Program
Slides and camera-ready papers will be posted by the workshop. The conference will take place in the Sculptor Room at the Hyatt Regency San Francisco Downtown SOMA.
Remote participation is available at: Zoom connection
| Time (PDT) | Duration | Presentations | ||
|---|---|---|---|---|
| 8:15 | 15' | Welcome and introduction Javier Duarte, UCSD |
[Slides] | |
| 8:30 | 30' | Community Vision, Needs, and Progress Vladimir Loncar, MIT |
[Slides] | |
| 9:00 | 30' | Design Tools Perspective: Catapult + hls4ml for Inference at the Edge David Burnette, Siemens |
[Slides] | |
| 9:30 | 30' | Designing Hardware for Machine Learning John Wawrzynek, UC Berkeley |
[Slides] | |
| 10:00 | 30' | Coffee |
||
| 10:30 | 30' | Design Tools Perspective: Mapping ML to the AMD RyzenAI Architecture Elliott Delaye, AMD |
[Slides] | |
| 11:00 | 30' | Fast ML in the NSF HDR Institute: A3D3 Shih-Chieh Hsu, UW |
[Slides] | |
| 11:30 | 30' | Real-time ML at the Linac Coherent Light Source Jana Thayer, SLAC |
[Slides] | |
| 12:00 | 60' | Lunch |
||
| 1:20 | 30' | Robust and Efficient Machine Learning for Mission-Critical Applications Bhavya Kailkhura, LLNL |
[Slides] | |
| 1:50 | 20' | Quantifying the Efficiency of High-Level Synthesis for Machine Learning Inference Caroline Johnson (UW), Scott Hauck, Shih-Chieh Hsu, Waiz Khan, Stephany Ayala-Cerna, Geoff Jones, Anatoliy Martynyuk, Matthew Bavier, Oleh Kondratyuk, Trinh Nguyen, Jan Silva, Aidan Short (UW) |
[Paper] | [Slides] |
| 2:10 | 20' | TT-QEC: Transferable Transformer for Quantum Error Correction Code Decoding Hanrui Wang (MIT), Kevin Shao (MIT), Dantong Li (Yale University), Jiaqi Gu (ASU), David Pan (University of Texas), Yongshan Ding (Yale University), Song Han (MIT) |
[Paper] | [Slides] |
| 2:30 | 20' | Benchmarking the Robustness of Neural Network-based Partial Differential Equation
Solver Jiaqi Gu (ASU), Mohit Dighamber, Zhengqi Gao, Duane S. Boning (MIT) |
[Paper] | [Slides] |
| 2:50 | 20' | Smart pixel sensors: towards on-sensor filtering of pixel clusters with deep learning Giuseppe Di Guglielmo (FNAL), Jieun Yoo (UIC), Jennet Dickinson (FNAL), Morris Swartz (JHU), Alice Bean (KU), Doug Berry (FNAL), Manuel Blanco Valentin (NU), Karri DiPetrillo (UChicago), Farah Fahim, Lindsey Gray, James Hirschauer (FNAL), Shruti Kulkarni (ORNL), Ron Lipton (FNAL), Petar Maksimovic (JHU), Corinne Mills (UIC), Mark Neubauer (UIUC), Benjamin Parpillon, Gauri Pradhan, Chinar Syal, Nhan Tran (FNAL), Dahai Wen (JHU), Aaron Young (ORNL) |
[Paper] | [Slides] |
| 3:10 | 30' | Coffee |
||
| 3:40 | 20' | FKeras: A Sensitivity Analysis Tool for Edge Neural Networks Andres Meza (UCSD), Olivia Weng (UCSD), Quinlan Bock (FNAL), Benjamin Hawks (FNAL), Javier Campos (FNAL), Nhan Tran (FNAL), Javier Mauricio Duarte (UCSD), Ryan Kastner (UCSD) |
[Paper] | [Slides] |
| 4:00 | 20' | FPGA Deployment of LFADS for Real-time Neuroscience Experiments Elham E Khoda (UW), Xiaohan Liu (UW), ChiJui Chen, YanLun Huang, LingChi Yang (National Yang Ming Chiao Tung University), Scott Hauck, Shih-Chieh Hsu (UW), Bo-Cheng Lai (National Yang Ming Chiao Tung University) | [Paper] | [Slides] |
| 4:20 | 20' | Toward Reinforcement Learning-based Rectilinear Macro Placement Under Human
Constraints Jungwoo Lee (AgileSoDA Company), Tuyen P. Le, Hieu T. Nguyen, Seungyeol Baek, Taeyoun Kim (AgileSoDA Company), Seongjung Kim, Hyunjin Kim, Misu Jung, Daehoon Kim, Seokyong Lee (Asicland Company), Daewoo Choi (Hankuk University of Foreign Studies) | [Paper] | [Slides] |
| 4:40 | 20' | ResilienQ: Boosting Fidelity of Quantum State Preparation via Noise-Aware Variational
Training Hanrui Wang (MIT), Yilian Liu (Cornell University), Pengyu Liu (CMU), Song Han (MIT) | [Paper] | [Slides] |
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