Exploring power behaviors and trade-offs of in-situ data analytics

pre-printAs scientific applications target exascale, challenges related to data and energy are becoming dominating concerns. For example, coupled simulation workflows are increasingly adopting in-situ data processing and analysis techniques to address costs and overheads due to data movement and I/O. However it is also critical to understand these overheads and associated trade-offs from an energy perspective. The goal of this paper is exploring data-related energy/performance trade-offs for end-to-end simulation workflows running at scale on current high-end computing systems. Specifically, this paper presents: (1) an analysis of the data-related behaviors of a combustion simulation workflow with an in-situ data analytics pipeline, running on the Titan system at ORNL; (2) a power model based on system power and data exchange patterns, which is empirically validated; and (3) the use of the model to characterize the energy behavior of the workflow and to explore energy/performance tradeoffs on current as well as emerging systems

Federated Computing for the Masses – Aggregating Resources to Tackle Large-scale Engineering Problems

The complexity of many problems in science and engineering requires computational capacity exceeding what average user can expect from a single computational center. While many of these problems can be viewed as a set of independent tasks, their collective complexity easily requires millions core-hours on any state-of-the-art HPC resource, and throughput that cannot be sustained by a single multi-user queuing system. In this paper we explore the use of aggregated HPC resources to solve large-scale engineering problems. We show it is possible to build a computational federation that is easy to use by end-users, and is elastic, resilient and scalable. We argue that the fusion of federated computing and real-life engineering problems can be brought to average user if relevant middleware is provided. We report on the use of federation of 10 distributed heterogeneous HPC resources to perform a large-scale interrogation of the parameter space in the microscale fluid flow problem

Componentes biosociales y enfermedades prevalentes de la infancia en menores de 5 años del Bañado Sur de Asunción = Biosocial components and prevalent childhood diseases in children under 5 years from the Bañado Sur of Asunción

Las enfermedades prevalentes de la infancia en condiciones adversas como la pobreza pueden ser graves o mortales. La Atención Integrada a las Enfermedades Prevalentes de la Infancia (AIEPI) aborda los determinantes sociales de la salud. El trabo tiene el objetivo de conocer las enfermedades prevalentes y las condiciones ambientales de menores de 5 años del Bañado Sur aplicando AIEPI.CONACYT – Consejo Nacional de Ciencia y TecnologíaPROCIENCI

eNANOS Grid Resource Broker

Abstract. Grid computing has been presented as a way of sharing geographically and organizationally distributed resources and of performing successfully distributed computation. To achieve these goals a software layer is necessary to interact with grid environments. Therefore, not only a middleware and its services are needed, but it is also necessary to offer resource management services to hide the underlying complexity of the Grid resources to Grid users. In this paper, we present the design and implementation of an OGSI-compliant Grid resource broker compatible with both GT2 and GT3. It focuses in resource discovery and management, and dynamic policies management for job scheduling and resource selection. The presented resource broker is designed in an extensible and modular way using standard protocols and schemas to become compatible with new middleware versions. We also present experimental results to demonstrate the resource broker behavior

Salud, Enfermedad y Pobreza Urbana : Estudio de los procesos de salud, enfermedad y atención de las familias en la periferia sur de Asunción

El acercamiento del proyecto “Salud, enfermedad y pobreza urbana” a la realidad del Bañado Sur tuvo en cuenta la triple dimensionalidad de los procesos de salud, enfermedad y atención, partiendo del enfoque de la Antropología de la salud. Esta publicación y el proyecto de investigación del cual forma parte son financiados por el Consejo Nacional de Ciencia y Tecnología (CONACYT) a través del Programa PROCIENCIA, con recursos del Fondo para la Excelencia de la Educación e Investigación (FEEI) del FONACIDE.CONACYT – Consejo Nacional de Ciencia y TecnologíaPROCIENCI

The Ocean Observatories Initiative

Author Posting. © The Oceanography Society, 2018. This article is posted here by permission of The Oceanography Society for personal use, not for redistribution. The definitive version was published in Oceanography 31, no. 1 (2018): 16–35, doi:10.5670/oceanog.2018.105.The Ocean Observatories Initiative (OOI) is an integrated suite of instrumented platforms and discrete instruments that measure physical, chemical, geological, and biological properties from the seafloor to the sea surface. The OOI provides data to address large-scale scientific challenges such as coastal ocean dynamics, climate and ecosystem health, the global carbon cycle, and linkages among seafloor volcanism and life. The OOI Cyberinfrastructure currently serves over 250 terabytes of data from the arrays. These data are freely available to users worldwide, changing the way scientists and the broader community interact with the ocean, and permitting ocean research and inquiry at scales of centimeters to kilometers and seconds to decades.Funding for the OOI is provided by the National Science Foundation through a Cooperative Support Agreement with the Consortium for Ocean Leadership (OCE-1026342)

Soporte para el análisis de workloads en el proyecto eNANOS

El proyecto eNANOS plantea la planificación coordinada de trabajos entre varios niveles, desde el entorno heterogéneo y dinámico de un Grid hasta la ejecución de procesos y threads en las CPU’s de un computador o un cluster. Para estudiar las políticas de planificación se necesita algún mecanismo de análisis de workloads. En este artículo presentamos un mecanismo de monitorización de trabajos integrado en el planificador eNANOS Scheduler. También presentamos una herramienta que a partir de la información obtenida en la monitorización es capaz de generar trazas que pueden ser visualizadas y analizadas fácilmente con Paraver. Para mostrar las ventajas del sistema planteado se presenta la evaluación de un workload y se compara con posibles alternativas.Peer ReviewedPostprint (published version