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How to scale dynamic tuning to large parallel applications

How to scale dynamic tuning to large parallel applications

引用

2013 IEEE 37th Annual Computer Software and Applications Conference, COMPSAC 2013

作者： Martinez, Andrea Sikora, Anna Cesar, Eduardo Sorribes, Joan Computer Architecture and Operating Systems Department Universitat Autonoma de Barcelona 08193 Bellaterra Barcelona Spain

ISBN: (纸本)9780769549798

Current performance analysis and tuning tools must be able to improve the performance of large-scale parallel applications. To be effective, such analysis and tuning tools must be scalable and be able to manage the dynamic behaviour of parallel applications. This work presents a scalable solution for dynamic tuning. This approach is based on a hierarchical performance analysis architecture that uses a novel information abstraction mechanism to solve local and global performance problems. We have developed a prototype implementation of the proposed analysis architecture making use of the MRNet framework. Scalability experiments have been performed using this prototype with up to 6400 application tasks. The results obtained show that the proposed analysis architecture will provide the scalability required to carry out dynamic tuning of large-scale parallel applications. © 2013 IEEE.

关键词： Scalability

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High performance adaptive distributed scheduling algorithm

High performance adaptive distributed scheduling algorithm

引用

2013 IEEE 37th Annual Computer Software and Applications Conference, COMPSAC 2013

作者： Narang, Ankur Srivastava, Abhinav Shyamasundar, R.K. IBM India Research Laboratory New Delhi India Laboratoire DInformatique de Grenoble Grenoble France Tata Institute of Fundamental Research Mumbai India

ISBN: (纸本)9780769549798

Exascale computing requires complex runtime systems that need to consider affinity, load balancing and low time and message complexity for scheduling massive scale parallel computations. Simultaneous consideration of these objectives makes online distributed scheduling a very challenging problem. Prior distributed scheduling approaches are limited to shared memory or primarily use work-stealing across distributed memory nodes for load-balancing or depend on the programmer specified affinity. However, the performance of affinity driven scheduling and work stealing based algorithms degrades when the input is irregular(UTS) and/or sparse. In this paper we present a novel adaptive distributed scheduling algorithm (ALDS) for multi-place parallel computations, that uses a unique combination of remote (inter-place) spawns and remote work steals to reduce the overheads in the scheduler, which helps to dynamically maintain load balance across the compute nodes of the system, while ensuring affinity maximally. Using parallel machine learning algorithms such as Support Vector Regression running concurrently with program execution on the target architecture, ALDS can automatically and adaptively tune the parameters for scalable performance. Our design was implemented using GASNet API and POSIX threads. For the UTS (Unbalanced Tree Search) benchmark (using up to 2048 nodes of Blue Gene/P), we deliver superior performance over Charm++ [1] and [2]. © 2013 IEEE.

关键词： Scheduling

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Hybrid modelling of distributed water supply networks

Hybrid modelling of distributed water supply networks

引用

13th IFAC symposium on Large Scale Complex systems: Theory and Applications, LSS 2013

作者： Liu, Dongming Wu, Jing Li, Ning Li, Shaoyuan Department of Automation Shanghai Jiao Tong University Shanghai 200240 China Key Laboratory of System Control and Information Processing Ministry of Education China Changzhou Institute of Light Industry Technology Changzhou Jiangsu 213164 China

In this paper, the modelling of a class of distributed water supply networks is considered, where the modelling of pipes, valves, pump stations and reservoirs are presented separately. Two laws, nodal mass balance and energy conservation, are introduced to derive a general model for the water supply networks. The pumps are assumed to be working in parallel and a hybrid model is provided to describe the dynamics of pump stations, the discrete/ continuous variables in which represent the status (on or off) and the speed of pumps, respectively. Finally, a case study is given to illustrate the effectiveness of our proposed methods. © IFAC.

关键词： Water supply

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HyCache: A user-level caching middleware for distributed file systems

HyCache: A user-level caching middleware for distributed fil...

