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Kyle Schochenmaier

dblp:96/1805 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2006
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Storage systems · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Storage systems
network-attached storage
0.112006
Storage challenge - Trading memory for disk: using parallel access to fast InfiniBand disk arrays for large computational chemistry applications · SC 2006
Storage systems › distributed storage
parallel storage system
0.112006
Storage challenge - Trading memory for disk: using parallel access to fast InfiniBand disk arrays for large computational chemistry applications · SC 2006
Storage systems
out-of-core computation
0.012006
Storage challenge - Trading memory for disk: using parallel access to fast InfiniBand disk arrays for large computational chemistry applications · SC 2006
YearPublicationVenuePosition
2006 Storage challenge - Trading memory for disk: using parallel access to fast InfiniBand disk arrays for large computational chemistry applications
abstract
We present a novel approach for using high performance network attached parallel storage for out-of-core computation. Our approach utilizes many parallel disks and storage controllers with a near 1:1 ratio of compute nodes to storage servers. This, when combined with 30 Gigabit 12X InfiniBand interconnects, allows remote storage subsystem bandwidth to reach the same performance level as local memory-cache file I/O performance. This combination allows computational chemistry application problem sizes which require more than 100GB of intermediate data to store this data on disk without the disk I/O subsystem becoming the limiting factor. With sequential storage access speeds on the same order of magnitude as main memory performance, this allows out-of-core computation to become practical due to disk storage size being several orders of magnitude cheaper per GB than main memory storage.
Troy Benjegerdes, Brett M. Bode, Kyle Schochenmaier
SC3