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parallel AI Planning on the SCC 4

Parallel AI Planning on the SCC

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4th Many-Core Applications Research Community Symposium, MARC 2011

作者： Vidal, Vincent Vernhes, Simon Guillaume Infantes France

ISBN: (纸本)9783869561691

We present in this paper a parallelized version of an existing Artificial Intelligence automated planner, implemented with standard programming models and tools (hybrid OpenMP/MPI). We then evaluate this planner with respect to its sequential version through extensive experiments over a wide range of academic benchmarks, on two different target architectures: a small standard cluster and the research processor SCC ("Single-chip Cloud Computer") developed by Intel Labs and made available to the research community through the MARC program ("Many-core Applications Research Community"). We obtain interesting speedups (super-linear in some cases) on both architectures. Interestingly enough, these experiments also reveal different behaviors between the cluster and the SCC. © 2012 Universitatsverlag Potsdam. All rights reserved.

关键词： Application programs

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A low-cost bidimensional smart pixel network for video coding operations

A low-cost bidimensional smart pixel network for video codin...

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conference on VLSI Circuits and Systems II

作者： López, S Callicó, GM López, JF Sarmiento, R ULPGC Res Inst Appl Microelect IUMA Dept Elect Engn & ControlDIEA Las Palmas Gran Canaria Spain

ISBN: (纸本)0819458325

Optimum visual and hearing qualities at high compression ratios as well as reduced area/power dissipation are key factors for actual and future commercial mobile multimedia devices. In this sense, a real time Smart Pixels Array designed to perform efficiently key video coding operations is presented in this paper. In particular, the array introduced is capable to perform the Discrete Wavelet Transform (DWT), Zerotree Entropy (ZTE) Coding and Frame Differencing (FD) over SQCIF images (128x96 pixels) by dividing them into wavelet blocks (84 pixels). In order to perform these tasks, the array has been designed as a bidimensional network of interconnected smart pixel processors working in a massively parallel fashion, allowing the operation at very low clock frequencies and hence, low power dissipation. Each of these smart pixels is composed by a photodetector, an analog-digital converter in order to obtain a digital representation of the light intensity received by the photodetector and a Ferroelectric Liquid Crystal placed over the whole surface of the pixel to display the image. Additionally, each pixel has a dedicated circuitry associated which performs all the specific computations related with the three video coding operations previously mentioned, exhibiting a power dissipation of 4.15 mu W@128 kHz and a square area of 110x110 mu m(2) using a 0.25 mu m CMOS technology. The array has been integrated into a mobile multimedia device prototype, fully designed at our research centre, capable to send and receive compressed audio and video information with a total power consumption of 1.36 W in an area of 351.5 mm2.

关键词： Discrete wavelet transforms Image processing Multimedia Video coding Prototyping Wavelets Computer programming Control systems Photodetectors Video compression

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20th Annual German conference on Artificial Intelligence, KI 1996

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20th Annual German conference on Artificial Intelligence, KI 1996

ISBN: (纸本)3540617086

The proceedings contain 39 papers. The special focus in this conference is on Advances in Artificial Intelligence. The topics include: Rational models of normal logic programs;massively parallel reasoning about actions;a disjunctive logic programming system based on protein theorem prover;abstraction as a heuristic to guide planning;equational theorem proving using taxonomic constraints;planning for distributed theorem proving;a revision of dependency-directed backtracking for JTMS;a compiler-interpreter-system for decoding the user's intention with in a speech understanding application;cyclic rules in linear connection proofs;optimized nearest-neighbor classifiers using generated instances;towards a totally distributed meeting scheduling system;representations as basis of cognitive processes;improving the functionality of a text-to-speech system by adding morphological knowledge;solving hard combinatorial problems with GSAT;using rippling for equational reasoning;reasoning about action and change;defeasible observations and actions with abnormal effects;integration of prosodic and grammatical information in the analysis of dialogs;application of a genetic algorithm for plausible justification of observations;managing multiple contexts efficiently;inductive learning in symbolic domains using structure-driven recurrent neural networks;avoiding combinatorial explosion in automatic test generation;reasoning about measurements is the key;putting default logics in perspective;a prototypical knowledge-based decision support system for the performance of office tasks;probabilistic knowledge representation and reasoning at maximum entropy by spirit;knowledge based image understanding by iterative optimization and knowledge organization using the development system FAENSY.

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A One-Layer Neural Network for Robust Mean-Variance Portfolio Selection Problem 14

A One-Layer Neural Network for Robust Mean-Variance Portfoli...

