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PIDX: Efficient Parallel I/O for Multi-resolution Multi-dimensional Scientific Datasets
2011
2011 IEEE International Conference on Cluster Computing
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PIDX achieves up to 18 GiB/s I/O throughput at 8,192 processes for S3D to write data out in the IDX format. ...
We have therefore developed PIDX -a parallel API for writing data in an IDX format. ...
Previous work in multi-resolution data formats for parallel processing environments include work from Chiueh and Katz in developing a multi-resolution video format for parallel disk arrays [6] . ...
doi:10.1109/cluster.2011.19
dblp:conf/cluster/KumarVCSSPRCKG11
fatcat:acjkja3mxzeqljwjd4uir5tskq
Towards parallel access of multi-dimensional, multi-resolution scientific data
2010
2010 5th Petascale Data Storage Workshop (PDSW '10)
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Large scale scientific simulations routinely produce data of increasing resolution. Analyzing this data is key to scientific discovery. ...
HPC applications must therefore either write all data from a single process or convert existing data as a post-processing step, in either case failing to utilize available parallel I/O resources. ...
IDX supports multi-dimensional data of arbitrary dimensions and sizes. HZ order computation requires the spatial coordinates of data samples. ...
doi:10.1109/pdsw.2010.5668090
fatcat:voq3zktnnjcydkwfajjx4ak5pe
Advancing Fusion with Machine Learning Research Needs Workshop Report
2020
Journal of fusion energy
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The advent of powerful and dedicated computers specialized for large-scale parallel computation, as well as advances in statistical inference algorithms, have greatly enhanced the capabilities of these ...
The workshop drew on broad representation from both FES and ASCR scientific communities, and identified seven Priority Research Opportunities (PRO's) with high potential for advancing fusion energy. ...
Clearly, highly challenging data storage and I/O speed issues lie ahead. ...
doi:10.1007/s10894-020-00258-1
fatcat:pzk3vza7v5eytbsrg2htkr5ujq