Applied Parallel and Scientific Computing: 10th by Bo Kågström, Daniel Kressner, Meiyue Shao (auth.), Kristján

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By Bo Kågström, Daniel Kressner, Meiyue Shao (auth.), Kristján Jónasson (eds.)

The quantity set LNCS 7133 and LNCS 7134 constitutes the completely refereed post-conference lawsuits of the tenth foreign convention on utilized Parallel and clinical Computing, PARA 2010, held in Reykjavík, Iceland, in June 2010. those volumes include 3 keynote lectures, 29 revised papers and forty five minisymposia displays prepared at the following subject matters: cloud computing, HPC algorithms, HPC programming instruments, HPC in meteorology, parallel numerical algorithms, parallel computing in physics, medical computing instruments, HPC software program engineering, simulations of atomic scale platforms, instruments and environments for accelerator dependent computational biomedicine, GPU computing, excessive functionality computing period equipment, real-time entry and processing of huge info units, linear algebra algorithms and software program for multicore and hybrid architectures in honor of Fred Gustavson on his seventy fifth birthday, reminiscence and multicore matters in clinical computing - concept and praxis, multicore algorithms and implementations for software difficulties, quickly PDE solvers and a posteriori blunders estimates, and scalable instruments for top functionality computing.

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Additional info for Applied Parallel and Scientific Computing: 10th International Conference, PARA 2010, Reykjavík, Iceland, June 6-9, 2010, Revised Selected Papers, Part I

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1 The Informed Inversion Problem The Necessity of Algorithm Tuning We have demonstrated above that the performance of all blind inversion schemes are exactly the same, when averaged over all conceivable fit functions, or subsets hereof. This means that if, for example, a genetic algorithm performs better than a crude random search on certain problems, it will perform worse on other problems. Apparently, this result is contradicted by the experience of a vast number of researchers who have seen popular algorithms outperforming crude random search by several orders of magnitude.

Mosegaard The Blind Inversion Problem It is often reported in the literature that solutions to nonlinear inverse problems were obtained by problem-independent algorithms, the so-called meta-heuristics. This type of algorithms is claimed to work efficiently because of some general, external (problem independent) principle. For example, simulated annealing [5] inherits its efficiency from thermodynamic principles, genetic algorithms [6,7] exploit evolutionary principles, and taboo-search [8] uses some ’common sense’ strategy.

LAPACK User’s Guide, 3rd edn. SIAM, Philadelphia (1999) 3. : On a Block Implementation of Hessenberg Multishift QR Iteration. Intl. J. of High Speed Comput. 1, 97–112 (1989) 4. : On Swapping Diagonal Blocks in Real Schur Form. Linear Algebra Appl. 186, 73–95 (1993) 5. : ScaLAPACK Users’ Guide. SIAM, Philadelphia (1997) 6. : The Multishift QR Algorithm. Part I: Maintaining Well-focused Shifts and Level 3 Performance. SIAM J. Matrix Anal. Appl. 23(4), 929–947 (2002) 7. : The Multishift QR Algorithm.

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