New PDF release: An Introduction to Parallel Programming

By Tobias Wittwer

ISBN-10: 9071301788

ISBN-13: 9789071301780

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If you are lucky to have access to such a machine, the system’s documentation should contain information about performance measurement. Please note that the goal of parallelisation and optimisation is not to maximise the efficiency, but to minimise the runtime required for a program. Sometimes, one algorithm may be less efficient than another, but also require a smaller number of floating point operations, resulting in a shorter runtime. 1 Spherical harmonic analysis Spherical harmonic analysis (SHA) is Fourier analysis on the sphere.

Parallelising this loop is easy, done in the same 44 CHAPTER 5. 4), making sure that all required variables are set PRIVATE. $OMP DO do i=1,nobs ... $OMP END PARALLEL To our dismay, the build of Nbd is not sped up, and problem does not converge any more: the preconditioner was not built correctly. As all threads may access Nbd at the same time, some summations are not done correctly. This problem can be circumvented by giving each thread its own copy of Nbd , and combining them later. threadnum = omp_get_thread_num()+1 ...

Architecture and use of shared and distributed memory parallel computers. Published by Willi Schönauer, Karlsruhe. , 2005. Minimizing development and maintenance costs in supporting persistently optimized BLAS. Software: Practice and Experience 35 (2), 101-121. Index ACML, 18 ATLAS, 19 BLACS, 21 BLAS, 16, 17, 21, 25, 30, 31, 33, 46, 49 bus, 6, 11, 44 ccNUMA, 8, 13 cluster, 9, 11, 38, 47, 48 conjugate gradients, 40 crossbar switch, 7 DGEMM, 25 distributed memory, 1, 7, 9, 19, 21, 34, 46 DPOSV, 30, 33, 36, 46 DSYRK, 25, 30, 31, 33, 36, 46 efficiency, 24, 33, 39, 49 FLOPS, 24 FPU, 4, 24 gfortran, 2, 16 Goto BLAS, 18 grid, 10 ifort, 2, 15 Infiniband, 9, 20, 38, 47, 48 multithreading, 15, 19, 20, 31, 36, 46, 49 MVAPICH, 20 Myrinet, 9, 20 node, 9, 20, 34, 39, 46, 47 Open MPI, 20 OpenMP, 1, 2, 15, 16, 24, 31, 43, 48 performance, 5, 7, 8, 11, 24, 33, 39, 44 pipeline, 4 preconditioning, 41, 42, 44, 46 process, 34, 46, 47 profiling, 24, 42 ScaLAPACK, 1, 21, 33, 49 SHALE, 2, 27 shared memory, 1, 6, 9, 15, 20, 33 SIMD, 5 SMP, 6, 9, 36 spherical harmonic analysis, 2, 27 superscalar, 4 thread, 31, 32, 40, 44, 49 timing, 23, 30 vectorisation, 5 LAPACK, 16, 17, 21, 30, 31, 33, 46, 49 MIMD, 5 MKL, 17 MPI, 1, 19, 24, 33, 46, 49 MPICH, 20 MPP, 8, 12 53 An Introduction to Parallel Programming Many scientic computations require a considerable amount of computing time.

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An Introduction to Parallel Programming by Tobias Wittwer


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