HEXO: Offloading HPC Compute-Intensive Workloads on Low-Cost, Low-Power Embedded Systems

被引:8
|
作者
Olivier, Pierre [1 ]
Mehrab, A. K. M. Fazla [1 ]
Lankes, Stefan [2 ]
Karaoui, Mohamed Lamine [1 ]
Lyerly, Robert [1 ]
Ravindran, Binoy [1 ]
机构
[1] Virginia Tech, Blacksburg, VA 24061 USA
[2] Rhein Westfal TH Aachen, Aachen, Germany
关键词
heterogeneous ISAs; unikernels; migration; offloading;
D O I
10.1145/3307681.3325408
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
OS-capable embedded systems exhibiting a very low power consumption are available at an extremely low price point. It makes them highly compelling in a datacenter context. In this paper we show that sharing long-running, compute-intensive datacenter HPC workloads between a server machine and one or a few connected embedded boards of negligible cost and power consumption can bring significant benefits in terms of consolidation. Our approach, named Heterogeneous EXecution Offloading (HEXO), selectively offloads Virtual Machines (VMs) from server class machines to embedded boards. Our design tackles several challenges. We address the Instruction Set Architecture (ISA) difference between typical servers (x86) and embedded systems (ARM) through hypervisor and guest OS-level support for heterogeneous-ISA runtime VM migration. We cope with the low amount of resources in embedded systems by using lightweight VMs: unikernels. VMs are offloaded based on an estimation of the slowdown expected from running on a given board. We build a prototype of HEXO and demonstrate significant increase in throughput (up to 67%) and energy efficiency (up to 56%) over a set of macro-benchmarks running datacenter compute-intensive jobs.
引用
收藏
页码:85 / 96
页数:12
相关论文
共 50 条
  • [21] ELECTRONIC LOCK BOASTS LOW-COST AND LOW-POWER
    SOKOL, BJ
    ELECTRONICS, 1981, 54 (14): : 127 - 127
  • [22] A LOW-COST, LOW-POWER RESONANT PRESSURE SENSOR
    LANGDON, RM
    GEC JOURNAL OF RESEARCH, 1989, 7 (01): : 28 - 33
  • [23] Low-Power Low-Cost Acoustic Underwater Modem
    Renner, Christian
    Gabrecht, Alexander
    Meyer, Benjamin
    Osterloh, Christoph
    Maehle, Erik
    QUANTITATIVE MONITORING OF THE UNDERWATER ENVIRONMENT, 2016, 6 : 59 - 65
  • [24] Performance Analysis of HPC Applications on Low-Power Embedded Platforms
    Stanisic, Luka
    Videau, Brice
    Cronsioe, Johan
    Degomme, Augustin
    Marangozova-Martin, Vania
    Legrand, Arnaud
    Mehaut, Jean-Francois
    DESIGN, AUTOMATION & TEST IN EUROPE, 2013, : 475 - 480
  • [25] A proposal of low-cost and low-power embedded wireless image sensor node for IoT applications
    Tresanchez, M.
    Pujol, A.
    Palleja, T.
    Martinez, D.
    Clotet, E.
    Palacin, J.
    15TH INTERNATIONAL CONFERENCE ON MOBILE SYSTEMS AND PERVASIVE COMPUTING (MOBISPC 2018) / THE 13TH INTERNATIONAL CONFERENCE ON FUTURE NETWORKS AND COMMUNICATIONS (FNC-2018) / AFFILIATED WORKSHOPS, 2018, 134 : 99 - 106
  • [26] DESIGNING LOW-POWER EMBEDDED SYSTEMS
    Gelmuda, Wojciech
    Kos, Andrzej
    ELECTRONICS WORLD, 2012, 118 (1915): : 18 - 20
  • [27] An Experimental Evaluation of Datacenter Workloads On Low-Power Embedded Micro Servers
    Zhao, Yiran
    Li, Shen
    Hu, Shaohan
    Wang, Hongwei
    Yao, Shuochao
    Shao, Huajie
    Abdelzaher, Tarek
    PROCEEDINGS OF THE VLDB ENDOWMENT, 2016, 9 (09): : 696 - 707
  • [28] Signal Processing for Low-Power and Low-Cost Radar Systems in Bicycle Safety Applications
    Dorn, Christian
    Kurin, Thomas
    Erhardt, Stefan
    Lurz, Fabian
    Hagelauer, Amelie
    2022 IEEE TOPICAL CONFERENCE ON WIRELESS SENSORS AND SENSOR NETWORKS (WISNET), 2022, : 11 - 13
  • [29] A Low-Cost Scalable Voltage-Frequency Adjustor for Implementing Low-Power Systems
    Cheng, Ching-Hwa
    Hsu, Sheng-Wei
    Guo, Jiun-In
    2013 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS), 2013, : 655 - 658
  • [30] CNN hardware acceleration on a low-power and low-cost APSoC
    Meloni, Paolo
    Garufi, Antonio
    Deriu, Gianfranco
    Carreras, Marco
    Loi, Daniela
    2019 CONFERENCE ON DESIGN AND ARCHITECTURES FOR SIGNAL AND IMAGE PROCESSING (DASIP), 2019, : 7 - 12