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检索条件"任意字段=13th IEEE International Symposium on Parallel and Distributed Processing with Applications"

共 2574 条记录，以下是181-190 订阅

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SNOW Revisited: Understanding When Ideal READ Transactions Are Possible 35

SNOW Revisited: Understanding When Ideal READ Transactions A...

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35th ieee international parallel and distributed processing symposium (IPDPS)

作者： Konwar, Kishori M. Lloyd, Wyatt Lu, Haonan Lynch, Nancy MIT RLE 77 Massachusetts Ave Cambridge MA 02139 USA Princeton Univ Comp Sci Princeton NJ 08544 USA MIT CSAIL 77 Massachusetts Ave Cambridge MA 02139 USA

ISBN: (纸本)9781665440660

READ transactions that read data distributed across servers dominate the workloads of real-world distributed storage systems. the SNOW theorem [13] stated that ideal READ transactions that have optimal latency and the strongest guarantees-i.e., "SNOW" READ transactions-are impossible in one specific setting that requires three or more clients: at least two readers and one writer. However, it left many open questions. We close all of these open questions with new impossibility results and new algorithms. First, we prove rigorously the result from [13] saying that it is impossible to have a READ transactions system that satisfies SNOW properties with three or more clients. the insight we gained from this proof led to leasing out the implicit assumptions that are required to stale the results and also, resolving the open question regarding the possibility of SNOW with two clients. We show that it is possible to design an algorithm, where SNOW is possible in a multi-writer, single-reader (MWSR) setting when a client can send messages to other clients;on the other hand, we prove it is impossible to implement SNOW in a multi-writer, single-reader (MWSR) setting-which is more general than the two-client setting-when client-to-client communication is disallowed. We also correct the previous claim in [13] that incorrectly identified one existing system, Eiger [12], as supporting the strongest guarantees (SW) and whose read-only transactions had bounded latency. thus, there were no previous algorithms that provided the strongest guarantees and had bounded latency. Finally, we introduce the first two algorithms to provide the strongest guarantees with bounded latency.

关键词： distributed transactions strict-serializability

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Combining Static and Dynamic Analysis to Query Characteristics of HPC applications

Combining Static and Dynamic Analysis to Query Characteristi...

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35th ieee international parallel and distributed processing symposium (IPDPS)

作者： Welch, Aaron Hernandez, Oscar Chapman, Barbara Univ Houston Houston TX 77004 USA Oak Ridge Natl Lab Oak Ridge TN USA SUNY Stony Brook Stony Brook NY 11794 USA

ISBN: (纸本)9781665435772

Emerging HPC platforms are becoming more difficult to program as a result of systems with different node architectures, some with a small number of "fat" heterogenous nodes (consisting of multiple accelerators) and others with a large number of "thin" homogenous nodes consisting of multi-core CPUs connected with high speed interconnects. New programming models are emerging to address performance portability of the applications as well as a set of scientific libraries that applications can use to exploit these architectures efficiently. To port applications to new architectures, developers need information about their source code characteristics including static and dynamic (e.g. performance) information to refactor the code, understand their data and code structure, and library usage as well as program information to direct their optimisation efforts and make key decisions. In this paper, we describe a tool that combines compiler and profiler information to query program characteristics in a given programming environment. Static and dynamic data about applications is collected and stored together in an SQL database that can be later queried to study application characteristics and patterns. We will demonstrate the capabilities of this tool with an application-driven case study that aims at understanding application code and its use of scientific libraries via a real world example from the molecular simulation application CP2K.

关键词： distributed processing Program processors Databases Conferences Tools Programming Libraries

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parallel Real-time Simulation on Commodity Hardware with Reusable Power System Models 25

Parallel Real-time Simulation on Commodity Hardware with Reu...