引用

2013 IEEE 37th Annual Computer Software and Applications Conference, COMPSAC 2013

作者： Zhao, Dongfang Raicu, Ioan Department of Computer Science Illinois Institute of Technology Chicago IL 60616 United States Mathematics and Computer Science Division Argonne National Laboratory Argonne IL 60439 United States

ISBN: (纸本)9780769549798

One of the bottlenecks of distributed file systems deals with mechanical hard drives (HDD). Although solid-state drives (SSD) have been around since the 1990's, HDDs are still dominant due to large capacity and relatively low cost. Hybrid hard drives with a small built-in SSD cache does not meet the need of a large variety of workloads. This paper proposes a middleware that manages the underlying heterogeneous storage devices in order to allow distributed file systems to leverage the SSD performance while leveraging the capacity of HDD. We design and implement a user-level file system, HyCache, that can offer SSD-like performance at a cost similar to a HDD. We show how HyCache can be used to improve performance in distributed file systems, such as the Hadoop HDFS. Experiments show that HyCache achieves up to 7X higher throughput and 76X higher IOPS than Linux Ext4 file system, and can accelerate HDFS by 28% at 32-node scales (compared to vanilla HDFS). © 2013 IEEE.

关键词： Hard disk storage

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Lega SCi: Legacy system C model integration into parallel systemc simulators

Lega SCi: Legacy system C model integration into parallel sy...

引用

2013 IEEE 37th Annual Computer Software and Applications Conference, COMPSAC 2013

作者： Schumacher, Christoph Weinstock, Jan Henrik Leupers, Rainer Ascheid, Gerd Tosoratto, Laura Lonardo, Alessandro Petras, Dietmar Grotker, Thorsten Institute for Communication Technologies and Embedded Systems RWTH Aachen University Germany Istituto Nazionale di Fisica Nucleare Sezione di Roma Rome Italy Synopsys Inc. Aachen Germany

ISBN: (纸本)9780769549798

Virtual prototyping of parallel and embedded systems increases insight into existing computer systems. It further allows to explore properties of new systems already during their specification phase. Virtual prototypes of such systems benefit from parallel simulation techniques due to the increased simulation speed. One common problem full system simulator implementers face is the revision and integration of legacy models coded without thread-safety and deterministic behavior in mind. To lessen this burden, this paper presents a methodology to integrate unmodified SystemC legacy models into parallel SystemC simulators. Using the proposed technique, the embedded platform simulator of the EU FP7 project EURETILE, which inherited a number of legacy models from its predecessor project SHAPES, has been transformed into a parallel simulation platform, demonstrating speed-ups of up to 3.36 on four simulation host cores. © 2013 IEEE.

关键词： Simulators

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On a hybrid MPI-Pthread approach for simplicial branch-And-bound

On a hybrid MPI-Pthread approach for simplicial branch-And-b...

引用

2013 IEEE 37th Annual Computer Software and Applications Conference, COMPSAC 2013

作者： Herrera, Juan F.R. Casado, Leocadio G. Paulavicius, Remigijus Ilinskas, Julius Hendrix, Eligius M.T. Informatics Department University of Almería Agrifood Campus of Int. Excell Almería Spain Institute of Mathematics and Informatics Vilnius University Lithuania Department of Computer Architecture University of Málaga Spain

ISBN: (纸本)9780769549798

We investigate models that efficiently map branch-And-bound algorithms on a distributed computer architecture using a case of multidimensional Lipschitz Global Optimization. A combination of MPI and Pthreads is studied: MPI for distributed computation (inter-node) and Pthreads for multicore computation (intra-node). That model adapts the algorithm to the characteristics of the architecture at hand with an increasing number of nodes. Dynamic load balancing is performed in intra-node space through dynamic generation of threads. Results show performance improvements compared to OpenMP and MPI versions used in previous work. © 2013 IEEE.

关键词： distributed computer systems

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Model Checking Software - 20th international symposium, SPIN 2013, proceedings

Model Checking Software - 20th International Symposium, SPIN...

引用

20th international symposium on Model Checking Software, SPIN 2013

ISBN: (纸本)9783642391750

The proceedings contain 22 papers. The topics discussed include: verifying a quantitative relaxation of linearizability via refinement;a map-reduce parallel approach to automatic synthesis of control software;on-the-fly control software synthesis;compositional approach to suspension and other improvements to LTL translation;regression verification using impact summaries;abstraction-based guided search for hybrid systems;probabilistic verification of coordinated multi-robot missions;synthesizing controllers for automation tasks with performance guarantees;specification and validation of link reversal routing via graph transformations;towards modeling and model checking fault-tolerant distributed algorithms;guard-based partial-order reduction;on the synergy of probabilistic causality computation and causality checking;and mining sequential patterns to explain concurrent counterexamples.

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Accelerating all-to-All protein structures comparison with tmalign using a noc many-cores processor architecture

Accelerating all-to-All protein structures comparison with t...