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14th International conference on Information Science and Technology, ICIST 2024

作者： Zhou, Keying Hu, Jin School of Mathematics and Statistics Chongqing Jiaotong University Chongqing China

ISBN: (纸本)9798350353334

Driven by globalization and technological innovation, the financial markets have experienced unprecedented volatility and uncertainty. Portfolio selection is a fundamental strategy in finance. During recent decades, the frequent occurrence of extreme market events and uncertainties has exposed significant limitations in the traditional mean-variance model, emphasizing the critical need for more robust approaches. In response to these challenges, this paper introduces a neurodynamic approach to robust portfolio selection. This approach is capable of efficiently handling high-dimensional data through massively parallel processing, providing a resilient solution to the complexities of modern financial markets. First, the corresponding robust counterpart model is derived by eliminating uncertainty from the robust portfolio selection model under the box uncertainty set. Consequently, the robust portfolio selection problem is transformed into a solvable quadratic programming problem. Next, a one-layer neural network model is constructed based on the Karush-Kuhn-Tucker (KKT) conditions. Subsequently, the stability and convergence of the proposed neural network are analyzed. Finally, simulation experiments are conducted using two global stock market datasets. The proposed neural network model demonstrates convergence even with large-scale data in the second dataset, highlighting the effectiveness of the neurodynamic approach in addressing robust portfolio selection problems. © 2024 IEEE.

关键词： Neural network models

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Performance Evaluation of Heterogeneous GPU programming Frameworks for Hemodynamic Simulations

Performance Evaluation of Heterogeneous GPU Programming Fram...

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2023 International conference on High Performance Computing, Network, Storage, and Analysis, SC Workshops 2023

作者： Martin, Aristotle Liu, Geng Ladd, William Lee, Seyong Gounley, John Vetter, Jeffrey Patel, Saumil Rizzi, Silvio Mateevitsi, Victor Insley, Joseph Randles, Amanda Biomedical Engineering Duke University DurhamNC United States Leadership Computing Facility Argonne National Laboratory LemontIL United States Computer Science and Mathematics Oak Ridge National Laboratory Oak RidgeTN United States Computational Sciences and Engineering Oak Ridge National Laboratory Oak RidgeTN United States

ISBN: (纸本)9798400707858

Preparing for the deployment of large scientific and engineering codes on upcoming exascale systems with GPU-dense nodes is made challenging by the unprecedented diversity of device architectures and heterogeneous programming models. In this work, we evaluate the process of porting a massively parallel, fluid dynamics code written in CUDA to SYCL, HIP, and Kokkos with a range of backends, using a combination of automated tools and manual tuning. We use a proxy application along with a custom performance model to inform the results and identify additional optimization strategies. At scale performance of the programming model implementations are evaluated on pre-production GPU node architectures for Frontier and Aurora, as well as on current NVIDIA device-based systems Summit and Polaris. Real-world workloads representing 3D blood flow calculations in complex vasculature are assessed. Our analysis highlights critical trade-offs between code performance, portability, and development time. © 2023 ACM.

关键词： Graphics processing unit

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parallelization of Virtual Screening in Drug Discovery on massively parallel Architectures

Parallelization of Virtual Screening in Drug Discovery on Ma...

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Euromicro conference on parallel, Distributed and Network-Based Processing

作者： Gines D. Guerrero Horacio E. Perez-S´nchez Jose M. Cecilia Jose M. Garcia Grupo de Arquitectura y Computación Paralela Dpto. de Ingeniería y Tecnología de Computadores Universidad de Murcia Campus de Espinardo Murcia Spain

The current trend in medical research for the discovery of new drugs is the use of Virtual Screening (VS) methods. In these methods, the calculation of the non-bonded interactions, such as electrostatics or van der Waals forces, plays an important role, representing up to 80% of the total execution time. These kernels are computational intensive and massively parallel in nature, and thus they are well suited to be accelerated on parallel architectures. In this work, we discuss the effective parallelization of the non-bonded electrostatic interactions kernel for VS on three different parallel architectures: a shared memory system, a distributed memory system, and a Graphics Processing Units (GPUs). For an efficient handling of the computational intensive and massively parallelism of this kernel, we enable different data policies on those architectures to take advantage of all computational resources offered by them. Four implementations are provided based on MPI, OpenMP, Hybrid MPI Open MP and CUDA programming models. The sequential implementation is defeated by a wide margin by all parallel implementations, obtaining up to 72x speed-up factor on the shared memory system through OpenMP, up to 60x and229x speed-ups factors on the distributed memory system for the MPI implementation and the Hybrid MPI-Open MP implementation respectively, and finally, up to 213x speedup factor for the CUDA implementation on the GPU architecture to offer the best alternative in terms of performance/cost ratio.

关键词： Graphics processing unit Kernel Instruction sets Message systems parallel processing programming Computer architecture

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Speeding Up Distributed MapReduce Applications Using Hardware Accelerators

Speeding Up Distributed MapReduce Applications Using Hardwar...

