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A3D3 Kick-off meeting

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Description

The National Science Foundation (NSF), under the Harnessing the Data Revolution (HDR) program, is providing funding to establish the Accelerated AI Algorithms for Data-Driven Discovery (A3D3) Institute, a multi-disciplinary and geographically distributed entity with the primary mission to lead a paradigm shift in the application of real-time artificial intelligence (AI) at scale to advance scientific knowledge and accelerate discovery. 

The A3D3 Institute was funded on 1 October 2021, and is ramping up its activities. This kickoff workshop brings together members and collaborators of the A3D3 to develop the activities which will be pursued in the five years of the Institute. The goal, motivation, deliverables, milestones, and timeline will be identified for each activity. We should leave the workshop with a comprehensive Project Execution Plan. This plan will be used to develop the Management Plan requested by the NSF due mid of December. 

A3D3 Kick-off meeting
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  • Monday 8 November
    • 11:00 → 11:07
      Introduction 7m
      Speaker: Shih-Chieh Hsu (University of Washington Seattle (US))
      gslide
    • 11:10 → 11:17
      Logo and Website 7m
      Speakers: Miaoyuan Liu (Purdue University (US)), Philip Coleman Harris (Massachusetts Inst. of Technology (US))
      logo
      website
    • 11:25 → 12:10
      Lightning talks
    • 12:20 → 13:25
      HEP
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      Convener: Miaoyuan Liu (Purdue University (US))
      • 12:20
        Graph neural networks in HEP 15m

        10 mins talk + 5 mins discussion

        Speaker: Yongbin Feng (Fermi National Accelerator Lab. (US))
        GNN_Overview_A3D3.pdf
      • 12:35
        Anomaly detection in HEP 15m

        10 mins talk + 5 mins discussion

        Speaker: Sang Eon Park (Massachusetts Inst. of Technology (US))
        A3D3 Final 1.pdf
      • 12:50
        SPVCNN applications in HEP 15m

        10 mins talk + 5 mins discussion

        Speaker: Alexander Joseph Schuy (University of Washington (US))
        SPVCNN slides
    • 12:20 → 13:10
      MMA
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      Convener: Michael Coughlin (University of Minnesota)
    • 12:20 → 13:10
      Neuroscience
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      Convener: Amy Orsborn
    • 13:10 → 14:00
      HAC
      Convener: Pan Li
      • 13:10
        Intro 2m

        HAC (Hardware and Algorithm co-development) is one main research direction of A3D3, where the goal is to study the state-of-the-art AI hardware and algorithms for scientific applications. In this session, we have four talks that include AI algorithm/hardware design for physical applications, and efficient compilation tools for AI hardware automatic design.

        Speaker: Pan Li (Purdue)
      • 13:12
        Point cloud methods for science 12m
        Speaker: Zhijian Liu (MIT)
        20211108 - A3D3.pdf
      • 13:24
        GNN-for-Science 12m
        Speaker: Siqi Miao (Purdue)
        tau3mu-siqi[17973].pdf
      • 13:36
        ScaleHLS 12m
        Speaker: Hanchen Ye (UIUC)
        A3D3_ScaleHLS_Slides_Hanchen[17518].pdf
      • 13:48
        HLS4ML 12m
        Speaker: Dylan Rankin (MIT)
        a3d3_hac_dsr_01Nov21 (1).pdf
  • Tuesday 9 November
    • 11:00 → 12:40
      Targeted and heterogeneous systems
      Conveners: Eli Shlizerman, Javier Mauricio Duarte (Univ. of California San Diego (US))
      • 11:00
        Intro 5m

        Targeted systems: hardware-based, edge devices, on-sensor, including FPGA, ASIC, or other technology used for monitoring, instrument control, data selection, or data processing often in real-time or with very low latency.

        Heterogenous systems: CPUs + coprocessors, high-throughput data processing, may include HPCs, cloud resources, asynchronous communication, as-a-service.