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2013 IEEE 37th Annual Computer Software and Applications Conference, COMPSAC 2013

作者： Sharma, Anuj Papanikolaou, Antonis Manolakos, Elias S. Department of Informatics and Telecommunications University of Athens Athens Greece Institute of Communication and Computer Systems National Technical University Athens Greece

ISBN: (纸本)9780769549798

Computational challenges for the one-to-many and many-to-many protein structure comparison (PSC) problem are a result of several factors: constantly expanding large-size structural proteomics databases, high computational complexity of pair wise protein comparison algorithms, and the multitude of pair wise comparison approaches used in the field. Advances in processor architectures, such as manycore CPUs, have enabled them to support parallelism making them of interest in speeding up PSC techniques. We presentrckAlign, an implementation of the popularly used TM-AlignPSC algorithm, designed for the Single-Chip Cloud Computer(SCC), an experimental processor created by Intel Labs. We developed a skeleton library, rckskel, and implemented amaster-slaves variant of TM-Align to exploit the parallelism offered by the SCC. We evaluated rckAlign on the SCC and compared it with existing TM-Align software running on a dualcore AMD CPU (2.4 GHz) and on a single-core Intel P54CPentium CPU (800 MHz). We observed an 11-fold speedup relatively to the former and a 44-fold speedup relatively to the latter. A key aspect of the performance of rckAlign on the SCC, is the almost linear speedup achieved with the number of SCC cores used as slaves. The method presented can easily be applied to other PSC algorithms and extended to running multiple PSC algorithms within the same SCC chip. © 2013 IEEE.

关键词： parallel algorithms

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A parallel spatial data analysis infrastructure for the cloud 13

A parallel spatial data analysis infrastructure for the clou...

引用

21st ACM SIGSPATIAL international Conference on Advances in Geographic Information systems, ACM SIGSPATIAL GIS 2013

作者： Ray, Suprio Simion, Bogdan Brown, Angela Demke Johnson, Ryan Department of Computer Science University of Toronto Canada

ISBN: (纸本)9781450325219

Spatial data analysis applications are emerging from a wide range of domains such as building information management, environmental assessments and medical imaging. Time-consuming computational geometry algorithms make these applications slow, even for medium-sized datasets. At the same time, there is a rapid expansion in available processing cores, through multicore machines and Cloud computing. The confluence of these trends demands effective parallelization of spatial query processing. Unfortunately, traditional parallel spatial databases are ill-equipped to deal with the performance heterogeneity that is common in the Cloud. We introduce Niharika, a parallel spatial data analysis infrastructure that exploits all available cores in a heterogeneous cluster. Niharika first uses a declustering technique that creates balanced spatial partitions. Then, Niharika adapts to performance heterogeneity and processing skew in the spatial dataset using dynamic load-balancing. We evaluate Niharika with three load-balancing algorithms and two different spatial datasets (both from TIGER) using Amazon EC2 instances. Niharika adapts to the performance heterogeneity in the EC2 nodes, thereby achieving excellent speedups (e.g., 63.6X using 64 cores on 16 4-core EC2 nodes, in the best case) and outperforming an approach that does not adapt. © 2013 ACM.

关键词： Information management

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HadoopCL: MapReduce on distributed heterogeneous platforms through seamless integration of hadoop and OpenCL

HadoopCL: MapReduce on distributed heterogeneous platforms t...

引用

2013 IEEE 37th Annual Computer Software and Applications Conference, COMPSAC 2013

作者： Grossman, Max Breternitz, Mauricio Sarkar, Vivek Department of Computer Science Rice University United States AMD United States

ISBN: (纸本)9780769549798

As the scale of high performance computing systems grows, three main challenges arise: the programmability, reliability, and energy efficiency of those systems. Accomplishing all three without sacrificing performance requires a rethinking of legacy distributed programming models and homogeneous clusters. In this work, we integrate Hadoop MapReduce with OpenCL to enable the use of heterogeneous processors in a distributed system. We do this by exploiting the implicit data parallelism of mappers and reducers in a MapReduce system. Combining Hadoop and OpenCL provides 1) an easy-to-learn and flexible application programming interface in a high level and popular programming language, 2) the reliability guarantees and distributed file system of Hadoop, and 3) the low power consumption and performance acceleration of heterogeneous processors. This paper presents HadoopCL: an extension to Hadoop which supports execution of user-written Java kernels on heterogeneous devices, optimizes communication through asynchronous transfers and dedicated I/O threads, automatically generates OpenCL kernels from Java byte code using the open source tool APARAPI, and achieves nearly 3x overall speedup and better than 55x speedup of the computational sections for example MapReduce applications, relative to Hadoop. © 2013 IEEE.

关键词： MapReduce

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