A Framework for Graph Machine Learning on Heterogeneous Architecture

被引：1
|
作者：
Lin, Yi-Chien [1 ]
Prasanna, Viktor [1 ]
机构：
[1] Univ Southern Calif, Los Angeles, CA USA
来源：
2023 IEEE 31ST ANNUAL INTERNATIONAL SYMPOSIUM ON FIELD-PROGRAMMABLE CUSTOM COMPUTING MACHINES, FCCM | 2023年
关键词：
D O I：
10.1109/FCCM57271.2023.00062
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
引用
收藏
页码：245 / 246
页数：2
相关论文
共 50 条
  • [1] A Machine Learning based Knowledge Graph Framework for Heterogeneous Power Grid Systems
    Zhang, Shujuan
    Zheng, GuoQiang
    Liu, Li
    Li, Longyue
    Li, JinZhong
    Wang, Xin
    2021 IEEE INTERNATIONAL CONFERENCE ON CONSUMER ELECTRONICS AND COMPUTER ENGINEERING (ICCECE), 2021, : 119 - 123
  • [2] Machine learning in a graph framework for subcortical segmentation
    Guo, Zhihui
    Kashyap, Satyananda
    Sonka, Milan
    Oguz, Ipek
    MEDICAL IMAGING 2017: IMAGE PROCESSING, 2017, 10133
  • [3] Machine Learning for a Heterogeneous Water Modeling Framework
    Frame, Jonathan M.
    Araki, Ryoko
    Bhuiyan, Soelem Aafnan
    Bindas, Tadd
    Rapp, Jeremy
    Bolotin, Lauren
    Deardorff, Emily
    Liu, Qiyue
    Haces-Garcia, Francisco
    Liao, Mochi
    Frazier, Nels
    Ogden, Fred L.
    JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION, 2025, 61 (01):
  • [4] Graph machine learning framework for depicting wavefunction on interface
    Wu, Ao
    Liu, Li
    Wang, Zifeng
    Pan, Shurong
    Huang, Jiangxue
    Huang, Qijun
    He, Jin
    Wang, Hao
    Chang, Sheng
    MACHINE LEARNING-SCIENCE AND TECHNOLOGY, 2023, 4 (04):
  • [5] Cymbalo: An Efficient Graph Processing Framework for Machine Learning
    Tian, Xinhui
    Xie, Biwei
    Zhan, Jianfeng
    2018 IEEE INT CONF ON PARALLEL & DISTRIBUTED PROCESSING WITH APPLICATIONS, UBIQUITOUS COMPUTING & COMMUNICATIONS, BIG DATA & CLOUD COMPUTING, SOCIAL COMPUTING & NETWORKING, SUSTAINABLE COMPUTING & COMMUNICATIONS, 2018, : 572 - 579
  • [6] AIgean: An Open Framework for Machine Learning on Heterogeneous Clusters
    Tarafdar, Naif
    Di Guglielmo, Giuseppe
    Harris, Philip C.
    Krupa, Jeffrey D.
    Loncar, Vladimir
    Rankin, Dylan S.
    Nhan Tran
    Wu, Zhenbin
    Shen, Qianfeng
    Chow, Paul
    28TH IEEE INTERNATIONAL SYMPOSIUM ON FIELD-PROGRAMMABLE CUSTOM COMPUTING MACHINES (FCCM), 2020, : 239 - 239
  • [7] A Unique Framework of Heterogeneous Augmentation Graph Contrastive Learning for Both Node and Graph Classification
    Shao, Qi
    Chen, Duxin
    Yu, Wenwu
    IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING, 2024, 11 (06): : 5818 - 5828
  • [8] Benchmarking Machine Learning Applications on Heterogeneous Architecture using Reframe
    Rae, Christopher
    Lee, Joseph K. L.
    Richings, James
    Weiland, Michele
    PROCEEDINGS OF THE 2024 ON 4TH WORKSHOP ON PERFORMANCE ENGINEERING, MODELLING, ANALYSIS, AND VISUALIZATION STRATEGY, PERMAVOST 2024, 2024, : 16 - 22
  • [9] LEARNING AND GENERATING SPATIAL CONCEPTS OF MODERNIST ARCHITECTURE VIA GRAPH MACHINE LEARNING
    Bauscher, Erik
    Dai, Anni
    Elshani, Diellza
    Wortmann, Thomas
    PROCEEDINGS OF THE 29TH INTERNATIONAL CONFERENCE OF THE ASSOCIATION FOR COMPUTER-AIDED ARCHITECTURAL DESIGN RESEARCH IN ASIA, CAADRIA 2024, VOL 1, 2024, : 159 - 168
  • [10] Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals
    Chen, Chi
    Ye, Weike
    Zuo, Yunxing
    Zheng, Chen
    Ong, Shyue Ping
    CHEMISTRY OF MATERIALS, 2019, 31 (09) : 3564 - 3572
12345