Workshop
Benchmarking Machine Learning Workloads on Emerging Hardware
Tom St John · Murali Emani
Mission Ballroom B4
With evolving system architectures, hardware and software stack, diverse machine learning workloads, and data, it is important to understand how these components interact with each other. Well-defined benchmarking procedures help evaluate and reason the performance gains with ML workload to system mapping.
Key problems that we seek to address are: (i) which representative ML benchmarks cater to workloads seen in industry, national labs, and interdisciplinary sciences; (ii) how to characterize the ML workloads based on their interaction with hardware; (iii) what novel aspects of hardware, such as heterogeneity in compute, memory, and bandwidth, will drive their adoption; (iv) performance modeling and projections to next-generation hardware.
The workshop will invite experts in these research areas to present recent work and potential directions to pursue. Accepted papers from a rigorous evaluation process will present state-of-the-art research efforts. We have also secured funding from MLCommonsTM to provide a best paper award for an outstanding submission. A panel discussion will foster an interactive platform for discussion between speakers and the audience.
Schedule
Thu 8:00 a.m. - 8:10 a.m.
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Opening Remarks
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Opening Remarks
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Thu 8:10 a.m. - 9:00 a.m.
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Keynote Talk - Sophia Shao
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Invited Talk
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Sophia Shao 🔗 |
Thu 9:00 a.m. - 9:30 a.m.
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FastML Science Benchmarks: Accelerating Real-Time Scientific Edge Computing
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Talk
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Thu 9:30 a.m. - 10:00 a.m.
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MetaBench: Real-Time Multi-Modal Benchmark for Metaverse
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Talk
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Hyoukjun Kwon 🔗 |
Thu 10:00 a.m. - 10:30 a.m.
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Break
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Break
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Thu 10:30 a.m. - 11:10 a.m.
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Invited Talk - John Owens
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Invited Talk
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John Owens 🔗 |
Thu 11:10 a.m. - 11:30 a.m.
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Benchmarking and Accelerating Session-Based Recommendation Model on Heterogeneous Accelerators
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Talk
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Mayank Mishra 🔗 |
Thu 11:30 a.m. - 11:50 a.m.
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Optimizing Data Collection in Deep Reinforcement Learning
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Talk
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James Gleeson 🔗 |
Thu 11:50 a.m. - 1:30 p.m.
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Lunch
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Break
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Thu 1:30 p.m. - 2:20 p.m.
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Invited Talk - Venkatram Vishwanath
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Invited Talk
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Venkatram Vishwanath 🔗 |
Thu 2:20 p.m. - 2:40 p.m.
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Open-Source FPGA-ML Co-Design for the MLPerf Tiny Benchmark
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Invited Talk
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Thu 2:40 p.m. - 3:00 p.m.
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Operation-Level Performance Benchmarking of Graph Neural Networks for Scientific Applications
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Talk
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Ryien Hosseini 🔗 |
Thu 3:00 p.m. - 3:30 p.m.
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Break
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Break
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Thu 3:30 p.m. - 4:45 p.m.
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Panel Discussion
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Panel Discussion
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Thu 4:45 p.m. - 5:00 p.m.
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Best Paper Award and Wrap-Up
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Awards
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