Sriram Lakshminarasimhan

Works (7)

Updated: July 5th, 2023 15:45

2014 article

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

Lakshminarasimhan, S., Zou, X., Boyuka, D. A., Pendse, S. V., Jenkins, J., Vishwanath, V., … Samatova, N. F. (2014, March 11). Cluster Computing.

By: S. Lakshminarasimhan n, X. Zou n, D. Boyuka n, S. Pendse n, J. Jenkins n, V. Vishwanath *, M. Papka *, S. Klasky *, N. Samatova n

author keywords: Exascale computing; Indexing; Query processing; Compression
topics (OpenAlex): Graph Theory and Algorithms; Advanced Data Storage Technologies; Distributed and Parallel Computing Systems
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

2012 article

Byte-precision level of detail processing for variable precision analytics

Jenkins, J., Schendel, E. R., Lakshminarasimhan, S., Boyuka, D. A., Rogers, T., Ethier, S., … Samatova, N. F. (2012, November 1). 2012 International Conference for High Performance Computing, Networking, Storage and Analysis.

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

topics (OpenAlex): Advanced Data Storage Technologies; Parallel Computing and Optimization Techniques; Algorithms and Data Compression
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

ISABELA for effective in situ compression of scientific data

Lakshminarasimhan, S., Shah, N., Ethier, S., Ku, S. H., Chang, C. S., Klasky, S., … Samatova, N. F. (2012, July 11). Concurrency and Computation Practice and Experience.

By: S. Lakshminarasimhan n, N. Shah n, S. Ethier *, S. Ku *, C. Chang *, S. Klasky *, R. Latham *, R. Ross *, N. Samatova n

author keywords: lossy compression; B-spline; in situ processing; data-intensive application; high performance computing
topics (OpenAlex): Advanced Data Storage Technologies; Computer Graphics and Visualization Techniques; Algorithms and Data Compression
TL;DR: The random nature of real‐valued scientific datasets renders lossless compression routines ineffective, and these techniques also impose significant overhead during decompression, making them unsuitable for data analysis and visualization, which require repeated data access. (via Semantic Scholar)
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Source: Web Of Science
Added: August 6, 2018

2012 article

Multi-level Layout Optimization for Efficient Spatio-temporal Queries on ISABELA-compressed Data

Gong, Z., Lakshminarasimhan, S., Jenkins, J., Kolla, H., Ethier, S., Chen, J., … Samatova, N. F. (2012, May 1).

By: Z. Gong n, S. Lakshminarasimhan n, J. Jenkins n, H. Kolla *, S. Ethier *, J. Chen*, R. Ross *, S. Klasky*, N. Samatova n

topics (OpenAlex): Advanced Data Storage Technologies; Advanced Database Systems and Queries; Distributed and Parallel Computing Systems
TL;DR: This work presents a parallel query-processing engine that can handle both range queries and queries with spatio-temporal constraints, on B-spline compressed data with user-controlled accuracy, and shows it to be efficient with respect to storage, computation, and I/O compared to existing database technologies optimized for query processing on scientific data. (via Semantic Scholar)
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Source: Web Of Science
Added: August 6, 2018

2012 article

On the path to sustainable, scalable, and energy-efficient data analytics: Challenges, promises, and future directions

Lakshminarasimhan, S., Kumar, P., Liao, N. W.-keng, Choudhary, A., Kumar, V., & Samatova, N. F. (2012, June 1).

By: S. Lakshminarasimhan n, P. Kumar *, N. Liao *, A. Choudhary *, V. Kumar * & N. Samatova n

topics (OpenAlex): Advanced Data Storage Technologies; Parallel Computing and Optimization Techniques; Distributed systems and fault tolerance
TL;DR: This paper proposes a number of future directions that could be pursued on the path to sustainable data analytics at scale, including transformative approaches to efficient data reduction, analytics-driven query processing, scalable analytical kernels, approximate analytics, among others. (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

report

Compressing the Incompressible with ISABELA: In-situ Reduction of Spatio-Temporal Data

Lakshminarasimhan, S., Shah, N., Ethier, S. J., Klasky, S., Latham, R., Ross, R., & N.F., S. In Technical Report- Not held in TRLN member libraries.

By: S. Lakshminarasimhan, N. Shah, S. Ethier, S. Klasky, R. Latham, R. Ross, S. N.F.

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

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