William Won

According to our database, William Won authored at least 9 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

FRED: Flexible REduction-Distribution Interconnect and Communication Implementation for Wafer-Scale Distributed Training of DNN Models.

Saeed Rashidi, William Won, Sudarshan Srinivasan, Puneet Gupta, Tushar Krishna

CoRR, 2024

TACOS: Topology-Aware Collective Algorithm Synthesizer for Distributed Machine Learning.

William Won, Midhilesh Elavazhagan, Sudarshan Srinivasan, Swati Gupta, Tushar Krishna

Proceedings of the 57th IEEE/ACM International Symposium on Microarchitecture, 2024

LIBRA: Enabling Workload-Aware Multi-Dimensional Network Topology Optimization for Distributed Training of Large AI Models.

William Won, Saeed Rashidi, Sudarshan Srinivasan, Tushar Krishna

Proceedings of the IEEE International Symposium on Performance Analysis of Systems and Software, 2024

Towards a Standardized Representation for Deep Learning Collective Algorithms.

Jinsun Yoo, William Won, Meghan Cowan, Nan Jiang, Benjamin Klenk, Srinivas Sridharan, Tushar Krishna

Proceedings of the IEEE Symposium on High-Performance Interconnects, 2024

2023

TACOS: Topology-Aware Collective Algorithm Synthesizer for Distributed Training.

William Won, Midhilesh Elavazhagan, Sudarshan Srinivasan, Ajaya Durg, Swati Gupta, Tushar Krishna

CoRR, 2023

ASTRA-sim2.0: Modeling Hierarchical Networks and Disaggregated Systems for Large-model Training at Scale.

William Won, Taekyung Heo, Saeed Rashidi, Srinivas Sridharan, Sudarshan Srinivasan, Tushar Krishna

Proceedings of the IEEE International Symposium on Performance Analysis of Systems and Software, 2023

2022

Themis: a network bandwidth-aware collective scheduling policy for distributed training of DL models.

Saeed Rashidi, William Won, Sudarshan Srinivasan, Srinivas Sridharan, Tushar Krishna

Proceedings of the ISCA '22: The 49th Annual International Symposium on Computer Architecture, New York, New York, USA, June 18, 2022

2021

Exploring Multi-dimensional Hierarchical Network Topologies for Efficient Distributed Training of Trillion Parameter DL Models.

William Won, Saeed Rashidi, Sudarshan Srinivasan, Tushar Krishna

CoRR, 2021

Extending Sparse Tensor Accelerators to Support Multiple Compression Formats.

Eric Qin, Geonhwa Jeong, William Won, Sheng-Chun Kao, Hyoukjun Kwon, Sudarshan Srinivasan, Dipankar Das, Gordon Euhyun Moon, Sivasankaran Rajamanickam, Tushar Krishna

Proceedings of the 35th IEEE International Parallel and Distributed Processing Symposium, 2021