Bizarim
Menu

Research library

Search papers on equipment connectivity, quality inspection, production analysis, and manufacturing work.

Search and filter

Paper list

T13. Edge AI, streaming inference, and resource scheduling

Running models near the machine under limited compute and latency budgets.

  1. T13-9Candidate approach

    INFaaS

    Authors
    Francisco Romero, Qian Li, Neeraja J. Yadwadkar, Christos Kozyrakis
    Year
    2021
    Venue
    USENIX ATC 2021, pp. 397-411

    Korean review of T13-9

  2. T13-10Candidate approach

    Orca: A Distributed Serving System for Transformer-Based Generative Models

    Authors
    Gyeong-In Yu, Joo Seong Jeong, Geon-Woo Kim, Soojeong Kim, Byung-Gon Chun
    Year
    2022
    Venue
    USENIX OSDI 2022, pp. 521-538

    Korean review of T13-10

  3. T13-11Candidate approach

    Efficient Memory Management for Large Language Model Serving with PagedAttention

    Authors
    Woosuk Kwon, Zhuohan Li, Siyuan Zhuang, Ying Sheng, Lianmin Zheng, Cody Hao Yu, Joseph E. Gonzalez, Hao Zhang, Ion Stoica
    Year
    2023
    Venue
    ACM SOSP 2023, pp. 611-626

    Korean review of T13-11

  4. T13-12Candidate approach

    Gandiva: Introspective Cluster Scheduling for Deep Learning

    Authors
    Wencong Xiao, Romil Bhardwaj, Ramachandran Ramjee, Muthian Sivathanu, Nipun Kwatra, Zhenhua Han, Pratyush Patel, Xuan Peng, Hanyu Zhao, Quanlu Zhang, Fan Yang, Lidong Zhou
    Year
    2018
    Venue
    USENIX OSDI 2018, pp. 595-610

    Korean review of T13-12

  5. T13-13Candidate approach

    Tiresias: A GPU Cluster Manager for Distributed Deep Learning

    Authors
    Juncheng Gu, Mosharaf Chowdhury, Kang G. Shin, Yibo Zhu, Myeongjae Jeon, Junjie Qian, Hongqiang Liu, Chuanxiong Guo
    Year
    2019
    Venue
    USENIX NSDI 2019, pp. 485-500

    Korean review of T13-13

  6. T13-14Candidate approach

    AntMan: Dynamic Scaling on GPU Clusters for Deep Learning

    Authors
    Wencong Xiao, Shiru Ren, Yong Li, Yang Zhang, Pengyang Hou, Zhi Li, Yihui Feng, Wei Lin, Yangqing Jia
    Year
    2020
    Venue
    USENIX OSDI 2020, pp. 533-548

    Korean review of T13-14

  7. T13-15Candidate approach

    Heterogeneity-Aware Cluster Scheduling Policies for Deep Learning Workloads

    Authors
    Deepak Narayanan, Keshav Santhanam, Fiodar Kazhamiaka, Amar Phanishayee, Matei Zaharia
    Year
    2020
    Venue
    USENIX OSDI 2020, pp. 481-498

    Korean review of T13-15

  8. T13-16Candidate approach

    Pollux: Co-adaptive Cluster Scheduling for Goodput-Optimized Deep Learning

    Authors
    Aurick Qiao, Sang Keun Choe, Suhas Jayaram Subramanya, Willie Neiswanger, Qirong Ho, Hao Zhang, Gregory R. Ganger, Eric P. Xing
    Year
    2021
    Venue
    USENIX OSDI 2021, pp. 1-18

    Korean review of T13-16

From research to product use

Operating capabilities, pilots, and technologies in development are identified separately.

View technology