By Michael Bader, Hans-Joachim Bungartz, Martin Schreiber (auth.), Rainer Keller, David Kramer, Jan-Philipp Weiss (eds.)
This state of the art survey gains themes with regards to the effect of multicore, manycore, and coprocessor applied sciences in technological know-how and large-scale purposes in an interdisciplinary surroundings. The papers integrated during this survey disguise study in mathematical modeling, layout of parallel algorithms, features of microprocessor structure, parallel programming languages, hardware-aware computing, heterogeneous systems, manycore applied sciences, functionality tuning, and necessities for large-scale purposes. The contributions offered during this quantity are an end result of an inspiring convention conceived and arranged by means of the editors on the collage of technologies (HfT) in Stuttgart, Germany, in September 2012. the ten revised complete papers chosen from 21 submissions are provided including the twelve poster abstracts and concentrate on mix of recent features of microprocessor applied sciences, parallel functions, numerical simulation, and software program improvement; hence they essentially express the potential for rising applied sciences within the quarter of multicore and manycore processors which are paving the best way in the direction of own supercomputing and extremely most likely in the direction of exascale computing.
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This quantity set LNCS 10039 and 10040 constitutes the refereed post-conference complaints of the second one overseas convention on Cloud Computing and defense, ICCCS 2016, held in Nanjing, China, in the course of July 29-31, 2016. The ninety seven papers of those volumes have been rigorously reviewed and chosen from 272 submissions.
- Scientific Computing in Electrical Engineering SCEE 2010
- [Magazine] Embedded Computing Design. 2007. Number 2 (March)
- The Government Machine: A Revolutionary History of the Computer
- Soft Computing Based Modeling in Intelligent Systems
- Microsoft Access 2016 – Das Handbuch, 1st Edition
- Opportunities and Constraints of Parallel Computing
Extra resources for Facing the Multicore-Challenge III: Aspects of New Paradigms and Technologies in Parallel Computing
The performance results show that applications can gain a speedup by using ﬁne-grained reduction since this implementation enables to hide the reduction between calculation while minimising the time waiting for synchronisation. 1 Introduction For applications of parallel scientiﬁc computing, reduction operations play an important role. In many cases, the performance of reduction operations, which aggregate data located on diﬀerent processors to a common result datum using a speciﬁed operation, is crucial to the overall performance of the application.
Fig. 4. Buﬀered ping-pong communication strategy for the calculation of the DG operator 44 5 C. Altmann et al. Scale-Up Eﬃciency Besides the promising fundamental eﬃciency of the DGSEM method, its main advantages are based on its “high performance computing” capability. The DG algorithm is inherently parallel, since all elements do communicate only with their direct neighbors via solution and ﬂux exchange.
For example, gradients in η-direction are already sent while the numerical ﬂux in ξ-direction is yet to be calculated. This is important since all send-receive operations have to be buﬀered. 42 C. Altmann et al.
! Fig. 3. Buﬀered ping-pong communication strategy for the calculation of BR1 lifting in ξ-direction
"$$ Eﬃcient HPC DGSEM Parallelization !