Eric R. Schendel

Works (5)

Updated: July 5th, 2023 15:45

2014 article

Transparent In Situ Data Transformations in ADIOS

2014 14TH IEEE/ACM INTERNATIONAL SYMPOSIUM ON CLUSTER, CLOUD AND GRID COMPUTING (CCGRID), pp. 256–266.

By: D. Boyuka n, S. Lakshminarasimhan, X. Zou n, Z. Gong n, J. Jenkins n, E. Schendel n, N. Podhorszki *, Q. Liu *, S. Klasky *, N. Samatova n

TL;DR: This work develops an in situ data transformation framework in the ADIOS I/O middleware with a "plug in" interface, thus greatly simplifying both the deployment and use of data transform services in scientific applications. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Source: Web Of Science
Added: August 6, 2018

2013 conference paper

A generic high-performance method for deinterleaving scientific data

Euro-par 2013 parallel processing, 8097, 571–582.

By: E. Schendel n, S. Harenberg n, H. Tang n, V. Vishwanath *, M. Papka * & N. Samatova*

TL;DR: To the best of the knowledge, this is the first deinterleaving method that exploits data cache prefetching, reduces memory accesses, and optimizes the use of complete cache line writes. (via Semantic Scholar)
UN Sustainable Development Goal Categories
7. Affordable and Clean Energy (OpenAlex)
Source: NC State University Libraries
Added: August 6, 2018

2012 conference paper

Byte-precision level of detail processing for variable precision analytics

International conference for high performance computing networking.

By: J. Jenkins n, E. Schendel n, S. Lakshminarasimhan n, D. Boyuka n, T. Rogers n, S. Ethier *, R. Ross *, S. Klasky*, N. Samatova n

TL;DR: A precision level of detail (APLOD) library is developed, which partitions double-precision datasets along user-defined byte boundaries, and finds a strong applicability for the use of varying degrees of precision to reduce the cost of analyzing extreme-scale data. (via Semantic Scholar)
Source: NC State University Libraries
Added: August 6, 2018

2012 article

ISOBAR Preconditioner for Effective and High-throughput Lossless Data Compression

2012 IEEE 28TH INTERNATIONAL CONFERENCE ON DATA ENGINEERING (ICDE), pp. 138–149.

By: E. Schendel n, Y. Jin n, N. Shah n, J. Chen*, C. Chang *, S. Ku *, S. Ethier *, S. Klasky * ...

TL;DR: The In-Situ Orthogonal Byte Aggregate Reduction Compression (ISOBAR-compression) methodology is introduced as a preconditioner of loss less compression to identify and optimize the compression efficiency and throughput of hard-to-compress datasets. (via Semantic Scholar)
Source: Web Of Science
Added: August 6, 2018

conference paper

ALACRITY: Analytics-driven lossless data compression for rapid in-situ indexing, storing, and querying

Jenkins, J., Arkatkar, I., Lakshminarasimhan, S., Boyuka, D. A., Schendel, E. R., Shah, N., … Samatova, N. F. Transactions on large-scale data- and knowledge- centered systems x: special issue on database- and expert-systems applications, 8220, 95–114.

By: J. Jenkins, I. Arkatkar, S. Lakshminarasimhan, D. Boyuka, E. Schendel, N. Shah, S. Ethier, C. Chang ...

Source: NC State University Libraries
Added: August 6, 2018

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