This session will focus on how to do high speed math using PETSc and SLEPc. PETSc\, pronounced PET-see (the S is silent)\, is a suit e of data structures and routines for the scalable (parallel) solution of scientific applications modeled by partial differential equations. It su pports MPI\, shared memory pthreads\, and GPUs through CUDA or OpenCL\, a s well as hybrid MPI-shared memory pthreads or MPI-GPU parallelism. SLEPc is an extension of PETSc and can be used for linear eigenvalue problems in either standard or generalized form\, with real or complex arithmetic. It can also be used for computing a partial SVD of a large\, sparse\, re ctangular matrix\, and to solve nonlinear eigenvalue problems (quadratic or genuinely nonlinear). Additionally\, SLEPc provides solvers for the co mputation of the action of a matrix function on a vector.

DTEND;TZID=America/Phoenix:20141018T151500 DTSTAMP:20230322T085806Z DTSTART;TZID=America/Phoenix:20141018T141500 GEO:33.293070;-111.796620 LOCATION:Chandler - Gilbert Community College - IRN-125 ORGANIZER: SEQUENCE:0 STATUS:CONFIRMED SUMMARY:This session will focus on how to do high speed math using PETS c and SLEPc. PETSc\, pronounced PET-see (the S is silent)\, is a suite of data structures and routines for the scalable (parallel) solution of sci entific applications modeled by partial differential equations. It suppor ts MPI\, shared memory pthreads\, and GPUs through CUDA or OpenCL\, as we ll as hybrid MPI-shared memory pthreads or MPI-GPU parallelism. SLEPc is an extension of PETSc and can be used for linear eigenvalue problems in e ither standard or generalized form\, with real or complex arithmetic. It can also be used for computing a partial SVD of a large\, sparse\, rectan gular matrix\, and to solve nonlinear eigenvalue problems (quadratic or g enuinely nonlinear). Additionally\, SLEPc provides solvers for the comput ation of the action of a matrix function on a vector.

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