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Hardware and software support for NUMA computing on configurable emulated shared memory architectures

Hardware and software support for NUMA computing on configur...

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

作者： Forsell, Martti Hansson, Erik Kessler, Christoph Makela, Jari-Matti Leppanen, Ville Platform Architectures Team VTT Technical Research Centre of Finland Box 1100 FI-90571 Oulu Finland Computer Science Deptartment Linköping University S-58183 Linkoping Sweden Information Technology University of Turku Joukahaisenkatu 3-5 FI-20014 Turku Finland

ISBN: (纸本)9780769549798

the emulated shared memory (ESM) architectures are good candidates for future general purpose parallel computers due to their ability to provide easy-to-use explicitly parallel synchronous model of computation to programmers as well as avoid most performance bottlenecks present in current multicore architectures. In order to achieve full performance the applications must, however, have enough thread-level parallelism (TLP). To solve this problem, in our earlier work we have introduced a class of configurable emulated shared memory (CESM) machines that provides a special non-uniform memory access (NUMA) mode for situations where TLP is limited or for direct compatibility for legacy code sequential computing or NUMA mechanism. Unfortunately the earlier proposed CESM architecture does not integrate the different modes of the architecture well together e.g. by leaving the memories for different modes isolated and therefore the programming interface is non-integrated. In this paper we propose a number of hardware and software techniques to support NUMA computing in CESM architectures in a seamless way. the hardware techniques include three different NUMA-shared memory access mechanisms and the software ones provide a mechanism to integrate NUMA computation into the standard parallel random access machine (PRAM) operation of the CESM. the hardware techniques are evaluated on our REPLICA CESM architecture and compared to an ideal CESM machine making use of the proposed software techniques. © 2013 ieee.

关键词： Software architecture

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CoHadoop++: A load balanced data co-location in Hadoop distributed File System 5

CoHadoop++: A load balanced data co-location in Hadoop Distr...

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5th International Conference on Advanced Computing, ICoAC 2013

作者： Nishanth, S. Radhikaa, B. Ragavendar, T.J. Babu, Chitra Prabavathy, B.

ISBN: (纸本)9781479934478

Hadoop [4] is a popular distributed computing framework, widely used for business data analytics. While Hadoop performs parallel operations on large data sets, it does not co-locate related data by default. However, performance of log processing operations such as indexing, grouping joins and sessionization on Hadoop can be significantly improved if related logs are partitioned and processed as a group. In order to facilitate this, these partitions need to be placed on the same set of nodes in the cluster. To enable this, a grouping key can be used to identify the related logs. CoHadoop [1], an extension of Hadoop, uses this key to co-locate all those files which correspond to the same key. However, it selects the data nodes randomly for every new key. While doing so, the load introduced on every data node of the cluster is not considered. this leads to an imbalance in the cluster. In order to address this issue, a load balanced co-location algorithm is incorporated into CoHadoop and it is termed as CoHadoop++. It achieves load balance in the cluster through optimal selection of data nodes based their load. Experimental results on CoHadoop++ show that the data placement happens in a load balanced manner. © 2013 ieee.

关键词： Data Analytics

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A Lightweight I/O Scheme to Facilitate Spatial and Temporal Queries of Scientific Data Analytics

A Lightweight I/O Scheme to Facilitate Spatial and Temporal ...

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29th ieee symposium on Massive Storage Systems and Technologies (MSST) - Research Track

作者： Tian, Yuan Liu, Zhuo Klasky, Scott Wang, Bin Abbasi, Hasan Zhou, Shujia Podhorszki, Norbert Clune, Tom Logan, Jeremy Yu, Weikuan Auburn Univ Auburn AL 36849 USA Oak Ridge Natl Lab Oak Ridge TN USA Goddard Space Flight Ctr Greenbelt MD USA Northrop Grumman Corp Falls Church VA USA Univ Tennessee Knoxville Knoxville TN USA

ISBN: (纸本)9781479902170;9781479902187

In the era of petascale computing, more scientific applications are being deployed on leadership scale computing platforms to enhance the scientific productivity. Many I/O techniques have been designed to address the growing I/O bottleneck on large-scale systems by handling massive scientific data in a holistic manner. While such techniques have been leveraged in a wide range of applications, they have not been shown as adequate for many mission critical applications, particularly in data post-processing stage. One of the examples is that some scientific applications generate datasets composed of a vast amount of small data elements that are organized along many spatial and temporal dimensions but require sophisticated data analytics on one or more dimensions. Including such dimensional knowledge into data organization can be beneficial to the efficiency of data post-processing, which is often missing from exiting I/O techniques. In this study, we propose a novel I/O scheme named STAR ( Spatial and Temporal AggRegation) to enable high performance data queries for scientific analytics. STAR is able to dive into the massive data, identify the spatial and temporal relationships among data variables, and accordingly organize them into an optimized multi-dimensional data structure before storing to the storage. this technique not only facilitates the common access patterns of data analytics, but also further reduces the application turnaround time. In particular, STAR is able to enable efficient data queries along the time dimension, a practice common in scientific analytics but not yet supported by existing I/O techniques. In our case study with a critical climate modeling application GEOS-5, the experimental results on Jaguar supercomputer demonstrate an improvement up to 73 times for the read performance compared to the original I/O method.

