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 applications. We propose an end-to-end approach to parallel supercomputing. The key idea is to replace the cumbersome file interface with a scalable, parallel, runtime data structure, on top of which all simulation components are constructed in a tightly coupled way. We have implemented this new methodology within an octree-based finite element simulation system named Hercules. The only input to Hercules is material property descriptions of a problem domain; the only outputs are lightweight jpegformated images generated as they are simulated at every visualization time step. There is absolutely no other intermediary file I/O. Performance evaluation of Hercules on up to 2048 processors on the AlphaServer system at Pittsburgh Supercomputing Center has shown good isogranular scalability and fixed-size scalability.

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