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Parallelising multi-agent systems for high performance computing

Leitão, Paulo; Inden, Udo; Rückemann, Claus-Peter
Fonte: IARIA Publicador: IARIA
Tipo: Conferência ou Objeto de Conferência
ENG
Relevância na Pesquisa
95.88%
Multi-Agent Systems (MAS) are seen as a promising technology to face the current requirements of large-scale distributed and complex systems, e.g., autonomous traffic systems or risk management. The application of MAS to such large scale systems, characterised by millions of distributed nodes, imposes special demanding requirements in terms of fast computation. The paper discusses the parallelisation of MAS solutions using larger-scale distributed High End Computing platforms as well as High Performance Computing as a suitable approach to handle the complexity associated to collaborative solutions for large-scale systems.

Técnicas de programação e avaliação de desempenho de solvers de sistemas de equações lineares em sistemas computacionais de alto desempenho.; Programming techniques and performance evaluation of solvers of linear systems of equations in high performance computing.

Ferreira, Alexandre Beletti
Fonte: Biblioteca Digitais de Teses e Dissertações da USP Publicador: Biblioteca Digitais de Teses e Dissertações da USP
Tipo: Tese de Doutorado Formato: application/pdf
Publicado em 08/07/2013 PT
Relevância na Pesquisa
95.91%
Os problemas de engenharia atualmente têm aumentado a sua ordem de grandeza, por conta de diversos fatores. A modelagem em ambiente computacional dos mesmos esbarra em limitações, como grandes quantidades de tempo de processamento gastos com diversas simulações da modelagem e a pouca quantidade de memória disponível para alocar propriamente os problemas. A resolução de grandes sistemas de equações lineares, comumente abordado nos problemas atuais de engenharia, necessita da exploração das duas situações mencionadas anteriormente. A subárea computacional que permite explorar a redução do tempo e a possibilidade de alocação na memória de tais problemas é chamada de computação de alto desempenho. O objetivo deste trabalho é ilustrar o uso de softwares de resolução de sistemas de equações lineares, chamados de solvers, projetados para os ambientes computacionais de alto desempenho, testando-os e avaliando-os em um conjunto de matrizes conhecido, bem como abordar os detalhes computacionais envolvidos em tais procedimentos.; Engineering problems today have increased their order of magnitude, due to several factors. Modeling these problems with computers brings up certain limitations, as the amount of processing time needed for several simulations and the lack of available memory to properly allocate them. The resolution of large systems of linear equations...

Viability and performance of high-performance computing in the cloud; Viabilidade e desempenho de processamento de alto desempenho na nuvem

Roloff, Eduardo
Fonte: Universidade Federal do Rio Grande do Sul Publicador: Universidade Federal do Rio Grande do Sul
Tipo: Dissertação Formato: application/pdf
ENG
Relevância na Pesquisa
95.99%
Cloud computing is a new paradigm, where computational resources are offered as services. In this context, the user does not need to buy infrastructure, the resources can be rented from a provider and used for a period of time. Furthermore the user can easily allocate as many resources as needed, and deallocate them as well, in a totally elastic environment. The resources need to be paid only for the effective usage time. On the other hand, High-Performance Computing (HPC) requires a large amount of computational power. To acquire systems capable for HPC, large financial investments are necessary. Apart from the initial investment, the user must pay the maintenance costs, and has only limited computational resources. To overcome these issues, this thesis aims to evaluate the cloud computing paradigm as a candidate environment for HPC. We analyze the efforts and challenges for porting and deploy HPC applications to the cloud. We evaluate if this computing model can provide sufficient capacities for running HPC applications, and compare its cost efficiency to traditional HPC systems, such as clusters. The cloud computing paradigm was analyzed to identify which models have the potential to be used for HPC purposes. The identified models were then evaluated using major cloud providers...