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25th ieee/ACM international symposium on distributed Simulation and Real Time applications (DS-RT)

作者： Eidenbenz, Raphael Franke, Carsten Larsson, Mats Moga, Alexandru Sivanthi, thanikesavan Hitachi ABB Power Grids Res Zurich Switzerland Munich Univ Appl Sci Munich Germany Hitachi ABB Power Grids Zurich Switzerland ABB Corp Res Baden Switzerland

ISBN: (纸本)9781665433266

this paper proposes a real-time power system simulation framework that is capable of simulating steady state and electromechanical transients of power systems, with submillisecond time resolution. the framework can integrate power system component models packed as reusable Functional Mockup Units (FMUs) to flexibly create power system simulations without the need to recreate new models for different power systems. the integration of individual components is based on a novel model decomposition method, which enables the FMU reuse in different system contexts, as well as a parallel simulation execution onto multi-core machines. Furthermore, the paper proposes methods to optimize the allocation of components to cores and shows that the framework can simulate a medium voltage distributed electrical grid of about 20 components in real-time on a commodity multi-core machine.

关键词： Multicore processing Power system simulation Medium voltage Real-time systems Hardware Power systems Steady-state

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Consistent Lock-free parallel Stochastic Gradient Descent for Fast and Stable Convergence 35

Consistent Lock-free Parallel Stochastic Gradient Descent fo...

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35th ieee international parallel and distributed processing symposium (IPDPS)

作者： Backstrom, Karl Walulya, Ivan Papatriantafilou, Marina Tsigas, Philippas Chalmers Univ Technol Dept Comp Sci & Engn Gothenburg Sweden

ISBN: (纸本)9781665440660

Stochastic Gradient Descent (SGD) is an essential element in Machine Learning (ML) algorithms. Asynchronous shared-memory parallel SGD (AsyncSGD), including synchronization-free algorithms, e.g. HOGWILD!, have received interest in certain contexts, due to reduced overhead compared to synchronous parallelization. Despite that they induce staleness and inconsistency, they have shown speedup for problems satisfying smooth, strongly convex targets, and gradient sparsity. Recent works take important steps towards understanding the potential of parallel 50D for problems not conforming to these strong assumptions, in particular for deep learning (DL). there is however a gap in current literature in understanding when AsyncSGD algorithms are useful in practice, and in particular how mechanisms for synchronization and consistency play a role. We contribute with answering questions in this gap by studying a spectrum of parallel algorithmic implementations of AsyncSGD, aiming to understand how shared-data synchronization influences the convergence properties in fundamental DL applications. We focus on the impact of consistency-preserving non-blocking synchronization in SGD convergence, and in sensitivity to hyperparameter tuning. We propose Leashed-SGD, an extensible algorithmic framework of consistency-preserving implementations of AsyncSGD, employing lock-free synchronization, effectively balancing throughput and latency. Leashed-SGD features a natural contention-regulating mechanism, as well as dynamic memory management, allocating space only when needed. We argue analytically about the dynamics of the algorithms, memory consumption, the threads' progress over time, and the expected contention. We provide a comprehensive empirical evaluation, validating the analytical claims, benchmarking the proposed Leashed-SGD framework, and comparing to baselines for two prominent deep learning (DL) applications: multilayer perceptrons (MLP) and convolutional neural networks (CNN). We o

关键词： artificial neural networks parallel algorithms lock-free synchronization stochastic gradient descent

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Providing In-depth Performance Analysis for Heterogeneous Task-based applications with StarVZ

Providing In-depth Performance Analysis for Heterogeneous Ta...

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35th ieee international parallel and distributed processing symposium (IPDPS)

作者： Pinto, Vinicius Garcia Nesi, Lucas Leandro Miletto, Marcelo Cogo Schnorr, Lucas Mello Fed Univ Rio Grande do Sul UFRGS Inst Informat Porto Alegre RS Brazil

ISBN: (纸本)9781665435772

Task-based parallelism has adequately addressed the coding complexity required to fully exploit the processing power offered by omnipresent hybrid CPU/GPU supercomputers. However, its performance highly depends on the proper runtime system setup. Analyzing and tuning the performance of task-based applications running on hybrid platforms is challenging since they present unstructured communication and computation overlap, with finer granularity, dynamic scheduling, and inherent irregularity. this paper discusses the StarVZ approach to enable a comprehensive performance analysis in such a heterogeneous context. StarVZ is built on top of modern data analysis tools and is publicly available as an R package. We collect traces from five diverse task-based applications running on top of the StarPU runtime system on a set of multi-node platforms enhanced with GPUs. We demonstrate how it can highlight disturbances that are particularly hard to identify or explain with traditional analysis tools. Additionally, we provide a detailed performance evaluation of StarVZ with different workloads and setups.

