inner joins, there is little published work solving the corresponding problem for parallel outer joins. Conventional approaches to this problem such as ones based on hash redistribution often lead to load balancing problems while duplication-based approaches incurs significant overhead in terms of network communication. In this paper, we propose a new algorithm, query with counters (QC), for directly handling skew in outer joins on distributed architectures. We present an efficient implementation of our approach based on the asynchronous partitioned global address space (APGAS) parallel programming model. We evaluate the performance of our approach on a cluster of 192 cores (16 nodes) and datasets of 1 billion tuples with different skew. Experimental results show that our method is scalable and, in cases of high skew, faster than the state-of-the-art.

关键词： distributed join parallel join outer join data skew X10

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proceedings of the IEEE symposium on Reliable distributed systems

Proceedings of the IEEE Symposium on Reliable Distributed Sy...

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33rd IEEE international symposium on Reliable distributed systems, SRDS 2014

ISBN: (纸本)9781479955848

The proceedings contain 45 papers. The topics discussed include: Gemini: an emergency line of defense against phishing attacks;a practical experience on the impact of plugins in web security;improving cloud service resilience using brownout-aware load-balancing;the performance of paxos in the cloud;transfer as a service: towards a cost-effective model for multi-site cloud data management;optimistic parallel state-machine replication;ZooFence: principled service partitioning and application to the ZooKeeper coordination service;make the leader work: executive deferred update replication;on the support of versioning in distributed key-value stores;transaction management using causal snapshot isolation in partially replicated databases;and exploiting decoding computational locality to improve the I/O performance of an XOR-coded storage cluster under concurrent failures.

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DisSLib:CC: A Library for distributed Search with a Central Common Search State 28

DisSLib:CC: A Library for Distributed Search with a Central ...

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28th IEEE international parallel & distributed Processing symposium Workshops (IPDPSW)

作者： Kendon, Tyson Denzinger, Joerg Univ Calgary Dept Comp Sci Calgary AB Canada

ISBN: (纸本)9781479941162

distributed search is important for finding solutions to hard problems in artificial intelligence. Building distributed search systems can be difficult because the steps required to solve these problems are interdependent. Fortunately, aspects of search systems exhibit commonalities that allow them to be distributed using several different paradigms. These paradigms can be used as the basis for libraries to make implementing new systems, or distributing existing systems, easier. DisSLib:CC is such a library. DisSLib:CC implements the distributed search paradigm search with a central common search state. In this paradigm, agents collaborate to update a central search state. systems built with DisSLib:CC require very little extra code to implement compared to the standalone versions. These systems can also show improvements in wall-clock run-times, which can be improved by varying the meta-parameters of the distribution paradigm. One such parameter is the number of steps, transitions, that the agents execute before consulting the common search state and in this paper we show how varying this meta-parameter improves the efficiency of the systems.

关键词： distributed Search systems Knowledge Based Search

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