X10 for high-performance scientific computing

Milthorpe, Joshua John
Fonte: Universidade Nacional da Austrália Publicador: Universidade Nacional da Austrália
Tipo: Thesis (PhD)
EN
Relevância na Pesquisa
75.96%
High performance computing is a key technology that enables large-scale physical simulation in modern science. While great advances have been made in methods and algorithms for scientific computing, the most commonly used programming models encourage a fragmented view of computation that maps poorly to the underlying computer architecture. Scientific applications typically manifest physical locality, which means that interactions between entities or events that are nearby in space or time are stronger than more distant interactions. Linear-scaling methods exploit physical locality by approximating distant interactions, to reduce computational complexity so that cost is proportional to system size. In these methods, the computation required for each portion of the system is different depending on that portion’s contribution to the overall result. To support productive development, application programmers need programming models that cleanly map aspects of the physical system being simulated to the underlying computer architecture while also supporting the irregular workloads that arise from the fragmentation of a physical system. X10 is a new programming language for high-performance computing that uses the asynchronous partitioned global address space (APGAS) model...

Communication performance measurement and analysis on commodity clusters.

Abdul Hamid, Nor Asilah Wati
Fonte: Universidade de Adelaide Publicador: Universidade de Adelaide
Tipo: Tese de Doutorado
Publicado em //2008
Relevância na Pesquisa
75.86%
Cluster computers have become the dominant architecture in high-performance computing. Parallel programs on these computers are mostly written using the Message Passing Interface (MPI) standard, so the communication performance of the MPI library for a cluster is very important. This thesis investigates several different aspects of performance analysis for MPI libraries, on both distributed memory clusters and shared memory parallel computers. The performance evaluation was done using MPIBench, a new MPI benchmark program that provides some useful new functionality compared to existing MPI benchmarks. Since there has been only limited previous use of MPIBench, some initial work was done on comparing MPIBench with other MPI benchmarks, and improving its functionality, reliability, portability and ease of use. This work included a detailed comparison of results from the Pallas MPI Benchmark (PMB), SKaMPI, Mpptest, MPBench and MPIBench on both distributed memory and shared memory parallel computers, which has not previously been done. This comparison showed that the results for some MPI routines were significantly different between the different benchmarks, particularly for the shared memory machine. A comparison was done between Myrinet and Ethernet network performance on the same machine...

Design of efficient Java communications for high performance computing

López Taboada, Guillermo
Fonte: Universidade da Corunha Publicador: Universidade da Corunha
Tipo: Tese de Doutorado
ENG
Relevância na Pesquisa
95.94%
[Abstract] There is an increasing interest to adopt Java as the parallel programming language for the multi-core era. Although Java offers important advantages, such as built-in multithreading and networking support, productivity and portability, the lack of efficient communication middleware is an important drawback for its uptake in High Performance Computing (HPC). This PhD Thesis presents the design, implementation and evaluation of several solutions to improve this situation: (1) a high performance Java sockets implementation (JFS, Java Fast Sockets) on high-speed networks (e.g., Myrinet, InfiniBand) and shared memory (e.g., multi-core) machines; (2) a low-level messaging device, iodev, which efficiently overlaps communication and computation; and (3) a more scalable Java message-passing library, Fast MPJ (F-MPJ). Furthermore, new Java parallel benchmarks have been implemented and used for the performance evaluation of the developed middleware. The final and main conclusion is that the use of Java for HPC is feasible and even advisable when looking for productive development, provided that efficient communication middleware is made available, such as the projects presented in this Thesis.; [Resumen] La tesis doctoral "Design of Efficient Java Communications for High Performance Computing" parte de la hipótesis inicial de que es posible desarrollar aplicaciones Java en computación de altas prestaciones...

