Abstract
The deluge of data from scientific instruments (SNS, LHC), experiments (DZero) and observations (SDSS) will soon surpass the ability of storage systems to store and retrieve data in a reliable and cost-effective manner. While the capacity, performance and the mean time to failure (MTTF) of a single disk has been improving, large-scale storage systems and parallel file systems (PFS) can comprise tens of thousands of drives, thus bringing down the overall mean time to data loss (MTTDL) of the entire system to unacceptably low levels. For example, the Lustre-based Spider PFS of the Jaguar supercomputer (No. 3 machine on the Top500 list) comprises 10,000+ disks. An exaflop machine in 2018 is projected to host hundreds of thousands of drives to support the desired I/O throughput.
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Notes
- 1.
Context funneling uses advanced features of the Fermi architecture to execute concurrent kernels, which must be launched from the same context [37].
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Acknowledgement
This research was supported in part by the National Science Foundation under Grants CCF-0746832, CNS-1016793, and CNS-1016408, and used the resources of, the Oak Ridge Leadership Computing Facility, located in the National Center for Computational Sciences at ORNL, which is managed by UT Battelle, LLC for the U.S. DOE (under the contract No. DE-AC05-00OR22725).
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Khasymski, A., Rafique, M., Butt, A., Vazhkudai, S., Nikolopoulos, D. (2015). Realizing Accelerated Cost-Effective Distributed RAID. In: Khan, S., Zomaya, A. (eds) Handbook on Data Centers. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-2092-1_25
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