Wenzhao Zhang

Works (5)

Updated: July 5th, 2023 15:38

2016 article

AMRZone: A Runtime AMR Data Sharing Framework For Scientific Applications

2016 16TH IEEE/ACM INTERNATIONAL SYMPOSIUM ON CLUSTER, CLOUD AND GRID COMPUTING (CCGRID), pp. 116–125.

By: W. Zhang n, H. Tang n, S. Harenberg n, S. Byna *, X. Zou n, D. Devendran*, D. Martin *, K. Wu * ...

TL;DR: AMRZone's performance and scalability are even comparable with existing state-of-the-art work when tested over uniform mesh data with up to 16384 cores, in the best case, the framework achieves a 46% performance improvement. (via Semantic Scholar)
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Source: Web Of Science
Added: August 6, 2018

2016 conference paper

Exploring memory hierarchy and network topology for runtime AMR data sharing across scientific applications

2016 IEEE International Conference on Big Data (Big Data), 1359–1366.

By: W. Zhang n, H. Tang *, S. Ranshous n, S. Byna *, D. Martin *, K. Wu *, B. Dong *, S. Klasky*, N. Samatova n

TL;DR: Results show the proposed framework's spatial access pattern detection and prefetching methods demonstrate about 26% performance improvement for client analytical processes and the framework's topology-aware data placement can improve overall data access performance by up to 18%. (via Semantic Scholar)
Source: NC State University Libraries
Added: August 6, 2018

2016 article

In situ Storage Layout Optimization for AMR Spatio-temporal Read Accesses

PROCEEDINGS 45TH INTERNATIONAL CONFERENCE ON PARALLEL PROCESSING - ICPP 2016, pp. 406–415.

By: H. Tang n, S. Byna *, S. Harenberg n, W. Zhang n, X. Zou n, D. Martin *, B. Dong *, D. Devendran* ...

TL;DR: This work develops an in situ data layout optimization framework that automatically selects from a set of candidate layouts based on a performance model, and reorganizes the data before writing to storage to enable efficient AMR read accesses. (via Semantic Scholar)
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Source: Web Of Science
Added: August 6, 2018

2016 article

Usage Pattern-Driven Dynamic Data Layout Reorganization

2016 16TH IEEE/ACM INTERNATIONAL SYMPOSIUM ON CLUSTER, CLOUD AND GRID COMPUTING (CCGRID), pp. 356–365.

By: H. Tang n, S. Byna *, S. Harenberg n, X. Zou n, W. Zhang n, K. Wu *, B. Dong *, O. Rubel * ...

TL;DR: This work proposes a framework that dynamically recognizes the data usage patterns, replicates the data of interest in multiple reorganized layouts that would benefit common read patterns, and makes runtime decisions on selecting a favorable layout for a given read pattern. (via Semantic Scholar)
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4. Quality Education (OpenAlex)
Source: Web Of Science
Added: August 6, 2018

2015 article

Exploring Memory Hierarchy to Improve Scientific Data Read Performance

2015 IEEE INTERNATIONAL CONFERENCE ON CLUSTER COMPUTING - CLUSTER 2015, pp. 66–69.

By: W. Zhang n, H. Tang n, X. Zou n, S. Harenberg n, Q. Liu  n, S. Klasky n, N. Samatova n

author keywords: scientific data; read contention; memory hierarchy; SSD
TL;DR: This paper proposes a framework that exploits the memory hierarchy resource to address the read contention issues involved with SSDs and achieves up to 50% read performance improvement when tested on datasets from real-world scientific simulations. (via Semantic Scholar)
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Source: Web Of Science
Added: August 6, 2018

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