        This section will give a brief overview of the different systems we target in HEP, neuroscience, and MMA with a look toward how we can develop common tools and techniques. Each talk will address:

        1. What the targeted/heterogeneous systems look like (hardware specifications, constraints, etc.)
        2. How we currently "program" these targeted systems (including the use of AI algorithms and tool flows like hls4ml)
        3. Thoughts for improving workflows, infrastructure, which can be developed in common
        Speakers: Eli Shlizerman, Javier Mauricio Duarte (Univ. of California San Diego (US))
      • 11:05
        HEP: Level-1 trigger (FPGA) + On-detector readout (ASIC) 15m
        Speaker: Daniel Diaz (Univ. of California San Diego (US))
        A3D3_HEP-L1Trigger.pdf
      • 11:25
        HEP: Services for Optimized Network Inference on Coprocessors (SONIC) 15m
        Speaker: Jeffrey Krupa (Massachusetts Institute of Technology)
        a3d3_krupa.pdf
      • 11:45
        MMA: Gravitational Wave Inference as a Service 15m
        Speakers: Alec Gunny, Alec Gunny (Massachusetts Institute of Technology)
        A3D3 Kickoff Presentation - LIGO.pdf
      • 12:05
        Neuroscience: Sleep Spindles as a Driver of Low Latency, Low Power ML 15m
        Speaker: Xiaohan Liu
        Sleep Spindles as a Driver of Low Latency, Low Power ML in HLS4ML & TinyML.pdf
    • 12:40 → 13:30
      Diversity, Equity, Inclusion, & Career
      Conveners: Javier Mauricio Duarte (Univ. of California San Diego (US)), Miaoyuan Liu (Purdue University (US))
    • 13:30 → 14:20
      Education
      Conveners: Matthew Graham (California Institute of Technology), Matthew Graham
      gdoc
    • 14:20 → 15:15
      Engagement
      Conveners: Mark Neubauer (Univ. Illinois at Urbana Champaign (US)), Mark Stephen Neubauer (Univ. Illinois at Urbana-Champaign)
      • 14:25
        Engagement with other Communities/Projects and CEL Discussion 15m
        Speaker: Mark Neubauer (Univ. Illinois at Urbana Champaign (US))
        Session Notes
      • 14:40
        Resources: HAL at NCSA's Innovative Systems Laboratory 10m
        Speaker: Volodymyr Kindratenko (University of Illinois at Urbana-Champaign)
        caii_dl_tech.pdf
      • 14:50
        Resources: XACC Cluster at Illinois Coordinated Sciences Laboratory 10m
        Speaker: Deming Chen (University of Illinois at Urbana-Champaign)
        UIUC_XACC.pdf
      • 15:00
        Resources: Cloud 15m
        Speaker: Philip Coleman Harris (Massachusetts Inst. of Technology (US))
        PCH_Cloud_09_11.pdf
  • Wednesday 10 November
    • 11:00 → 13:10
      Summary
      Convener: Philip Coleman Harris (Massachusetts Inst. of Technology (US))
      • 11:00
        HAC 10m
        Speaker: Pan Li (Purdue University)
        HAC-summary.pdf
      • 11:10
        HEP 10m
        Speaker: Miaoyuan Liu (Purdue University (US))
      • 11:20
        MMA 10m
        Speaker: Michael Coughlin (University of Minnesota)
        MMA HDR Planning.pdf
      • 11:30
        Neuroscience 10m
        Speaker: Amy Orsborn
        Neuroscience in A3D3_Summary and Discussion.pdf
      • 11:40
        Targeted & Heterogeneous systems 20m
        Speakers: Eli Shlizerman, Javier Mauricio Duarte (Univ. of California San Diego (US))
        A3D3_TargetedSystems_10Nov2021.pdf
      • 12:00
        Diversity, Equality and Inclusive 10m
        Speakers: Javier Mauricio Duarte (Univ. of California San Diego (US)), Miaoyuan Liu (Purdue University (US))
      • 12:10
        Education 10m
        Speakers: Matthew Graham (California Institute of Technology), Matthew Graham
      • 12:20
        Engagement 10m
        Speakers: Mark Neubauer (Univ. Illinois at Urbana Champaign (US)), Mark Stephen Neubauer (Univ. Illinois at Urbana-Champaign)
        A3D3_Engagement_kickoff_meeting_summary.pdf
      • 12:30
        Final Remarks 10m
        Speaker: Shih-Chieh Hsu (University of Washington Seattle (US))
        gslide
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