http://dl.gi.de/handle/20.500.12116/1913 Tue, 21 Jul 2026 14:14:17 GMT 2026-07-21T14:14:17Z http://dl.gi.de/handle/20.500.12116/8622 Parallel coding for storage systems — An OpenMP and OpenCL capable framework Sobe, Peter Parallel storage systems distribute data onto several devices. This allows high access bandwidth that is needed for parallel computing systems. It also improves the storage reliability, provided erasure-tolerant coding is applied and the coding is fast enough. In this paper we assume storage systems that apply data distribution and coding in a combined way. We describe, how coding can be done parallel on multicore and GPU systems in order to keep track with the high storage access bandwidth. A framework is introduced that calculates coding equations from parameters and translates them into OpenMP- and OpenCL-based coding modules. These modules do the encoding for data that is written to the storage system, and do the decoding in case of failures of storage devices. We report on the performance of the coding modules and identify factors that influence the coding performance. Sun, 01 Jan 2012 00:00:00 GMT http://dl.gi.de/handle/20.500.12116/8622 2012-01-01T00:00:00Z http://dl.gi.de/handle/20.500.12116/8621 Achieving scalability for job centric monitoring in a distributed infrastructure Hilbrich, Marcus; Müller-Pfefferkorn, Ralph Job centric monitoring allows to observe jobs on remote computing resources. It may offer visualisation of recorded monitoring data and helps to find faulty or misbehaving jobs. If installations like grids or clouds are observed monitoring data of many thousands of jobs have to be handled. The challenge of job centric monitoring infrastructures is to store, search and access data collected in huge installations like grids or clouds. We take this challenge with a distributed layer based architecture which provides a uniform view to all monitoring data. The concept of this infrastructure called SLAte and an analysis of the scalability is provided in this paper. Sun, 01 Jan 2012 00:00:00 GMT http://dl.gi.de/handle/20.500.12116/8621 2012-01-01T00:00:00Z http://dl.gi.de/handle/20.500.12116/8623 Fooling the masses with performance results: Old classics and some new ideas Wellein, G.; Hager, G. G. Wellein and G. Hager Department for Computer Science and Erlangen Regional Computing Center Friedrich-Alexander-Universität Erlangen-Nürnberg In 1991, David H. Bailey published his insightful 'Twelve Ways to Fool the Masses When Giving Performance Results on Parallel Computers.' In that humorous article, Bailey pinpointed typical 'evade and disguise' techniques for presenting mediocre performance results in the best possible light. At that time, the supercomputing landscape was governed by the 'chicken vs. oxen' debate: Could strong vector CPUs survive against the new massively parallel systems? In the past two decades, hybrid, hierarchical systems, multi-core processors, accelerator technology, and the dominating presence of commodity hardware have reshaped the landscape of High Performance Computing. It's also not so much oxen vs. chickens anymore; billions of ants have entered the battlefield. This talk gives an update of the 'Twelve Ways.' Old classics are presented alongside new 'stunts' that reflect today's technological boundary conditions. DISCLAIMER: Although these musings are certainly inspired by experience with many publications and talks in HPC, I wish to point out that (i) no offense is intended, (ii) I am not immune to the inherent temptations myself and (iii) this all still just meant to be fun. Sun, 01 Jan 2012 00:00:00 GMT http://dl.gi.de/handle/20.500.12116/8623 2012-01-01T00:00:00Z http://dl.gi.de/handle/20.500.12116/8615 Euro-Par 2013 Aachen Sun, 01 Jan 2012 00:00:00 GMT http://dl.gi.de/handle/20.500.12116/8615 2012-01-01T00:00:00Z