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SOFTWARE CHALLENGES FOR EXTREME SCALE COMPUTING: GOING FROM PETASCALE TO EXASCALE SYSTEMS

INTERNATIONAL JOURNAL OF HIGH PERFORMANCE COMPUTING APPLICATIONS 2009年第4期23卷 437-439页

作者： Heroux, Michael A. Sandia Natl Labs Albuquerque NM 87185 USA

Preparing applications for a transition from petascale to exascale systems will require a very large investment in several areas of software research and development. The introduction of manycore nodes, the abundance of parallelism, an increase in system faults (including soft errors) and a complicated, multi-component software environment are some of the most challenging issues we face. In this paper we address four topics we believe to be the most the challenging issues and therefore the greatest opportunities for making effective next-generation scalable applications. First and foremost is the need to transform existing applications to run on manycore platforms and properly design new applications. This is particularly challenging in the absence of a standard, portable manycore programming environment, but we can make progress in this direction while manycore programming models are developed. Second is promoting advanced modeling and simulation capabilities such as embedded optimization and uncertainty quantification that lead to higher quality results and orders of magnitude more parallelism. Third is progress toward fault resilience in applications, a critical need as system reliability degrades. Fourth and finally is a qualitative improvement in software design, including the social aspects, as exascale software systems will be increasingly multi-team and multi-faceted efforts.

关键词： exascale computing parallel programming models advanced modeling and simulation fault resilient applications software engineering for computational science and engineering

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Using shared arrays in message-driven parallel programs

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parallel COMPUTING 2012年第1-2期38卷 66-74页

作者： Miller, Phil Becker, Aaron Kale, Laxmikant Univ Illinois Dept Comp Sci Urbana IL 61801 USA

This paper describes a safe and efficient combination of the object-based message-driven execution and shared array parallel programming models. In particular, we demonstrate how this combination engenders the composition of loosely coupled parallel modules safely accessing a common shared array. That loose coupling enables both better flexibility in parallel execution and greater ease of implementing multi-physics simulations. As a case study, we describe how the parallelization of a new method for molecular dynamics simulation benefits from both of these advantages. We also describe a system of typed handle objects that embed some of the determinacy constraints of the Multiphase Shared Array programming model in the C++ type system, to catch some violations at compile time. The combined programming model communicates in terms of these handles as a natural means of detecting and preventing errors. (C) 2011 Elsevier B.V. All rights reserved.

关键词： parallel programming models Composition Distributed shared arrays Asynchronous execution

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User transparent data and task parallel multimedia computing with Pyxis-DT

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FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF GRID COMPUTING AND ESCIENCE 2013年第8期29卷 2252-2261页

作者： van Kessel, Timo van Werkhoven, Ben Drost, Niels Maassen, Jason Bal, Henri E. Seinstra, Frank J. Vrije Univ Amsterdam Dept Comp Sci NL-1081 HV Amsterdam Netherlands Netherlands ESci Ctr NL-1098 XG Amsterdam Netherlands

The research area of Multimedia Content Analysis (MMCA) considers all aspects of the automated extraction of knowledge from multimedia archives and data streams. To satisfy the increasing computational demands of emerging MMCA problems, there is an urgent need to apply High Performance Computing (HPC) techniques. As most MMCA researchers are not also HPC experts, however, there is a demand for programming models and tools that are both efficient and easy to use. Existing user transparent parallelization tools generally use a data parallel approach in which data structures (e.g. video frames) are scattered among the available nodes in a compute cluster. For certain MMCA applications a data parallel approach induces intensive communication, however, which significantly decreases performance. In these situations, we can benefit from applying alternative approaches. We present Pyxis-DT, a user transparent parallel programming model for MMCA applications that employs both data and task parallelism. Hybrid parallel execution is obtained by run-time construction and execution of a task graph consisting of strictly defined building block operations. Results show that for realistic MMCA applications the concurrent use of data and task parallelism can significantly improve performance compared to using either approach in isolation. Extensions for CPU clusters are also presented. (C) 2013 Elsevier B.V. All rights reserved.

