Leonardo Ramírez-Guzmán

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Parallel supercomputing has traditionally focused on the inner kernel of scientific simulations: the solver. The front and back ends of the simulation pipeline---problem description and interpretation of the output---have taken a back seat to the solver when it comes to attention paid to scalability and performance, and are often relegated to offline,(More)
We have developed a novel analytic capability for scientists and engineers to obtain insight from ongoing large-scale parallel unstructured mesh simulations running on thousands of processors. The breakthrough is made possible by a new approach that visualizes partial differential equation (PDE) solution data simultaneously while a parallel PDE solver(More)
State-of-the-art numerical solvers in Earth Sciences produce multi ter-abyte datasets per execution. Operating on increasingly larger datasets becomes challenging due to insufficient data bandwidth. Queries result in difficult to handle I/O access patterns. BEMC is a new mechanism that allows querying and processing wavefields in the compressed(More)
Conventional parallel scientific computing uses files as interface between simulation components such as meshing, partitioning, solving and visualizing. This approach results in time-consuming file transfers, disk I/O and data format conversions that consume large amounts of network, storage, and computing resources while contributing nothing to(More)
We demonstrate a new scalable approach to real-time monitoring , visualization, and steering of massively parallel simulations from a personal computer. The basis is an end-to-end approach to parallel supercomputing in which all components — meshing, partitioning, solver, and visual-ization — are tightly coupled and execute in parallel on a supercomputer.(More)
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