Evaluation of messaging middleware for high-performance cloud computing

This is a post-peer-review, pre-copyedit version of an article published in Personal and Ubiquitous Computing. The final authenticated version is available online at: http://dx.doi.org/10.1007/s00779-012-0605-3[Abstract] Cloud computing is posing several challenges, such as security, fault tolerance, access interface singularity, and network constraints, both in terms of latency and bandwidth. In this scenario, the performance of communications depends both on the network fabric and its efficient support in virtualized environments, which ultimately determines the overall system performance. To solve the current network constraints in cloud services, their providers are deploying high-speed networks, such as 10 Gigabit Ethernet. This paper 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 communication performance, which demands more efficient communication middleware support to get over the current cloud network limitations.Ministerio de Ciencia e Innovación; TIN2010-16735Ministerio de Educación y Ciencia; AP2010-434

Device level communication libraries for high‐performance computing in Java

This is the peer reviewed version of the following article: Taboada, G. L., Touriño, J. , Doallo, R. , Shafi, A. , Baker, M. and Carpenter, B. (2011), Device level communication libraries for high‐performance computing in Java. Concurrency Computat.: Pract. Exper., 23: 2382-2403. doi:10.1002/cpe.1777, which has been published in final form at https://doi.org/10.1002/cpe.1777. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions.[Abstract] Since its release, the Java programming language has attracted considerable attention from the high‐performance computing (HPC) community because of its portability, high programming productivity, and built‐in multithreading and networking support. As a consequence, several initiatives have been taken to develop a high‐performance Java message‐passing library to program distributed memory architectures, such as clusters. The performance of Java message‐passing applications relies heavily on the communications performance. Thus, the design and implementation of low‐level communication devices that support message‐passing libraries is an important research issue in Java for HPC. MPJ Express is our Java message‐passing implementation for developing high‐performance parallel Java applications. Its public release currently contains three communication devices: the first one is built using the Java New Input/Output (NIO) package for the TCP/IP; the second one is specifically designed for the Myrinet Express library on Myrinet; and the third one supports thread‐based shared memory communications. Although these devices have been successfully deployed in many production environments, previous performance evaluations of MPJ Express suggest that the buffering layer, tightly coupled with these devices, incurs a certain degree of copying overhead, which represents one of the main performance penalties. This paper presents a more efficient Java message‐passing communications device, based on Java Input/Output sockets, that avoids this buffering overhead. Moreover, this device implements several strategies, both in the communication protocol and in the HPC hardware support, which optimizes Java message‐passing communications. In order to evaluate its benefits, this paper analyzes the performance of this device comparatively with other Java and native message‐passing libraries on various high‐speed networks, such as Gigabit Ethernet, Scalable Coherent Interface, Myrinet, and InfiniBand, as well as on a shared memory multicore scenario. The reported communication overhead reduction encourages the upcoming incorporation of this device in MPJ ExpressMinisterio de Ciencia e Innovación; TIN2010-16735

NPB-MPJ: NAS Parallel Benchmarks Implementation for Message-Passing in Java

This is a post-peer-review, pre-copyedit version. The final authenticated version is available online at: http://dx.doi.org/10.1109/PDP.2009.59[Abstract] Java is a valuable and emerging alternative for the development of parallel applications, thanks to the availability of several Java message-passing libraries and its full multithreading support. The combination of both shared and distributed memory programming is an interesting option for parallel programming multi-core systems. However, the concerns about Java performance are hindering its adoption in this field, although it is difficult to evaluate accurately its performance due to the lack of standard benchmarks in Java. This paper presents NPB-MPJ, the first extensive implementation of the NAS Parallel Benchmarks (NPB), the standard parallel benchmark suite, for Message-Passing in Java (MPJ) libraries. Together with the design and implementation details of NPB-MPJ, this paper gathers several optimization techniques that can serve as a guide for the development of more efficient Java applications for High Performance Computing (HPC). NPB-MPJ has been used in the performance evaluation of Java against C/Fortran parallel libraries on two representative multi-core clusters. Thus, NPB-MPJ provides an up-to-date snapshot of MPJ performance, whose comparative analysis of current Java and native parallel solutions confirms that MPJ is an alternative for parallel programming multi-core systems.Ministerio de Educación y Ciencia; TIN2004-07797-C02Ministerio de Educación y Ciencia; TIN2007-67537-C03-02Xunta de Galicia; PGIDIT06PXIB105228P

Performance measurement and analysis of PC based cluster server using SET of Architecture and modeling a scalable High performance cluster

