Half-day virtual workshop at MICRO 2021

Workshop Date: Friday, October 22, 2021, 10:00 am – 1:00 pm (EDT)

Many platforms, from data centers to edge devices, deploy multiple DNNs to provide high-quality results for diverse applications in the domains of computer vision, speech, language, and so on. In addition, because some applications rely on multi-DNN pipelines performing different tasks, DNN workloads are becoming more diverse and heterogeneous. Supporting inferences of such diverse and heterogeneous DNN workloads with high energy efficiency and low latency is becoming a great challenge since the major approach to achieve inference efficiency is to specialize architecture, compiler, and systems for a small set of target DNN models within the same domain. In addition to such performance and efficiency, multimodel DNN workloads introduce new challenges such as security and privacy. Therefore, this workshop will explore innovations to efficiently and safely support multi-model DNN workloads from each of the three areas: architecture, compiler, and system. We solicit papers in the research fields listed below.

Topics of Interest

  • Heterogeneous hardware architectures to concurrent execution of multiple DNN models
  • Reconfigurable accelerator architectures (CGRA-style, FPGA, etc.) to adapt to different DNN models
  • Compiler runtime for multi-DNN workloads on heterogeneous or reconfigurable hardware architectures
  • End-to-end compilation flow and optimization techniques targeting multi-DNN workloads on heterogeneous or reconfigurable hardware architectures
  • Design automation tools for heterogeneous or reconfigurable hardware architectures targeting multi-DNN workloads
  • Techniques in each of architecture, compiler, and system domains to enhance security and privacy when a platform runs a multi-model DNN workload in multi-tenant style

Author Information

Important Dates

  • Submission deadline: Sep 22, 2021 (AOE)
  • Notification: October 8, 2021 (AOE)
  • Camera-ready: October 14, 2021 (AOE)
  • Workshop date: October 22, 2021 (10:00 am – 1:00 pm EDT)

Program Committee

  • Hsien-Hsin Sean Lee (Facebook)
  • Jangwoo Kim (SNU)
  • Zhiru Zhang (Cornell)
  • Amir Yazdanbakhsh (Google)
  • Minsoo Rhu (KAIST)
  • Jongse Park (KAIST)
  • Hardik Sharma (Google)
  • Jie Wang (AWS)
  • Joel Hestness (Cerebras Systems)
  • Divya Mahajan (Microsoft Research)

For further information, please refer to our website (https://research.fb.com/arch-comp-sys-support-for-multi-model-dnn-workshop/) or email Hyoukjun Kwon (hyoukjunkwon@fb.com).

Architecture, Compiler, and System Support for Multi-model DNN Workloads (ACSMD) Workshop at MICRO 2021