Works Published in 2023
Displaying all 8 works
Sorted by most recent date added to the index first, which may not be the same as publication date order.
2023 journal article
CompressGraph: Efficient Parallel Graph Analytics with Rule-Based Compression
Proceedings of the ACM on Management of Data.
TL;DR:
CompressGraph is developed, an efficient rule-based graph analytics engine that leverages data redundancy in graphs to achieve both performance boost and space reduction for common graph applications.
(via Semantic Scholar)
Source: ORCID
Added: February 2, 2024
2023 article
BitGNN: Unleashing the Performance Potential of Binary Graph Neural Networks on GPUs
PROCEEDINGS OF THE 37TH INTERNATIONAL CONFERENCE ON SUPERCOMPUTING, ACM ICS 2023, pp. 264–276.
author keywords: graph neural networks; binarized GNN; bit manipulation; GPU; sparse matrix
TL;DR:
This work redesigns thebinary GNN inference backend from the efficiency perspective by proposing a series of abstractions and techniques to map binary GNNs and their computations best to fit the nature of bit manipulations on GPUs.
(via Semantic Scholar)
arxiv.org (repository)
Sources: Web Of Science, ORCID
Added: January 29, 2024
2023 article
SpecPMT: Speculative Logging for Resolving Crash Consistency Overhead of Persistent Memory
PROCEEDINGS OF THE 28TH ACM INTERNATIONAL CONFERENCE ON ARCHITECTURAL SUPPORT FOR PROGRAMMING LANGUAGES AND OPERATING SYSTEMS, VOL 2, ASPLOS 2023, pp. 762–777.
author keywords: persistent memory; transaction; logging; microarchitecture
TL;DR:
This paper introduces speculative logging, a new method that forgoes most memory fences and reduces data persistence overhead by logging data values early, which enables a novel persistent transaction model, speculatively persistent memory transactions (SpecPMT).
(via Semantic Scholar)
Sources: Web Of Science, ORCID
Added: November 6, 2023
2023 journal article
Expanding the Edge: Enabling Efficient Winograd CNN Inference With Deep Reuse on Edge Device
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 35(10), 10181–10196.
author keywords: CNN; deep reuse; inference; winograd
TL;DR:
A new inference method, called DREW, is proposed, which combines deep reuse with Winograd for further accelerating CNNs, and reduces the number of convolution operations to 10% of the original operations, thus achieving up to 60% energy-efficiency benefits than the original Winog Rad inference.
(via Semantic Scholar)
Sources: Web Of Science, ORCID
Added: October 23, 2023
2023 article
Reconciling Selective Logging and Hardware Persistent Memory Transaction
2023 IEEE INTERNATIONAL SYMPOSIUM ON HIGH-PERFORMANCE COMPUTER ARCHITECTURE, HPCA, pp. 664–676.
TL;DR:
An ISA extension is presented that enables selective logging for hardware persistent memory transactions for the first time and outperforms the state-of-the-art hardware counterpart by 1.8× on average.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
11. Sustainable Cities and Communities
(Web of Science)
Sources: Web Of Science, ORCID
Added: June 5, 2023
2023 journal article
Accelerating matrix-centric graph processing on GPUs through bit-level optimizations
JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING, 177, 53–67.
author keywords: GraphBLAS; Bit manipulation; GPU; Sparse matrix; Deep reinforcement learning
Sources: Web Of Science, ORCID
Added: April 11, 2023
2023 journal article
Automated Translation of Functional Big Data similar to eries to SQL
PROCEEDINGS OF THE ACM ON PROGRAMMING LANGUAGES-PACMPL, 7(OOPSLA).
author keywords: program synthesis; source-to-source compiler; query optimization
TL;DR:
Results show that (1) most RDD queries can be translated to SQL, (2) the tool is very effective at automating this translation, and (3) performing this translation offers significant performance benefits.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
11. Sustainable Cities and Communities
(Web of Science)
Sources: ORCID, Web Of Science
Added: April 8, 2023
2023 journal article
Survey: Exploiting Data Redundancy for Optimization of Deep Learning
ACM COMPUTING SURVEYS, 55(10).
author keywords: Data redundancy; representation redundancy; deep neural network; convolutional neural network; transformer
TL;DR:
This article surveys hundreds of recent papers on data redundancy, introduces a novel taxonomy to put the various techniques into a single categorization framework, and offers a comprehensive description of the main methods used for exploiting data redundancy in improving multiple kinds of DNNs on data.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
3. Good Health and Well-being
(Web of Science)
Sources: Web Of Science, ORCID
Added: March 6, 2023
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