关键词： task-based applications performance analysis trace visualization hybrid platforms CPU/GPU platforms

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Efficient and Eventually Consistent Collective Operations

Efficient and Eventually Consistent Collective Operations

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35th ieee international parallel and distributed processing symposium (IPDPS)

作者： Iakymchuk, Roman Faustino, Amandio Emerson, Andrew Barreto, Joao Bartsch, Valeria Rodrigues, Rodrigo Monteiro, Jose C. Fraunhofer ITWM D-67663 Kaiserslautern Germany Sorbonne Univ F-75252 Paris France INTESC ID P-1000029 Lisbon Portugal IST ULisboa P-1000029 Lisbon Portugal CINECA I-40033 Casalecchio Di Reno Italy

ISBN: (纸本)9781665435772

Collective operations are common features of parallel programming models that are frequently used in High-Performance (HPC) and machine/ deep learning (ML/ DL) applications. In strong scaling scenarios, collective operations can negatively impact the overall application performance: with the increase in core count, the load per rank decreases, while the time spent in collective operations increases logarithmically. In this article, we propose a design for eventually consistent collectives suitable for ML/ DL computations by reducing communication in Broadcast and Reduce, as well as by exploring the Stale Synchronous parallel (SSP) synchronization model for the Allreduce collective. Moreover, we also enrich the GASPI ecosystem with frequently used classic/ consistent collective operations - such as Allreduce for large messages and AlltoAll used in an HPC code. Our implementations show promising preliminary results with significant improvements, especially for Allreduce and AlltoAll, compared to the vendor-provided MPI alternatives.

关键词： Collectives Allreduce AlltoAll Stale Synchronous parallel GASPI

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Evaluating I/O Acceleration Mechanisms of SX-Aurora TSUBASA

Evaluating I/O Acceleration Mechanisms of SX-Aurora TSUBASA

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35th ieee international parallel and distributed processing symposium (IPDPS)

作者： Sasaki, Yuta Ishizuka, Ayumu Agung, Mulya Takizawa, Hiroyuki Tohoku Univ Grad Sch Informat Sci Sendai Miyagi Japan Tohoku Univ Cybersci Ctr Aoba Ku 6-3 Aramaki Aza Aoba Sendai Miyagi 9808578 Japan

ISBN: (纸本)9781665435772

In a heterogeneous computing system, different kinds of processors might need to be involved in the execution of a file I/O operation. Since NEC SX-Aurora TSUBASA is one such system, two I/O acceleration mechanisms are offered to reduce the data transfer overheads among the processors for a file I/O operation. this paper first investigates the effects of the two mechanisms on the I/O performance of SX-Aurora TSUBASA. Considering the results, proper use of the two mechanisms is discussed via a real-world application of flood damage estimation. these results clearly demonstrate the demand for auto-tuning, i.e., adaptively selecting either of the two mechanisms with considering application behaviors and system configuration.

关键词： Performance evaluation distributed processing Program processors File systems Conferences Estimation Data transfer

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P-FLEE: An Efficient parallel Algorithm for Simulating Human Migration

P-FLEE: An Efficient Parallel Algorithm for Simulating Human...

