William Won

William Won

Georgia Institute of Technology

H-index: 4

North America-United States

About William Won

William Won, With an exceptional h-index of 4 and a recent h-index of 4 (since 2020), a distinguished researcher at Georgia Institute of Technology, specializes in the field of Computer Science.

His recent articles reflect a diverse array of research interests and contributions to the field:

Astra-sim2. 0: Modeling hierarchical networks and disaggregated systems for large-model training at scale

TACOS: Topology-Aware Collective Algorithm Synthesizer for Distributed Training

Themis: A network bandwidth-aware collective scheduling policy for distributed training of dl models

Exploring multi-dimensional hierarchical network topologies for efficient distributed training of trillion parameter dl models

Extending sparse tensor accelerators to support multiple compression formats

MINT: Microarchitecture for Efficient and Interchangeable CompressioN Formats on Tensor Algebra.

William Won Information

University

Position

School of Computer Science

Citations(all)

55

Citations(since 2020)

55

Cited By

3

hIndex(all)

4

hIndex(since 2020)

4

i10Index(all)

3

i10Index(since 2020)

3

Email

University Profile Page

Google Scholar

William Won Skills & Research Interests

Computer Science

Top articles of William Won

Title

Journal

Author(s)

Publication Date

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

...

2023/4/23

TACOS: Topology-Aware Collective Algorithm Synthesizer for Distributed Training

arXiv preprint arXiv:2304.05301

William Won

Midhilesh Elavazhagan

Sudarshan Srinivasan

Ajaya Durg

Swati Gupta

...

2023/4/11

Themis: A network bandwidth-aware collective scheduling policy for distributed training of dl models

Saeed Rashidi

William Won

Sudarshan Srinivasan

Srinivas Sridharan

Tushar Krishna

2022/6/18

Exploring multi-dimensional hierarchical network topologies for efficient distributed training of trillion parameter dl models

arXiv preprint arXiv:2109.11762

William Won

Saeed Rashidi

Sudarshan Srinivasan

Tushar Krishna

2021/9/24

Extending sparse tensor accelerators to support multiple compression formats

Eric Qin

Geonhwa Jeong

William Won

Sheng-Chun Kao

Hyoukjun Kwon

...

2021/5/17

MINT: Microarchitecture for Efficient and Interchangeable CompressioN Formats on Tensor Algebra.

Eric Qin

Geonhwa Jeong

William Won

Sheng-Chun Kao

Hyoukjun Kwon

...

2020/5/1

See List of Professors in William Won University(Georgia Institute of Technology)

Co-Authors

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