Performance Optimization for the Trinity RNA-Seq Assembler

Wagner, Michael; Fulton, Ben; Henschel, Robert
Fonte: Springer Publicador: Springer
Tipo: Relatório
EN_US
Relevância na Pesquisa
75.87%
Presented at 9th Parallel Tools Workshop, September 2-3, 2015 in Dresden, Germany; Utilizing the enormous computing resources of high performance computing systems is anything but a trivial task. Performance analysis tools are designed to assist developers in this challenging task by helping to understand the application behavior and identify critical performance issues. In this paper we share our efforts and experiences in analyzing and optimizing Trinity, a well-established framework for the de novo reconstruction of transcriptomes from RNA-seq reads. Thereby, we try to reflect all aspects of the ongoing performance engineering: the identification of optimization targets, the code improvements resulting in 20% overall runtime reduction, as well as the challenges we encountered getting there.

Performance Optimization for the Trinity RNA-Seq Assembler (Presentation)

Wagner, Michael; Fulton, Ben; Henschel, Robert
Fonte: Universidade de Indiana Publicador: Universidade de Indiana
Tipo: Conferência ou Objeto de Conferência
EN_US
Relevância na Pesquisa
75.87%
Presented at 9th Parallel Tools Workshop, September 2-3, 2015 in Dresden, Germany; Utilizing the enormous computing resources of high performance computing systems is anything but a trivial task. Performance analysis tools are designed to assist developers in this challenging task by helping to understand the application behavior and identify critical performance issues. In this paper we share our efforts and experiences in analyzing and optimizing Trinity, a well-established framework for the de novo reconstruction of transcriptomes from RNA-seq reads. Thereby, we try to reflect all aspects of the ongoing performance engineering: the identification of optimization targets, the code improvements resulting in 20 % overall runtime reduction, as well as the challenges we encountered getting there.

High-Performance Computing in Geoscience - Data Preprocessing by Domain Decomposition and Load Balancing; High-Performance Computing in den Geowissenschaften - Datenvorverarbeitung mittels Gebietszerlegung und Lastbalancierung

Kemmler, Dany
Fonte: Universität Tübingen Publicador: Universität Tübingen
Tipo: Dissertation; info:eu-repo/semantics/doctoralThesis
EN
Relevância na Pesquisa
95.92%
The popularity and availability of computers is a simple fact of life in most of today's world. Computer simulation is a quick and relatively inexpensive alternative to physical experimentation in the scientific realm. Computer operations are meanwhile performed increasingly rapidly; one trillion operations per second are not anything extraordinary these days and are necessary in the field of automotive engineering, weather forecast or applied geology, for example. An interdependency of speed, power and storage space means that if one of these attributes is insufficient or impaired, it will limit the efficacy of the others. Data preprocessing and problem subdivision play a vital role in making real-world problems "computable." High-performance computing is not only a cornerstone of modern life, but also a compelling topic in itself. The task of descretizing real-world problems and processing models so that these problems can be solved by computers involves obtaining finite amounts of data from real-world problem domains and replacing them by grids consisting of inter-connected nodes and elements which will serve to model the problem in question on a computer. Altering the size of the grid, its number of nodes, etc. to determine the optimal structure to simulate a certain problem on a computer is the ultimate goal here. The more carefully discretization is accomplished...

IMPROVING MESSAGE-PASSING PERFORMANCE AND SCALABILITY IN HIGH-PERFORMANCE CLUSTERS

RASHTI, Mohammad Javad
Fonte: Quens University Publicador: Quens University
Tipo: Tese de Doutorado
EN; EN
Relevância na Pesquisa
85.84%
High Performance Computing (HPC) is the key to solving many scientific, financial, and engineering problems. Computer clusters are now the dominant architecture for HPC. The scale of clusters, both in terms of processor per node and the number of nodes, is increasing rapidly, reaching petascales these days and soon to exascales. Inter-process communication plays a significant role in the overall performance of HPC applications. With the continuous enhancements in interconnection technologies and node architectures, the Message Passing Interface (MPI) needs to be improved to effectively utilize the modern technologies for higher performance. After providing a background, I present a deep analysis of the user level and MPI libraries over modern cluster interconnects: InfiniBand, iWARP Ethernet, and Myrinet. Using novel techniques, I assess characteristics such as overlap and communication progress ability, buffer reuse effect on latency, and multiple-connection scalability. The outcome highlights some of the inefficiencies that exist in the communication libraries. To improve communication progress and overlap in large message transfers, a method is proposed which uses speculative communication to overlap communication with computation in the MPI Rendezvous protocol. The results show up to 100% communication progress and more than 80% overlap ability over iWARP Ethernet. An adaptation mechanism is employed to avoid overhead on applications that do not benefit from the method due to their timing specifications. To reduce MPI communication latency...