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35th ieee international parallel and distributed processing symposium (IPDPS)

作者： Anastasiadis, Petros Gogolenko, Sergiy Papadopoulou, Nikela Lawenda, Marcin Arabnejad, Hamid Jahani, Alireza Mahmood, Imran Groen, Derek Natl Tech Univ Athens Comp Syst Lab Athens Greece High Performance Comp Ctr Stuttgart Stuttgart Germany Poznan Supercomp & Networking Ctr Poznan Poland Brunel Univ London Dept Comp Sci Uxbridge Middx England

ISBN: (纸本)9781665435772

With over 79 million people forcibly displaced, forced human migration becomes a common issue in the modern world and a serious challenge for the global community. the Flee is a validated agent-based social simulation framework for forecasting the population displacements in the armed conflict settings. In this paper, we present two schemes to parallelize Flee, analyze computational complexity of those schemes, and outline results for benchmarks of our parallel codes with the real-world and synthetic scenarios on four state-of-the-art systems including a new European pre-exascale system, Hawk. On all testbeds, we evidenced high scalability of our codes. It exceeds more than 16,384 cores in our largest benchmark with 100 million agents on Hawk. parallelization schemes discussed in this work, can be extrapolated to a wide range of ABSS applications with frequent agent movement and lesser impact of direct communications between agents.

关键词： migration forcibly displaced people agent-based social simulation (ABSS) parallel and distributed agent-based systems (PDABS) high-performance computing (HPC)

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Performance Comparison for Scientific Computations on the Edge via Relative Performance

Performance Comparison for Scientific Computations on the Ed...

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35th ieee international parallel and distributed processing symposium (IPDPS)

作者： Sankaran, Aravind Bientinesi, Paolo Rhein Westfal TH Aachen IRTG Modern Inverse Problems Aachen Germany Umea Univ Dept Comp Sci Umea Sweden

ISBN: (纸本)9781665435772

In a typical Internet-of-things setting that involves scientific applications, a target computation can be evaluated in many different ways depending on the split of computations among various devices. On the one hand, different implementations (or algorithms)-equivalent from a mathematical perspective-might exhibit significant difference in terms of performance. On the other hand, some of the implementations are likely to show similar performance characteristics. In this paper, we focus on analysing the performance of a given set of algorithms by clustering them into performance classes. To this end, we use a measurement-based approach to evaluate and score algorithms based on pair-wise comparisons;we refer to this approach as "Relative performance analysis". Each comparison yields one of three outcomes: one algorithm can be "better", "worse", or "equivalent" to another;those algorithms evaluating to have "equivalent" performance are merged into the same performance class. We show that our clustering methodology facilitates algorithm selection with respect to more than one metric;for instance, from the subset of equivalently fast algorithms, one could then select an algorithm that consumes the least energy on a certain device.

关键词： performance analysis algorithm ranking clustering scientific computing distributed computing edge computing

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An Efficient Approach for Image Border Handling on GPUs via Iteration Space Partitioning

An Efficient Approach for Image Border Handling on GPUs via ...

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35th ieee international parallel and distributed processing symposium (IPDPS)

作者： Qiao, Bo Teich, Juergen Hannig, Frank Friedrich Alexander Univ Erlangen Nurnberg FAU Erlangen Germany

ISBN: (纸本)9781665435772

Border handling is a crucial step in many image processing applications. For stencil kernels such as the Gaussian filter where a window of pixels is required to compute an output pixel, the border of the image needs to be handled differently than the body of the image. To prevent out-of-bounds accesses, conditional statements need to be inserted into the pixel address calculation. this introduces significant overhead, especially on hardware accelerators such as GPUs. Existing research efforts mostly focus on image body computations, while neglecting the importance of border handling or treating it as a corner case. In this paper, we propose an efficient border handling approach for GPUs. Our approach is based on iteration space partitioning, which is a technique similar to index-set splitting, a well-known general-purpose compiler optimization. We present a detailed systematic analysis including an analytic model that quantitatively evaluates the benefits as well as the costs of the transformation. In addition, manually implementing the border handling technique is a tedious task and not portable at all. We integrate our approach into an image processing DSL and a source-to-source compiler called Hipacc to relieve the burden and increase programmers' productivity. We evaluate over five commonly used image processing applications on two Nvidia GPUs. Results show our proposed approach achieves a geometric mean speedup of up to 87% over a naive implementation.

关键词： Productivity Analytical models Systematics Program processors Image processing Predictive models Registers

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