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Commodity single board computer clusters and their applications

© 2018 Current commodity Single Board Computers (SBCs) are sufficiently powerful to run mainstream operating systems and workloads. Many of these boards may be linked together, to create small, low-cost clusters that replicate some features of large data center clusters. The Raspberry Pi Foundation produces a series of SBCs with a price/performance ratio that makes SBC clusters viable, perhaps even expendable. These clusters are an enabler for Edge/Fog Compute, where processing is pushed out towards data sources, reducing bandwidth requirements and decentralizing the architecture. In this paper we investigate use cases driving the growth of SBC clusters, we examine the trends in future hardware developments, and discuss the potential of SBC clusters as a disruptive technology. Compared to traditional clusters, SBC clusters have a reduced footprint, are low-cost, and have low power requirements. This enables different models of deployment—particularly outside traditional data center environments. We discuss the applicability of existing software and management infrastructure to support exotic deployment scenarios and anticipate the next generation of SBC. We conclude that the SBC cluster is a new and distinct computational deployment paradigm, which is applicable to a wider range of scenarios than current clusters. It facilitates Internet of Things and Smart City systems and is potentially a game changer in pushing application logic out towards the network edge

Operational mesoscale atmospheric dispersion prediction using a parallel computing cluster

An operational atmospheric dispersion prediction system is implemented on a cluster supercomputer for Online Emergency Response at the Kalpakkam nuclear site. This numerical system constitutes a parallel version of a nested grid meso-scale meteorological model MM5 coupled to a random walk particle dispersion model FLEXPART. The system provides 48-hour forecast of the local weather and radioactive plume dispersion due to hypothetical airborne releases in a range of 100 km around the site. The parallel code was implemented on different cluster configurations like distributed and shared memory systems. A 16-node dual Xeon distributed memory gigabit ethernet cluster has been found sufficient for operational applications. The runtime of a triple nested domain MM5 is about 4h for a 24h forecast. The system had been operated continuously for a few months and results were ported on the IMSc home page. Initial and periodic boundary condition data for MM5 are provided by NCMRWF, New Delhi. An alternative source is found to be NCEP, USA. These two sources provide the input data to the operational models at different spatial and temporal resolutions using different assimilation methods. A comparative study on the results of forecast is presented using these two data sources for present operational use. Improvement is noticed in rainfall forecasts that used NCEP data, probably because of its high spatial and temporal resolution

SCIT — Ukrainian Supercomputer Project

The paper describes a first supercomputer cluster project in Ukraine, its hardware, software and characteristics. The paper shows the performance results received on systems that were built. There are also shortly described software packages made by cluster users that have already made a return of investments into a cluster project

Analysis of I/O Performance on an Amazon EC2 Cluster Compute and High I/O Platform

“This is a post-peer-review, pre-copyedit version of an article published in Journal of Grid Computing. The final authenticated version is available online at: https://doi.org/10.1007/s10723-013-9250-y[Abstract] Cloud computing is currently being explored by the scientific community to assess its suitability for High Performance Computing (HPC) environments. In this novel paradigm, compute and storage resources, as well as applications, can be dynamically provisioned on a pay-per-use basis. This paper presents a thorough evaluation of the I/O storage subsystem using the Amazon EC2 Cluster Compute platform and the recent High I/O instance type, to determine its suitability for I/O-intensive applications. The evaluation has been carried out at different layers using representative benchmarks in order to evaluate the low-level cloud storage devices available in Amazon EC2, ephemeral disks and Elastic Block Store (EBS) volumes, both on local and distributed file systems. In addition, several I/O interfaces (POSIX, MPI-IO and HDF5) commonly used by scientific workloads have also been assessed. Furthermore, the scalability of a representative parallel I/O code has also been analyzed at the application level, taking into account both performance and cost metrics. The analysis of the experimental results has shown that available cloud storage devices can have different performance characteristics and usage constraints. Our comprehensive evaluation can help scientists to increase significantly (up to several times) the performance of I/O-intensive applications in Amazon EC2 cloud. An example of optimal configuration that can maximize I/O performance in this cloud is the use of a RAID 0 of 2 ephemeral disks, TCP with 9,000 bytes MTU, NFS async and MPI-IO on the High I/O instance type, which provides ephemeral disks backed by Solid State Drive (SSD) technology.Ministerio de Ciencia e Innovación; TIN2010-16735Ministerio de Educación; AP2010-4348Galicia. Consellería de Cultura, Educación e Ordenación Universitaria; ref. 2010/