Massive Parallel Fluid Flow Simulations Using Hierarchical Data Format Version 5 (HDF5)
| Autor: | Christoph Ertl, Ralf-Peter Mundani, Jérôme Frisch |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Distributed database
Computer science 02 engineering and technology Parallel computing computer.file_format Hierarchical Data Format Data structure Supercomputer 01 natural sciences Visualization 010101 applied mathematics File locking Server 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing 0101 mathematics Interactive visualization computer |
| Zdroj: | ISPDC |
| DOI: | 10.1109/ispdc.2016.13 |
| Popis: | More and more massive parallel codes running on several hundreds of thousands of cores enter the computational science and engineering domain, allowing high-fidelity computations up to trillions of unknowns for very detailed analyses of the underlying problems. During such runs, typically gigabytes of data are being produced, hindering both efficient storage and (interactive) data exploration. Here, advanced approaches based on inherently distributed data formats such as HDF5 become necessary in order to avoid long latencies when storing the data and to support fast (random) access when retrieving the data for visual processing. Avoiding file locking and using collective buffering, we achieved write bandwiths to a single file close to the theoretical peak on a modern supercomputing cluster. The structure of our output file supports a very fast interactive visualisation and introduces additional steering functionality. |
| Databáze: | OpenAIRE |
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