关键词： climate mitigation data analysis data structures geophysics computing input-output programs parallel machines query processing scientific information systems

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distributed memory breadth-first search revisited: Enabling bottom-up search

Distributed memory breadth-first search revisited: Enabling ...

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

作者： Beamer, Scott Buluc, Aydin Asanovic, Krste Patterson, David EECS Department University of California Berkeley CA United States Computational Research Division Laurence Berkeley National Laboratory Berkeley CA United States

ISBN: (纸本)9780769549798

Breadth-first search (BFS) is a fundamental graph primitive frequently used as a building block for many complex graph algorithms. In the worst case, the complexity of BFS is linear in the number of edges and vertices, and the conventional top-down approach always takes as much time as the worst case. A recently discovered bottom-up approach manages to cut down the complexity all the way to the number of vertices in the best case, which is typically at least an order of magnitude less than the number of edges. the bottom-up approach is not always advantageous, so it is combined with the top-down approach to make the direction-optimizing algorithm which adaptively switches from top-down to bottom-up as the frontier expands. We present a scalable distributed-memory parallelization of this challenging algorithm and show up to an order of magnitude speedups compared to an earlier purely top-down code. Our approach also uses a 2D decomposition of the graph that has previously been shown to be superior to a 1D decomposition. Using the default parameters of the Graph500 benchmark, our new algorithm achieves a performance rate of over 240 billion edges per second on 115 thousand cores of a Cray XE6, which makes it over 7× faster than a conventional top-down algorithm using the same set of optimizations and data distribution. © 2013 ieee.

关键词： Benchmarking

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Symmetric comparison-based fault diagnosis of multiprocessor and distributed systems using nonlinear support vector machines

Symmetric comparison-based fault diagnosis of multiprocessor...

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

作者： Elhadef, Mourad College of Engineering and Computer Science Abu-Dhabi University PO.Box 59911 Abu-Dhabi United Arab Emirates

ISBN: (纸本)9780769549798

In this paper, the problem of identifying the set of permanent faulty nodes using partial syndromes, i.e., when not all the comparison outcomes are available prior to initiating the diagnosis phase, is considered. A new diagnosis approach, using nonlinear support vector machines (SVMs), is described. We consider the symmetric comparison diagnosis model which assumes that nodes are assigned a set of tasks and their outcomes are compared, and that at most t nodes can fail simultaneously. Based on the agreements and disagreements among the nodes' outputs, the diagnosis algorithm must identify all faulty nodes. the new nonlinear SVM-based fault identification algorithm is first trained using various syndromes with known fault sets. then, it is extensively tested using randomly generated diagnosable systems of different sizes and under various fault scenarios. Simulations showed that the nonlinear SVM-based diagnosis performed efficiently, i.e. the diagnosis algorithm correctly identified almost all the faulty nodes even when at most half of the comparison outcomes are missing. In addition, results from the thorough simulation study demonstrate the effectiveness of the nonlinear SVM-based fault identification algorithm, in terms of diagnosis correctness, latency, and scalability. © 2013 ieee.

关键词： Fault tolerance

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Combining parallel algorithms solving the same application: What is the best approach?

Combining parallel algorithms solving the same application: ...

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

作者： Goldman, Alfredo Lepping, Joachim Ngoko, Yanik Trystram, Denis DCC IME USP Rua do Matão 1010 CEP 05508-090 São Paulo Brazil INRIA Rhône-Alpes Grenoble University 38330-Montbonnot-Saint-Martin France Grenoble University LIG Institut Universitaire de France 38330-Montbonnot-Saint-Martin France Université de Paris 13 LIPN 93430 Villetaneuse France

ISBN: (纸本)9780769549798

Given a hard computational problem and a pool of heuristics solving it, it is usual to have a subset of problem instances on which no heuristic outperforms all the others when measuring their runtimes on instances. this phenomenon motivated several studies whose goal was to design frameworks, that can automatically synthesize a set of heuristics solving the same problem for generating a superior one. the success of these investigations however introduced another combinatorial problem;indeed, given a basis of parallel heuristics, there are nowadays several frameworks that can be used for a synthesis: how to choose among them? this paper proposes a solution to this question considering three frameworks for heuristics synthesis, based on algorithm portfolio scheduling in parallel and homogeneous context. For choosing among the frameworks, we comparatively analyze two aspects: the runtime required for the heuristics synthesis within each framework and the performance that can be expected from the produced heuristics. We show that it is hard to make a clear distinction between the frameworks with respect to the runtime synthesis, since the key computational problem to solve here is on all frameworks, NP-complete. On the performance criterion, we show theoretically that from a knowledge of the parallel speedup distributions of the input heuristics, we can determine the framework that will lead to the best performance. the simulations on a SAT database confirm the theoretical results and give also insights into other parallel speed-up distributions that we did not analyze. Based on these results, we propose a preliminary conclusion on how to choose among the considered frameworks. © 2013 ieee.

