Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userR-GMA: First results after deployment
70
0
0.0
(
0
)
Added by
Steve Fisher
Publication date
2003
fields
Informatics Engineering
and research's language is
English
Ask ChatGPT about the research
No Arabic abstract
We describe R-GMA (Relational Grid Monitoring Architecture) which is being developed within the European DataGrid Project as an Grid Information and Monitoring System. Is is based on the GMA from GGF, which is a simple Consumer-Producer model. The special strength of this implementation comes from the power of the relational model. We offer a global view of the information as if each VO had one large relational database. We provide a number of different Producer types with different characteristics; for example some support streaming of information. We also provide combined Consumer/Producers, which are able to combine information and republish it. At the heart of the system is the mediator, which for any query is able to find and connect to the best Producers to do the job. We are able to invoke MDS info-provider scripts and publish the resulting information via R-GMA in addition to having some of our own sensors. APIs are available which allow the user to deploy monitoring and information services for any application that may be needed in the future. We have used it both for information about the grid (primarily to find what services are available at any one time) and for application monitoring. R-GMA has been deployed in Grid testbeds, we describe the results and experiences of this deployment.
rate research
Read More
We describe R-GMA (Relational Grid Monitoring Architecture) which has been developed within the European DataGrid Project as a Grid Information and Monitoring System. Is is based on the GMA from GGF, which is a simple Consumer-Producer model. The special strength of this implementation comes from the power of the relational model. We offer a global view of the information as if each Virtual Organisation had one large relational database. We provide a number of different Producer types with different characteristics; for example some support streaming of information. We also provide combined Consumer/Producers, which are able to combine information and republish it. At the heart of the system is the mediator, which for any query is able to find and connect to the best Producers for the job. We have developed components to allow a measure of inter-working between MDS and R-GMA. We have used it both for information about the grid (primarily to find out about what services are available at any one time) and for application monitoring. R-GMA has been deployed in various testbeds; we describe some preliminary results and experiences of this deployment.
Ookami is a computer technology testbed supported by the United States National Science Foundation. It provides researchers with access to the A64FX processor developed by Fujitsu in collaboration with RIK{Xi}N for the Japanese path to exascale computing, as deployed in Fugaku, the fastest computer in the world. By focusing on crucial architectural details, the ARM-based, multi-core, 512-bit SIMD-vector processor with ultrahigh-bandwidth memory promises to retain familiar and successful programming models while achieving very high performance for a wide range of applications. We review relevant technology and system details, and the main body of the paper focuses on initial experiences with the hardware and software ecosystem for micro-benchmarks, mini-apps, and full applications, and starts to answer questions about where such technologies fit into the NSF ecosystem.
Application users have now been experiencing for about a year with the standardized resource brokering services provided by the workload management package of the EU DataGrid project (WP1). Understanding, shaping and pushing the limits of the system has provided valuable feedback on both its design and implementation. A digest of the lessons, and better practices, that were learned, and that were applied towards the second major release of the software, is given.
In a previous paper [1], we presented a three-flavour oscillation analysis of the solar neutrino measurements and of the first data from the KamLAND experiment, in terms of the relevant mass-mixing parameters (delta m^2, theta_12, theta_13). The analysis, performed by including the terrestrial neutrino constraints coming from the CHOOZ (reactor), KEK-to-Kamioka (K2K, accelerator) and Super-Kamiokande (SK, atmospheric) experiments, provided a stringent upper limit on theta_13, namely, sin^2(theta_13)<0.05 at 3 sigma. We reexamine such upper bound in the light of a recent (although preliminary) reanalysis of atmospheric neutrino data performed by the SK collaboration, which seems to shift the preferred value of the largest neutrino square mass difference Delta m^2 downwards. By taking the results of the SK official reanalysis at face value, and by repeating the analysis in [1] with such a new input, we find that the upper bound on theta_{13} is somewhat relaxed: sin^2(theta_13)<0.067 at 3 sigma. Related phenomenological issues are briefly discussed.
The first results from the KamLAND experiment have provided confirmational evidence for the Large Mixing Angle (LMA) MSW solution to the solar neutrino problem. We do a global analysis of solar and the recently announced KamLAND data (both rate and spectrum) and investigate its effect on the allowed region in the $Delta m^2-tan^2theta$ plane. The best-fit from a combined analysis which uses the KamLAND rate plus global solar data comes at $Delta m^2 = 6.06 times 10^{-5}$ eV $^2$ and $tan^2theta=0.42$, very close to the global solar best-fit, leaving a large allowed region within the global solar LMA contour. The inclusion of the KamLAND spectral data in the global fit gives a best-fit $Delta m^2 = 7.15 times 10^{-5}$ eV $^2$ and $tan^2theta=0.42$ and constrains the allowed areas within LMA, leaving essentially two allowed zones. Maximal mixing though allowed by the KamLAND data alone is disfavored by the global solar data and remains disallowed at about $3sigma$. The LOW solution is now ruled out at about 5$sigma$ w.r.t. the LMA solution.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