关键词： parallel programming models User transparency GPU clusters

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PGAS-FMM: Implementing a distributed fast multipole method using the X10 programming language

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CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE 2014年第3期26卷 712-727页

作者： Milthorpe, Josh Rendell, Alistair P. Huber, Thomas Australian Natl Univ Res Sch Comp Sci Canberra ACT 0200 Australia Australian Natl Univ Res Sch Chem Canberra ACT 0200 Australia

The fast multipole method (FMM) is a complex, multi-stage algorithm over a distributed tree data structure, with multiple levels of parallelism and inherent data locality. X10 is a modern partitioned global address space language with support for asynchronous activities. The parallel tasks comprising FMM may be expressed in X10 by using a scalable pattern of activities. This paper demonstrates the use of X10 to implement FMM for simulation of electrostatic interactions between ions in a cyclotron resonance mass spectrometer. X10's task-parallel model is used to express parallelism by using a pattern of activities mapping directly onto the tree. X10's work stealing runtime handles load balancing fine-grained parallel activities, avoiding the need for explicit work sharing. The use of global references and active messages to create and synchronize parallel activities over a distributed tree structure is also demonstrated. In contrast to previous simulations of ion trajectories in cyclotron resonance mass spectrometers, our code enables both simulation of realistic particle numbers and guaranteed error bounds. Single-node performance is comparable with the fastest published FMM implementations, and critical expansion operators are faster for high accuracy calculations. A comparison of parallel and sequential codes shows the overhead of activity management and work stealing in this application is low. Scalability is evaluated for 8k cores on a Blue Gene/Q system and 512 cores on a Nehalem/InfiniBand cluster. Copyright (c) 2013 John Wiley & Sons, Ltd.

关键词： X10 partitioned global address space (PGAS) active messages parallel programming models scientific computing fast multipole method

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Global arrays: A nonuniform memory access programming model for high-performance computers

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JOURNAL OF SUPERCOMPUTING 1996年第2期10卷 169-189页

作者： Nieplocha, J Harrison, RJ Littlefield, RJ Pacific Northwest National Laboratory Richland USA

Portability efficiency, and ease of coding are all important considerations in choosing the programming model for a scalable parallel application. The message-passing programming model is widely used because of its portability, yet some applications are too complex to code in it while also trying to maintain a balanced computation load and avoid redundant computations. The shared-memory programming model simplifies coding, but it is not portable and often provides little control over interprocessor data transfer costs. This paper describes an approach, called Global Arrays (GAs), that combines the better features of both other models, leading to both simple coding and efficient execution. The key concept of GAs is that they provide a portable interface through which each process in a MIMD parallel program can asynchronously access logical blocks of physically distributed matrices, with no need for explicit cooperation by other processes. We have implemented the GA library on a variety of computer systems, including the Intel Delta and Paragon, the IBM SP-1 and SP-2 (all message passers), the Kendall Square Research KSR-1/2 and the Convex SPP-1200 (nonuniform access shared-memory machines), the GRAY T3D (a globally addressable distributed-memory computer), and networks of UNIX workstations. We discuss the design and implementation of these libraries, report their performance, illustrate the use of GAs in the context of computational chemistry applications, and describe the use of a GA performance Visualization tool.

关键词： NUMA architecture parallel programming models shared memory parallel programming environments distributed arrays Global Arrays one-sided communication scientific computing Grand Challenges computational chemistry

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Hybrid address spaces: A methodology for implementing scalable high-level programming models on non-coherent many-core architectures

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JOURNAL OF SYSTEMS AND SOFTWARE 2014年第0期97卷 47-64页

作者： Papagiannis, Anastasios Nikolopoulos, Dimitrios S. Fdn Res & Technol Hellas Inst Comp Sci FORTH ICS Iraklion Greece Queens Univ Belfast Sch Elect Elect Engn & Comp Sci Belfast BT7 1NN Antrim North Ireland

This paper introduces hybrid address spaces as a fundamental design methodology for implementing scalable runtime systems on many-core architectures without hardware support for cache coherence. We use hybrid address spaces for an implementation of MapReduce, a programming model for large-scale data processing, and the implementation of a remote memory access (RMA) model. Both implementations are available on the Intel SCC and are portable to similar architectures. We present the design and implementation of HyMR, a MapReduce runtime system whereby different stages and the synchronization operations between them alternate between a distributed memory address space and a shared memory address space, to improve performance and scalability. We compare HyMR to a reference implementation and we find that HyMR improves performance by a factor of 1.71 x over a set of representative MapReduce benchmarks. We also compare HyMR with Phoenix(++), a state-of-art implementation for systems with hardware-managed cache coherence in terms of scalability and sustained to peak data processing bandwidth, where HyMR demonstrates improvements of a factor of 3.1 x and 3.2x respectively. We further evaluate our hybrid remote memory access (HyRMA) programming model and assess its performance to be superior of that of message passing. (C) 2014 Elsevier Inc. All rights reserved.