Improving High Performance Networking Technologies for Data Center Clusters

Grant, RYAN
Fonte: Quens University Publicador: Quens University
Tipo: Tese de Doutorado
EN; EN
Relevância na Pesquisa
75.95%
This dissertation demonstrates new methods for increasing the performance and scalability of high performance networking technologies for use in clustered computing systems, concentrating on Ethernet/High-Speed networking convergence. The motivation behind the improvement of high performance networking technologies and their importance to the viability of modern data centers is discussed first. It then introduces the concepts of high performance networking in a commercial data center context as well as high performance computing (HPC) and describes some of the most important challenges facing such networks in the future. It reviews current relevant literature and discusses problems that are not yet solved. Through a study of existing high performance networks, the most promising features for future networks are identified. Sockets Direct Protocol (SDP) is shown to have unexpected performance issues for commercial applications, due to inefficiencies in handling large numbers of simultaneous connections. The first SDP over eXtended Reliable Connections implementation is developed to reduce connection management overhead, demonstrating that performance issues are related to protocol overhead at the SDP level. Datagram offloading for IP over InfiniBand (IPoIB) is found to work well. In the first work of its kind...

A review of High Performance Computing foundations for scientists

García-Risueño, Pablo; Ibáñez, Pablo E.
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 23/05/2012
Relevância na Pesquisa
75.85%
The increase of existing computational capabilities has made simulation emerge as a third discipline of Science, lying midway between experimental and purely theoretical branches [1, 2]. Simulation enables the evaluation of quantities which otherwise would not be accessible, helps to improve experiments and provides new insights on systems which are analysed [3-6]. Knowing the fundamentals of computation can be very useful for scientists, for it can help them to improve the performance of their theoretical models and simulations. This review includes some technical essentials that can be useful to this end, and it is devised as a complement for researchers whose education is focused on scientific issues and not on technological respects. In this document we attempt to discuss the fundamentals of High Performance Computing (HPC) [7] in a way which is easy to understand without much previous background. We sketch the way standard computers and supercomputers work, as well as discuss distributed computing and discuss essential aspects to take into account when running scientific calculations in computers.; Comment: 33 pages

Energy Efficient Algorithms and Power Consumption Techniques in High Performance Computing

Chalotra, Vivek; Bhasin, Anju; Gupta, Anik; Sambyal, Sanjeev Singh; Mahajan, Sanjay
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 30/10/2012
Relevância na Pesquisa
75.95%
High Performance Computing is an internet based computing which makes computer infrastructure and services available to the user for research purpose. However, an important issue which needs to be resolved before High Performance Computing Cluster with large pool of servers gain widespread acceptance is the design of data centers with less energy consumption. It is only possible when servers produce less heat and consume less power. Systems reliability decreases with increase in temperature due to heat generation caused by large power consumption as computing in high temperature is more error-prone. Here in this paper our approach is to design and implement a high performance cluster for high-end research in the High Energy Physics stream. This involves the usage of fine grained power gating technique in microprocessors and energy efficient algorithms that reduce the overall running cost of the data center.; Comment: 5 pages, 4 figures & Presented at 8th JKSC,Srinagar, J&K, India

Efficient HTTP based I/O on very large datasets for high performance computing with the libdavix library