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International conference on parallel Processing (ICPP)

作者： Yolanda Becerra Vicenç Beltran David Carrera Marc Gonzalez Jordi Torres Eduard Ayguade Barcelona Supercomputing Center (BSC) Technical University of Catalonia Barcelona Spain

In an attempt to increase the performance/cost ratio, large compute clusters are becoming heterogeneous at multiple levels: from asymmetric processors, to different system architectures, operating systems and networks. Exploiting the intrinsic multi-level parallelism present in such a complex execution environment has become a challenging task using traditional parallel and distributed programming models. As a result, an increasing need for novel approaches to exploiting parallelism has arisen in these environments. MapReduce is a data-driven programming model originally proposed by Google back in 2004 as a flexible alternative to the existing models, specially devoted to hiding the complexity of both developing and running massively distributed applications in large compute clusters. In some recent works, the MapReduce model has been also used to exploit parallelism in other non-distributed environments, such as multi-cores, heterogeneous processors and GPUs. In this paper we introduce a novel approach for exploiting the heterogeneity of a Cell BE cluster linking an existing MapReduce runtime implementation for distributed clusters and one runtime to exploit the parallelism of the Cell BE nodes. The novel contribution of this work is the design and evaluation of a MapReduce execution environment that effectively exploits the parallelism existing at both the Cell BE cluster level and the heterogeneous processors level.

关键词： Hardware Acceleration parallel processing Runtime Costs Computer networks Computer architecture Operating systems parallel programming Computer applications

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MasPaWS-a massively parallel War Simulator

MasPaWS-a Massively Parallel War Simulator

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Simulation Winter conference

作者： N. Chandrasekharan Zhi-Hai Ma U.B. Vemulapati W.J. Porthouse A.T. Irwin Department of Mathematical Sciences Loyola University of Chicago Chicago IL USA Department of Computer Science University of Central Florida Orlando FL USA Technology Parkway SAIC Orlando FL USA

Describes the design, implementation and performance of a battlefield simulator for massively parallel SIMD machines. MasPaWS (massively parallel War Simulator) is a first-generation prototype that simulates the battle dynamics of a 2D theater to the level of individual tanks in a battlefield having certain terrain features. Objects in the battlefield are the terrain features and tanks. The battle cycles through a set of protocols: perception and combat, update combat, migration, and update migration. MasPaWS, written in the MasPar programming Language (MPL), has been implemented on a MasPar machine. The salient features of MasPaWS include: (1) use of simple protocols to match the machine architecture, (2) parametrization of several quantities to control the computation of and communication between MasPar processors and to estimate performance, and (3) interactive user input for terrain specification and generation, and other key parameters. Our work appears to be the first of its kind in war simulation on a massively parallel SIMD machine, using thousands of processors. Our results indicate that MasPaWS is both data- and architecture-scalable for battlefield simulation, while achieving high efficiency at the same time.

关键词： Computational modeling Military computing Computer simulation Concurrent computing Analytical models Protocols Discrete event simulation Load management Lakes Computer science

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Load balancing hybrid programming models for SMP clusters and fully permutable loops

Load balancing hybrid programming models for SMP clusters an...

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International conference on parallel Processing Workshops (ICPPW)

作者： N. Drosinos N. Koziris School of Electrical and Computer Engineering Computing Systems Laboratory National and Technical University of Athens Greece

This paper emphasizes on load balancing issues associated with hybrid programming models for the parallelization of fully permutable nested loops onto SMP clusters. Hybrid parallel programming models usually suffer from intrinsic load imbalance between threads, mainly because most existing message passing libraries generally provide limited multi-threading support, allowing only the master thread to perform internode message passing communication. In order to mitigate this effect, the authors proposed a generic method for the application of static load balancing on the coarse-grain hybrid model for the appropriate distribution of the computational load to the working threads. The efficiency of the proposed scheme was experimentally evaluated against a micro-kernel benchmark, and demonstrated the potential of such load balancing schemes for the extraction of maximum performance out of hybrid parallel programs.

关键词： Load management parallel programming Message passing Yarn Concurrent computing Libraries Distributed computing Computer architecture Tiles Systems engineering and theory

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massively parallel landscape-evolution modelling using general purpose graphical processing units

Massively parallel landscape-evolution modelling using gener...

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International conference on High Performance Computing

作者： A. S. McGough S. Liang M. Rapoportas R. Grey G. Kumar Vinod D. Maddy A. Trueman J. Wainwright School of Computing Science Newcastle University Newcastle upon Tyne UK School of Geography Politics and Sociology Newcastle University Newcastle upon Tyne UK Department of Geography Durham University Durham UK

As our expectations of what computer systems can do and our ability to capture data improves, the desire to perform ever more computationally intensive tasks increases. Often these tasks, comprising vast numbers of repeated computations, are highly interdependent on each other - a closely coupled problem. The process of Landscape-Evolution Modelling is an example of such a problem. In order to produce realistic models it is necessary to process landscapes containing millions of data points over time periods extending up to millions of years. This leads to non-tractable execution times, often in the order of years. Researchers therefore seek multiple orders of magnitude reduction in the execution time of these models. The massively parallel programming environment offered through General Purpose Graphical Processing Units offers the potential for multiple orders of magnitude speedup in code execution times. In this paper we demonstrate how the time dominant parts of a Landscape- Evolution Model can be recoded for a massively parallel architecture providing two orders of magnitude reduction in execution time.

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