关键词： parallel programming models Runtime systems Many-core processors

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Performance implications of synchronization structure in parallel programming

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parallel COMPUTING 2009年第8-9期35卷 455-474页

作者： Gonzalez-Escribano, Arturo van Gemund, Arjan J. C. Cardenoso-Payo, Valentin Fac Elect Engn Math & Comp Sci NL-2600 GA Delft Netherlands Univ Valladolid Dept Informat E-47011 Valladolid Spain

The restricted synchronization structure of so-called structured parallel programming paradigms has an advantageous effect on programmer productivity, cost modeling, and scheduling complexity. However, imposing these restrictions can lead to a loss of parallelism, compared to using a programming approach that does not impose synchronization structure. In this paper we study the potential loss of parallelism when expressing parallel computations into a programming model which limits the computation graph (DAG) to series-parallel topology, which characterizes all well-known structured programming models. We present an analytical model that approximately captures this loss of parallelism in terms of simple parameters that are related to DAG topology and workload distribution. We validate the model using a wide range of synthetic and real-world parallel computations running on shared and distributed-memory machines. Although the loss of parallelism is theoretically unbounded, our measurements show that for all above applications the performance loss due to choosing a series-parallel structured model is invariably limited up to 10%. In all cases, the loss of parallelism is predictable provided the topology and workload variability of the DAG are known. (C) 2009 Elsevier B.V. All rights reserved.

关键词： parallel programming models Task graphs Performance prediction

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A GENTLE INTRODUCTION TO S-NET: TYPED STREAM PROCESSING AND DECLARATIVE COORDINATION OF ASYNCHRONOUS COMPONENTS

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parallel PROCESSING LETTERS 2008年第2期18卷 221-237页

作者： Grelck, Clemens Scholz, Sven-Bodo Shafarenko, Alex Univ Lubeck Inst Software Technol & Programming Languages Ratzeburger Allee 160 D-23538 Lubeck Germany Univ Hertfordshire Dept Comp Sci Hatfield AL10 9AB Herts England

We present the design of S-NET, a coordination language and component technology based on stream processing. S-NET achieves a near-complete separation between application code, written in a conventional programming language, and coordination code, written in S-NET itself. S-NET boxes integrate existing sequential code as stream-processing components into streaming networks, whose construction is based on algebraic formulae built out of four network combinators. Subtyping on the level of boxes and networks and a tailor-made inheritance mechanism achieve flexible software reuse.

关键词： parallel programming models stream processing component models coordination declarative programming structural subtyping

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programming models AT EXASCALE: ADAPTIVE RUNTIME SYSTEMS, INCOMPLETE SIMPLE LANGUAGES, AND INTEROPERABILITY

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INTERNATIONAL JOURNAL OF HIGH PERFORMANCE COMPUTING APPLICATIONS 2009年第4期23卷 344-346页

作者： Kale, Laxmikant Univ Illinois Siebel Ctr Comp Sci Parallel Programming Lab Urbana IL 61801 USA

Applications running on exascale machines will be complex in many ways. They will involve dynamic and adaptive refinements, and will be composed of multiple, independently developed modules, often involving a multiphysics simulation. The programming models of this era must have several characteristics. First, they need to do away with the notion of processors, and automate resource management via adaptive runtime systems. Data structure-specific frameworks and domain-specific environments will be needed to further simplify programming. More importantly, parallel mini-languages need to be developed, such that each language captures only a restricted subset of possible parallel interactions, but allows for a simple expression of them. Coupled with interoperability and parallel composition, which must be supported in many ways, including message-driven runtime systems, this will create a productive ecosystem of parallel programming models for the exascale era.

关键词： parallel programming models exascale adaptive runtime systems interoperability compositionality

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programming models and systems for Big Data analysis

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INTERNATIONAL JOURNAL OF parallel EMERGENT AND DISTRIBUTED SYSTEMS 2019年第6期34卷 632-652页

作者： Belcastro, Loris Marozzo, Fabrizio Talia, Domenico Univ Calabria DIMES Arcavacata Di Rende Italy

Big Data analysis refers to advanced and efficient datamining and machine learning techniques applied to large amount of data. Research work and results in the area of Big Data analysis are continuously rising, and more and more new and efficient architectures, programming models, systems, and data mining algorithms are proposed. Taking into account the most popular programming models for Big Data analysis (MapReduce, Directed Acyclic Graph, Message Passing, Bulk Synchronous parallel, Workflow and SQL-like), we analysed the features of the main systems implementing them. Such systems are compared using four classification criteria (i.e. level of abstraction, type of parallelism, infrastructure scale and classes of applications) for helping developers and users to identify and select the best solution according to their skills, hardware availability, productivity and application needs. [GRAPHICS] This figure is a word cloud highlighting the most popular words related to Big Data analysis.

关键词： parallel programming models programming systems Big Data analysis cloud computing programming frameworks MapReduce directed acyclic graph message passing bulk synchronous parallel workflow SQL-like

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