Monitoring Cluster on Online Compiler with Ganglia

Ganglia is an open source monitoring system for high performance computing (HPC) that collect both a whole cluster and every nodes status and report to the user. We use Ganglia to monitor our spasi.informatika.lipi.go.id (SPASI), a customized-fedora10-based cluster, for our cluster online compiler, CLAW (cluster access through web). Our experience on using Ganglia shows that Ganglia has a capability to view our cluster status and allow us to track them

High performance communication subsystem for clustering standard high-volume servers using Gigabit Ethernet

This paper presents an efficient communication subsystem, DP-II, for clustering standard high-volume (SHV) servers using Gigabit Ethernet. The DP-II employs several lightweight messaging mechanisms to achieve low-latency and high-bandwidth communication. The test shows an 18.32 us single-trip latency and 72.8 MB/s bandwidth on a Gigabit Ethernet network for connecting two Dell PowerEdge 6300 Quad Xeon SMP servers running Linux. To improve the programmability of the DP-II communication subsystem, the development of DP-II was based on a concise yet powerful abstract communication model, Directed Point Model, which can be conveniently used to depict the inter-process communication pattern of a parallel task in the cluster environment. In addition, the API of DP-II preserves the syntax and semantics of traditional UNIX I/O operations, which make it easy to use.published_or_final_versio

Towards Hybrid Classical-Quantum Computation Structures in Wirelessly-Networked Systems

With unprecedented increases in traffic load in today's wireless networks, design challenges shift from the wireless network itself to the computational support behind the wireless network. In this vein, there is new interest in quantum-compute approaches because of their potential to substantially speed up processing, and so improve network throughput. However, quantum hardware that actually exists today is much more susceptible to computational errors than silicon-based hardware, due to the physical phenomena of decoherence and noise. This paper explores the boundary between the two types of computation---classical-quantum hybrid processing for optimization problems in wireless systems---envisioning how wireless can simultaneously leverage the benefit of both approaches. We explore the feasibility of a hybrid system with a real hardware prototype using one of the most advanced experimentally available techniques today, reverse quantum annealing. Preliminary results on a low-latency, large MIMO system envisioned in the 5G New Radio roadmap are encouraging, showing approximately 2--10X better performance in terms of processing time than prior published results.Comment: HotNets 2020: Nineteenth ACM Workshop on Hot Topics in Networks (https://doi.org/10.1145/3422604.3425924

Teaching high-performance service in a cluster computing course

[EN] Most courses on cluster computing in graduate and postgraduate studies are focused on parallel programming and high-performance/high-throughput computing. This is the typical usage of clusters in academia and research centres. However, nowadays, many companies are providing web, mail and, in general, Internet services using computer clusters. These services require a different ``cluster flavour'': high-performance service and high availability. Despite the fact that computer clusters for each environment demand a different configuration, most university cluster computing courses keep focusing only on high-performance computing, ignoring other possibilities. In this paper, we propose several teaching strategies for a course on cluster computing that could fill this gap. The content developed here would be taught as a part of the course. The subject shows several strategies about how to configure, test and evaluate a high-availability/load-balanced Internet server. A virtualization-based platform is used to build a cluster prototype, using Linux as its operating system. Evaluation of the course shows that students knowledge and skills on the subject are improved at the end of the course. On the other hand, regarding the teaching methodology, the results obtained in the yearly survey of the University confirm student satisfaction.This work was supported in part by the Spanish Ministerio de Economia y Competitividad (MINECO) and by FEDER funds under Grant TIN2015-66972-C5-1-R.López Rodríguez, PJ.; Baydal Cardona, ME. (2018). Teaching high-performance service in a cluster computing course. Journal of Parallel and Distributed Computing. 117:138-147. https://doi.org/10.1016/j.jpdc.2018.02.027S13814711

On a course on computer cluster configuration and administration

[EN] Computer clusters are today a cost-effective way of providing either high-performance and/or high-availability. The flexibility of their configuration aims to fit the needs of multiple environments, from small servers to SME and large Internet servers. For these reasons, their usage has expanded not only in academia but also in many companies. However, each environment needs a different ¿cluster flavour¿. High-performance and high-throughput computing are required in universities and research centres while high-performance service and high-availability are usually reserved to use in companies. Despite this fact, most university cluster computing courses continue to cover only high-performance computing, usually ignoring other possibilities. In this paper, a master-level course which attempts to fill this gap is discussed. It explores the different types of cluster computing as well as their functional basis, from a very practical point of view. As part of the teaching methodology, each student builds from scratch a computer cluster based on a virtualization tool. The entire process is designed to be scalable. The goal is to be able to apply it to an actual computer cluster with a larger number of nodes, such as those the students may subsequently encounter in their professional life.This work was supported in part by the Spanish Ministerio de Economia y Competitividad (MINECO) and by FEDER funds under Grant TIN2015-66972-C5-1-R.López Rodríguez, PJ.; Baydal Cardona, ME. (2017). On a course on computer cluster configuration and administration. Journal of Parallel and Distributed Computing. 105:127-137. https://doi.org/10.1016/j.jpdc.2017.01.009S12713710

Procesamiento paralelo en clusters

En el contexto de procesamiento paralelo en clusters, existen muchas líneas de investigación que aún están abiertas a nivel internacional. Las dos más importantes que se tienen en cuenta en esta línea de investigación son: a) rendimiento paralelo y b) creación de ambientes de desarrollo y ejecución de aplicaciones en clusters. En el contexto de rendimiento paralelo se tienen en cuenta aspectos tales como la optimización, estimación y modelización; todos temas que aún no han sido resueltos en general y en el mejor de los casos se han presentado soluciones para algunas áreas de aplicación. En el contexto de ambientes de desarrollo y ejecución de aplicaciones en clusters se tiene en cuenta la posibilidad de proveer a los usuarios una "imagen única del sistema", o Single System Image (SSI) al menos en algunos aspectos o subsistemas específicos que son de interés general.Eje: Sistemas distribuidos y tiempo realRed de Universidades con Carreras en Informática (RedUNCI