Works (5)

Updated: April 8th, 2024 08:24

2020 article

HARP: Holistic Analysis for Refactoring Python-Based Analytics Programs

2020 ACM/IEEE 42ND INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING (ICSE 2020), pp. 506–517.

By: W. Zhou n, Y. Zhao*, G. Zhang n & X. Shen n

author keywords: machine learning program; computation graph; dynamic language; program analysis
TL;DR: HARP enables holistic analysis that spans across computation graphs and their hosting Python code and achieves it through a set of novel techniques: analytics-conscious speculative analysis to circumvent Python complexities, a unified representation augmented computation graphs to capture all dimensions of knowledge related with the holistic analysis, and conditioned feedback mechanism to allow risk-controlled aggressive analysis. (via Semantic Scholar)
Sources: Web Of Science, NC State University Libraries
Added: June 21, 2021

2018 conference paper

Bridging the Gap between Deep Learning and Sparse Matrix Format Selection

ACM SIGPLAN NOTICES, 53(1), 94–108.

By: Y. Zhao n, J. Li*, C. Liao* & X. Shen n

TL;DR: This work describes how to effectively bridge the gap between deep learning and the special needs of the pillar HPC problem through a set of techniques on matrix representations, deep learning structure, and cross-architecture model migrations. (via Semantic Scholar)
Sources: NC State University Libraries, NC State University Libraries
Added: October 16, 2018

2018 article

Overhead-Conscious Format Selection for SpMV-Based Applications

2018 32ND IEEE INTERNATIONAL PARALLEL AND DISTRIBUTED PROCESSING SYMPOSIUM (IPDPS), pp. 950–959.

By: Y. Zhao*, W. Zhou*, X. Shen* & G. Yiu*

author keywords: SpMV; High Performance Computing; Program Optimizations; Sparse Matrix Format; Prediction Model
TL;DR: A two-stage lazy-and-light scheme to help control the risks in the format predictions and at the same time maximize the overall format conversion benefits is proposed, which outperforms previous techniques significantly. (via Semantic Scholar)
Sources: Web Of Science, NC State University Libraries
Added: October 16, 2018

2017 conference paper

An infrastructure for HPC knowledge sharing and reuse

ACM SIGPLAN Notices, 52(8), 461–462.

By: Y. Zhao n, C. Liao* & X. Shen n

UN Sustainable Development Goal Categories
9. Industry, Innovation and Infrastructure (OpenAlex)
Sources: NC State University Libraries, NC State University Libraries
Added: August 6, 2018

2017 conference paper

EffiSha: A software framework for enabling efficient preemptive scheduling of GPU

ACM SIGPLAN Notices, 52(8), 3–16.

By: G. Chen n, Y. Zhao n, X. Shen n & H. Zhou n

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

Citation Index includes data from a number of different sources. If you have questions about the sources of data in the Citation Index or need a set of data which is free to re-distribute, please contact us.

Certain data included herein are derived from the Web of Science© and InCites© (2024) of Clarivate Analytics. All rights reserved. You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.