关键词： Scheduling algorithms

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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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Sonic Millip3De: A Massively parallel 3D-Stacked Accelerator for 3D Ultrasound

Sonic Millip3De: A Massively Parallel 3D-Stacked Accelerator...

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19th ieee International symposium on High Performance Computer Architecture (HPCA)

作者： Sampson, Richard Yang, Ming Wei, Siyuan Chakrabarti, Chaitali Wenisch, thomas F. Univ Michigan Dept EECS Ann Arbor MI 48109 USA

ISBN: (纸本)9781467355872

three-dimensional (3D) ultrasound is becoming common for non-invasive medical imaging because of its high accuracy, safety, and ease of use. Unlike other modalities, ultrasound transducers require little power, which makes hand-held imaging platforms possible, and several low-resolution 2D devices are commercially available today. However, the extreme computational requirements (and associated power requirements) of 3D ultrasound image formation has, to date, precluded hand-held 3D capable devices. We describe the Sonic Millip3De, a new system architecture and accelerator for 3D ultrasound beamformation-the most computationally intensive aspect of image formation. Our three-layer die-stacked design features a custom beamsum accelerator that employs massive data parallelism and a streaming transform-select-reduce pipeline architecture enabled by our new iterative beamsum delay calculation algorithm. Based on RTL-level design and floorplanning for an industrial 45nm process, we show Sonic Millip3De can enable 3D ultrasound with a fully sampled 128x96 transducer array within a 16W full-system power budget (400x less than a conventional DSP solution) and will meet a 5W safe power target by the 11nm node.

关键词： iterative methods medical image processing

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Network decontamination from a black virus

Network decontamination from a black virus

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

作者： Cai, Jie Flocchini, Paola Santoro, Nicola School of Computer Science Carleton University Ottawa ON K1S 5B6 Canada School of Electr. Eng. and Comp. Science University of Ottawa Ottawa ON K1N 6N5 Canada

ISBN: (纸本)9780769549798

In this paper, we consider the problem of decontaminating a network from a black virus (BV) using a team of mobile system agents. the BV is a harmful process which, like the extensively studied black hole (BH), destroys any agent arriving at the network site where it resides;when that occurs, unlike a black hole which is static by definition, a BV moves, spreading to all the neighboring sites, thus increasing its presence in the network. If however one of these sites contains a system agent, that clone of the BV is destroyed (i.e., removed permanently from the system). the initial location of the BV is unknown a priori. the objective is to permanently remove any presence of the BVfrom the network with minimum number of site infections (and thus casualties). the main cost measure is the total number of agents needed to solve the problem. this problem integrates in its definition both the harmful aspects of the classical black hole search problem (where however the dangerous elements are static) with the mobility aspects of the classical intruder capture or network decontamination problem(where however there is no danger for the agents). thus, it is the first attempt to model mobile intruders harmful not only forth sites but also for the agents. We start the study of this problem by focusing on some important classes of interconnection networks: grids, tori, and hypercubes. For each class we present solution protocols and strategies for the team of agents, analyze their worst case complexity, and prove their optimality. © 2013 ieee.

关键词： Gravitation

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Programming support for speculative execution with software transactional memory

Programming support for speculative execution with software ...

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

作者： Feng, Min Gupta, Rajiv Neamtiu, Iulian NEC Laboratories United States University of California Riverside United States

ISBN: (纸本)9780769549798

In this paper, we identify the practical issues that deter the adoption of software transactional memory (STM) for speculation in real applications. these issues include dealing with excessive instrumentation added by naive identification of potential shared accesses, functions that may be called from both transactional and non-transactional contexts, and calls to functions for which the source is unavailable. We address these challenges and provide an approach for developing speculatively-executed code in C/C++ that offers superior programmability and performance. Our contributions consist of a set of programming constructs for writing speculatively-executed code and a compiler that translates code annotated with these constructs into speculatively- executable code that uses STM runtime libraries. Our approach uses annotations that simply mark the boundaries of the code that is to be executed speculatively and supports calling precompiled (e.g., C standard library) and irreversible (e.g., I/O operations and system calls) functions from within transactions. We employ a series of important optimizations for reducing the overhead of speculative execution, including: placement of read/write barriers only for accesses that actually can cause a data race;elimination of redundant read/write barriers by caching shared variables;and eliminating unnecessary search in the write buffer. We evaluate the programmability of our constructs and the performance of our compiler implementation using eight STAMP benchmarks and two real applications-the Velvet genomic assembler and the ITI decision tree constructor. Compared to Intel's STM compiler, our approach requires 91% fewer constructs to be inserted by the programmer, yet it achieves 20.8% better performance. © 2013 ieee.

关键词： parallel programming

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