By Paul Graham, Matti Heikkurinen, Jarek Nabrzyski, Ariel Oleksiak (auth.), Marios D. Dikaiakos (eds.)
This ebook constitutes the completely refereed post-proceedings of the second one eu AcrossGrid convention, AxGrids 2004, held in Nicosia, Cyprus in January 2004.
The 27 revised complete papers and four revised brief papers offered have been rigorously chosen in the course of rounds of reviewing and development from fifty seven submissions. The papers tackle the whole variety of present issues in grid computing from computational and knowledge grids to the semantic grid and grid program in quite a few fields.
Read Online or Download Grid Computing: Second European AcrossGrids Conference, AxGrids 2004, Nicosia, Cyprus, January 28-30, 2004. Revised Papers PDF
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Additional resources for Grid Computing: Second European AcrossGrids Conference, AxGrids 2004, Nicosia, Cyprus, January 28-30, 2004. Revised Papers
It is the main module that applies the scheduling policy and procedure based on the Runtime Estimator, and according to the deadlines of the jobs as they are given by the customer. 1 Runtime Estimation Model Resource Performance Parameters for Heterogeneous Platforms A generic PC architecture consists of a CPU, L1, L2 cache and RAM (memory hierarchy) and the hard disk. There are several different architectures for each of the above components and different operating systems. For the CPU performance the most suitable generic measurement is the MFLOPS benchmark .
IEEE Transactions on Parallel and Distributed Systems, 4(2):175–187, February 1993. 17. H. Topcuoglu, S. Hariri, and M. Wu. Performance-effective and low-complexity task scheduling for heterogeneous computing. IEEE Transactions on Parallel and Distributed Systems, 13(3):260–274, March 2002. 18. H. Zhao and R. Sakellariou. An experimental investigation into the rank function of the heterogeneous earliest finish time scheduling algorithm. In Euro-Par 2003. Springer-Verlag, LNCS 2790, 2003. An Advanced Architecture for a Commercial Grid Infrastructure Antonios Litke1, Athanasios Panagakis1, Anastasios Doulamis1, Nikolaos Doulamis1, Theodora Varvarigou1, and Emmanuel Varvarigos2 1 Electrical and Computer Engineering Dept.
Different applications are characterized by different properties and thus require different modeling and prediction schemes. In this paper, we enhance the current Grid architecture by incorporating all the aforementioned described mechanisms so as to allow guarantees of the diverse and contradictory users’ QoS requirements. Our focus is oriented on developing a proper runtime estimation model, which is the heart of any scheduling and resource allocation algorithm. In particular, we propose a scheme able to predict the runtime of submitted jobs for any given application on any given computer by introducing a general prediction model.