Devresse, Adrien; Furano, Fabrizio
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 15/10/2014
Relevância na Pesquisa
75.97%
Remote data access for data analysis in high performance computing is commonly done with specialized data access protocols and storage systems. These protocols are highly optimized for high throughput on very large datasets, multi-streams, high availability, low latency and efficient parallel I/O. The purpose of this paper is to describe how we have adapted a generic protocol, the Hyper Text Transport Protocol (HTTP) to make it a competitive alternative for high performance I/O and data analysis applications in a global computing grid: the Worldwide LHC Computing Grid. In this work, we first analyze the design differences between the HTTP protocol and the most common high performance I/O protocols, pointing out the main performance weaknesses of HTTP. Then, we describe in detail how we solved these issues. Our solutions have been implemented in a toolkit called davix, available through several recent Linux distributions. Finally, we describe the results of our benchmarks where we compare the performance of davix against a HPC specific protocol for a data analysis use case.; Comment: Presented at: Very large Data Bases (VLDB) 2014, Hangzhou

A Holistic Approach to Log Data Analysis in High-Performance Computing Systems: The Case of IBM Blue Gene/Q

Sîrbu, Alina; Babaoglu, Ozalp
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
75.81%
The complexity and cost of managing high-performance computing infrastructures are on the rise. Automating management and repair through predictive models to minimize human interventions is an attempt to increase system availability and contain these costs. Building predictive models that are accurate enough to be useful in automatic management cannot be based on restricted log data from subsystems but requires a holistic approach to data analysis from disparate sources. Here we provide a detailed multi-scale characterization study based on four datasets reporting power consumption, temperature, workload, and hardware/software events for an IBM Blue Gene/Q installation. We show that the system runs a rich parallel workload, with low correlation among its components in terms of temperature and power, but higher correlation in terms of events. As expected, power and temperature correlate strongly, while events display negative correlations with load and power. Power and workload show moderate correlations, and only at the scale of components. The aim of the study is a systematic, integrated characterization of the computing infrastructure and discovery of correlation sources and levels to serve as basis for future predictive modeling efforts.; Comment: 12 pages...

EPOBF: Energy Efficient Allocation of Virtual Machines in High Performance Computing Cloud

Quang-Hung, Nguyen; Thoai, Nam; Son, Nguyen Thanh
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
75.95%
Cloud computing has become more popular in provision of computing resources under virtual machine (VM) abstraction for high performance computing (HPC) users to run their applications. A HPC cloud is such cloud computing environment. One of challenges of energy efficient resource allocation for VMs in HPC cloud is tradeoff between minimizing total energy consumption of physical machines (PMs) and satisfying Quality of Service (e.g. performance). On one hand, cloud providers want to maximize their profit by reducing the power cost (e.g. using the smallest number of running PMs). On the other hand, cloud customers (users) want highest performance for their applications. In this paper, we focus on the scenario that scheduler does not know global information about user jobs and user applications in the future. Users will request shortterm resources at fixed start times and non interrupted durations. We then propose a new allocation heuristic (named Energy-aware and Performance per watt oriented Bestfit (EPOBF)) that uses metric of performance per watt to choose which most energy-efficient PM for mapping each VM (e.g. maximum of MIPS per Watt). Using information from Feitelson's Parallel Workload Archive to model HPC jobs, we compare the proposed EPOBF to state of the art heuristics on heterogeneous PMs (each PM has multicore CPU). Simulations show that the EPOBF can reduce significant total energy consumption in comparison with state of the art allocation heuristics.; Comment: 10 pages...

Efficient Resource Sharing Through GPU Virtualization on Accelerated High Performance Computing Systems

Li, Teng; Narayana, Vikram K.; El-Ghazawi, Tarek
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 24/11/2015
Relevância na Pesquisa
75.85%
The High Performance Computing (HPC) field is witnessing a widespread adoption of Graphics Processing Units (GPUs) as co-processors for conventional homogeneous clusters. The adoption of prevalent Single- Program Multiple-Data (SPMD) programming paradigm for GPU-based parallel processing brings in the challenge of resource underutilization, with the asymmetrical processor/co-processor distribution. In other words, under SPMD, balanced CPU/GPU distribution is required to ensure full resource utilization. In this paper, we propose a GPU resource virtualization approach to allow underutilized microprocessors to effi- ciently share the GPUs. We propose an efficient GPU sharing scenario achieved through GPU virtualization and analyze the performance potentials through execution models. We further present the implementation details of the virtualization infrastructure, followed by the experimental analyses. The results demonstrate considerable performance gains with GPU virtualization. Furthermore, the proposed solution enables full utilization of asymmetrical resources, through efficient GPU sharing among microprocessors, while incurring low overhead due to the added virtualization layer.; Comment: 21 pages

