Works (7)

Updated: July 5th, 2023 15:43

2015 article

Parallel In Situ Detection of Connected Components in Adaptive Mesh Refinement Data

2015 15TH IEEE/ACM INTERNATIONAL SYMPOSIUM ON CLUSTER, CLOUD AND GRID COMPUTING, pp. 302–312.

By: X. Zou n, K. Wu*, D. Boyuka n, D. Martin*, S. Byna*, H. Tang n, K. Bansal n, T. Ligocki*, H. Johansen*, N. Samatova n

TL;DR: The first connected component detection methodology for structured AMR that is applicable in a parallel, in situ context is presented, incorporating an multi-phase AMR-aware communication pattern that synchronizes connectivity information across the AMR hierarchy. (via Semantic Scholar)
UN Sustainable Development Goal Categories
9. Industry, Innovation and Infrastructure (OpenAlex)
Source: Web Of Science
Added: August 6, 2018

2015 article

The Hyperdyadic Index and Generalized Indexing and Query with PIQUE

PROCEEDINGS OF THE 27TH INTERNATIONAL CONFERENCE ON SCIENTIFIC AND STATISTICAL DATABASE MANAGEMENT.

By: D. Boyuka n, H. Tang n, K. Bansal n, X. Zou n, S. Klasky* & N. Samatova n

TL;DR: PIQUE factors out commonalities in indexing, employing algorithmic/data structure "plugins" to mix orthogonal indexing concepts such as FastBit compressed bitmaps with ALACRITY binning, all within one framework. (via Semantic Scholar)
Source: Web Of Science
Added: August 6, 2018

2014 journal article

DIRAQ: scalable in situ data- and resource-aware indexing for optimized query performance

CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS, 17(4), 1101–1119.

author keywords: Exascale computing; Indexing; Query processing; Compression
TL;DR: DIRAQ is proposed, a parallel in situ, in network data encoding and reorganization technique that enables the transformation of simulation output into a query-efficient form, with negligible runtime overhead to the simulation run. (via Semantic Scholar)
Source: Web Of Science
Added: August 6, 2018

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 article

PARLO: PArallel Run-time Layout Optimization for Scientific Data Explorations with Heterogeneous Access Patterns

PROCEEDINGS OF THE 2013 13TH IEEE/ACM INTERNATIONAL SYMPOSIUM ON CLUSTER, CLOUD AND GRID COMPUTING (CCGRID 2013), pp. 343–351.

Source: Web Of Science
Added: August 6, 2018

2012 conference paper

Byte-precision level of detail processing for variable precision analytics

International conference for high performance computing networking.

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

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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