Hsin-Hsuan Sung
College of Engineering
Works (6)
Updated: November 19th, 2024 05:02
2024 journal article
Enabling Efficient Deep Learning on MCU With Transient Redundancy Elimination
IEEE TRANSACTIONS ON COMPUTERS, 73(12), 2649–2663.
author keywords: Microcontrollers; Redundancy; Vectors; Transient analysis; Accuracy; Computational modeling; Convolution; MCU; deep learning; compiler optimization; edge AI; heterogeneous systems; approximate computing
Sources: Web Of Science, ORCID, NC State University Libraries
Added: November 7, 2024
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, NC State University Libraries
Added: April 11, 2023
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)
open access via arxiv.org (repository)
Sources: Web Of Science, NC State University Libraries, ORCID
Added: January 29, 2024
2022 article
Bit-GraphBLAS: Bit-Level Optimizations of Matrix-Centric Graph Processing on GPU
2022 IEEE 36TH INTERNATIONAL PARALLEL AND DISTRIBUTED PROCESSING SYMPOSIUM (IPDPS 2022), pp. 515–525.
TL;DR:
A two-level representation named Bit-Block Compressed Sparse Row (B2SR) is proposed and a series of optimizations to the graph operations on B2SR by leveraging the intrinsics of modern GPUs are presented.
(via Semantic Scholar)
Sources: Web Of Science, NC State University Libraries
Added: September 29, 2022
2022 article
Brief Industry Paper: Enabling Level-4 Autonomous Driving on a Single $1k Off-the-Shelf Card
2022 IEEE 28TH REAL-TIME AND EMBEDDED TECHNOLOGY AND APPLICATIONS SYMPOSIUM (RTAS), pp. 297–300.
TL;DR:
It is shown that it is feasible to enable full leve1-4 autonomous driving workloads on a single off-the-shelf card (Jetson AGX Xavier) for less than 1.1 times less than the state-of- the-art systems, while meeting all the requirements of latency.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
9. Industry, Innovation and Infrastructure
(OpenAlex)
11. Sustainable Cities and Communities
(Web of Science)
Sources: Web Of Science, NC State University Libraries
Added: April 17, 2023
2021 article
Brief Industry Paper: Towards Real-Time 3D Object Detection for Autonomous Vehicles with Pruning Search
2021 IEEE 27TH REAL-TIME AND EMBEDDED TECHNOLOGY AND APPLICATIONS SYMPOSIUM (RTAS 2021), pp. 425–428.
author keywords: 3D object detection; real-time; point cloud
TL;DR:
It is demonstrated in experiments that for the first time, the pruning search framework can achieve real-time 3D object detection on mobile with state-of-the-art detection performance.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
3. Good Health and Well-being
(Web of Science)
Sources: Web Of Science, NC State University Libraries
Added: November 29, 2021
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