Evaluation of messaging middleware for high-performance cloud computing

Expósito, Roberto R.; Taboada, Guillermo L.; Ramos, Sabela; Touriño, Juan; Doallo, Ramón

doi:10.1007/s00779-012-0605-3

Cited by 7 publications

(3 citation statements)

References 20 publications

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“…In this paper, we consider Amazon EC2 cloud and use CGI heterogeneous instances, which consist of a dual-socket CPU host and two GPUs, and connected over 10 Gbps Ethernet with latency 60 μs [21]. The CPU host has two Intel Nehalem x5570 multicore processors coupled via QPI links with speed of 25.6 GB/s.…”

Section: Hardware Architecture Modelmentioning

confidence: 99%

Parallel circuit simulation using the direct method on a heterogeneous cloud

Helal

Bayoumi

Hanafy

2015

Proceedings of the 52nd Annual Design Automation Conference

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This paper discusses the development of a parallel SPICE circuit simulator using the direct method on a cloud-based heterogeneous cluster, which includes multiple HPC compute nodes with multi-sockets, multicores, and GPUs. A simple model is derived to optimally partition the circuit between the compute nodes. The parallel simulator is divided into four major kernels: Partition Device Model Evaluation (PME), Partition Matrix Factorization (PMF), Interconnection Matrix Evaluation (IME), and Interconnection Matrix Factorization (IMF). Another model is derived to assign each of the kernels to the most suitable execution platform of the Amazon EC2 heterogeneous cloud. The partitioning approach using heterogeneous resources has achieved an order-of-magnitude speedup over optimized multithreaded implementations of SPICE using state of the art KLU and NICSLU packages for matrix solution.

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Section: Hardware Architecture Modelmentioning

confidence: 99%

Parallel circuit simulation using the direct method on a heterogeneous cloud

Helal

Bayoumi

Hanafy

2015

Proceedings of the 52nd Annual Design Automation Conference

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“…Another paper entitled ''Evaluation of Messaging Middleware for High Performance Cloud Computing'' by Doallo et al [7] presents an evaluation of high-performance computing message-passing middleware on a cloud computing infrastructure, Amazon EC2 cluster compute instances, equipped with 10 gigabit Ethernet. The analysis of the experimental results, confronted with a similar testbed, has shown the significant impact that virtualized environments still have on communications performance, which demands more efficient communication middleware support to get over current cloud network limitations.…”

Section: Other Issues In Ubiquitous Computingmentioning

confidence: 99%

Agent societies and social networks for ubiquitous computing

Rho

Chilamkurti

Defrawy

2013

Pers Ubiquit Comput

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In ubiquitous computing environments, providing appropriate services and information to users at the right place in the right way is challenging for many reasons: different user interests, heterogeneous devices and services, dynamic networks, information overload, or differing privacy levels, for example. Agent technology is a paradigm expected to play an increasing role in complex computing environments, and due to the increasing popularity of social networking services, we expect to see the convergence of agent and social web technologies. The goal of this theme issue is to bring together state-of-the-art research contributions that examine the convergence of agent technologies and social networks for ubiquitous computing.

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“…In other words, the simple addition of instances and the use of load balancers have no effect in these applications since they are not able to detect and use these resources [11]. Technically, over recent years most parallel applications have been developed using the Message Passing Interface (MPI) 1.x, which does not have any support for changing the number of processes during the execution [12]. While this changed with MPI version 2.0, this feature is not yet supported by many of the available MPI implementations [9].…”

Section: Introductionmentioning

confidence: 99%

Impact of Thresholds and Load Patterns when Executing HPC Applications with Cloud Elasticity

Rodrigues

Rostirolla

Righi

et al. 2016

CLEIej

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Elasticity is one of the most known capabilities related to cloud computing, being largely deployed reactively using thresholds. In this way, maximum and minimum limits are used to drive resource allocation and deallocation actions, leading to the following problem statements: How can cloud users set the threshold values to enable elasticity in their cloud applications? And what is the impact of the application’s load pattern in the elasticity? This article tries to answer these questions for iterative high performance computing applications, showing the impact of both thresholds and load patterns on application performance and resource consumption. To accomplish this, we developed a reactive and PaaS-based elasticity model called AutoElastic and employed it over a private cloud to execute a numerical integration application. Here, we are presenting an analysis of best practices and possible optimizations regarding the elasticity and HPC pair. Considering the results, we observed that the maximum threshold influences the application time more than the minimum one. We concluded that threshold values close to 100% of CPU load are directly related to a weaker reactivity, postponing resource reconfiguration when its activation in advance could be pertinent for reducing the application runtime.

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Evaluation of messaging middleware for high-performance cloud computing

Cited by 7 publications

References 20 publications

Parallel circuit simulation using the direct method on a heterogeneous cloud

Parallel circuit simulation using the direct method on a heterogeneous cloud

Agent societies and social networks for ubiquitous computing

Impact of Thresholds and Load Patterns when Executing HPC Applications with Cloud Elasticity

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