Optimizing performance per watt on GPUs in High Performance Computing: temperature, frequency and voltage effects

Price, D. C.; Clark, M. A.; Barsdell, B. R.; Babich, R.; Greenhill, L. J.
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
75.92%
The magnitude of the real-time digital signal processing challenge attached to large radio astronomical antenna arrays motivates use of high performance computing (HPC) systems. The need for high power efficiency (performance per watt) at remote observatory sites parallels that in HPC broadly, where efficiency is an emerging critical metric. We investigate how the performance per watt of graphics processing units (GPUs) is affected by temperature, core clock frequency and voltage. Our results highlight how the underlying physical processes that govern transistor operation affect power efficiency. In particular, we show experimentally that GPU power consumption grows non-linearly with both temperature and supply voltage, as predicted by physical transistor models. We show lowering GPU supply voltage and increasing clock frequency while maintaining a low die temperature increases the power efficiency of an NVIDIA K20 GPU by up to 37-48% over default settings when running xGPU, a compute-bound code used in radio astronomy. We discuss how temperature-aware power models could be used to reduce power consumption for future HPC installations. Automatic temperature-aware and application-dependent voltage and frequency scaling (T-DVFS and A-DVFS) may provide a mechanism to achieve better power efficiency for a wider range of codes running on GPUs; Comment: In Computer Science - Research and Development special issue on Energy-Aware High-Performance Computing. The final publication is available at Springer via http://dx.doi.org/10.1007/s00450-015-0300-5

Comprehensive analysis of high-performance computing methods for filtered back-projection

Mendl, Christian B.; Eliuk, Steven; Noga, Michelle; Boulanger, Pierre
Fonte: Universidade Autônoma de Barcelona Publicador: Universidade Autônoma de Barcelona
Tipo: Artigo de Revista Científica Formato: application/pdf
Publicado em //2013 ENG
Relevância na Pesquisa
75.82%
This paper provides an extensive runtime, accuracy, and noise analysis of Computed To-mography (CT) reconstruction algorithms using various High-Performance Computing (HPC) frameworks such as: “conventional” multi-core, multi threaded CPUs, Compute Unified Device Architecture (CUDA), and DirectX or OpenGL graphics pipeline programming. The proposed algorithms exploit various built-in hardwired features of GPUs such as rasterization and texture filtering. We compare implementations of the Filtered Back-Projection (FBP) algorithm with fan-beam geometry for all frameworks. The accuracy of the reconstruction is validated using an ACR-accredited phantom, with the raw attenuation data acquired by a clinical CT scanner. Our analysis shows that a single GPU can run a FBP reconstruction 23 time faster than a 64-core multi-threaded CPU machine for an image of 1024 X 1024. Moreover, directly programming the graphics pipeline using DirectX or OpenGL can further increases the performance compared to a CUDA implementation.

Introducing Design Patterns, Graphical User Interfaces and Threads Within the Context of a High Performance Computing Application

Roper, James; Rendell, Alistair
Fonte: Springer Publicador: Springer
Tipo: Conference paper
Relevância na Pesquisa
95.87%
The cross fertilization of methods and techniques between different subject areas in the undergraduate curriculum is a challenge, especially at the more advanced levels. This paper describes an attempt to achieve this through a tutorial based around a traditional high performance computing application, namely molecular dynamics. The tutorial exposes students to elements of software design patterns, the construction of graphical user interfaces, and concurrent programming concepts. The tutorial targets senior undergraduate or early postgraduate students and is relevant to both those majoring in computing as well as other science disciplines.