Qidong Su

According to our database, Qidong Su authored at least 9 papers between 2020 and 2025.

Collaborative distances:

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

2025

Seesaw: High-throughput LLM Inference via Model Re-sharding.

Qidong Su, Wei Zhao, Xin Li, Muralidhar Andoorveedu, Chenhao Jiang, Zhanda Zhu, Kevin Song, Christina Giannoula, Gennady Pekhimenko

CoRR, March, 2025

Mist: Efficient Distributed Training of Large Language Models via Memory-Parallelism Co-Optimization.

Zhanda Zhu, Christina Giannoula, Muralidhar Andoorveedu, Qidong Su, Karttikeya Mangalam, Bojian Zheng, Gennady Pekhimenko

Proceedings of the Twentieth European Conference on Computer Systems, 2025

APPL: A Prompt Programming Language for Harmonious Integration of Programs and Large Language Model Prompts.

Honghua Dong, Qidong Su, Yubo Gao, Zhaoyu Li, Yangjun Ruan, Gennady Pekhimenko, Chris J. Maddison, Xujie Si

Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

2024

A Survey on Deep Learning for Theorem Proving.

Zhaoyu Li, Jialiang Sun, Logan Murphy, Qidong Su, Zenan Li, Xian Zhang, Kaiyu Yang, Xujie Si

CoRR, 2024

BOOM: Use your Desktop to Accurately Predict the Performance of Large Deep Neural Networks.

Qidong Su, Jiacheng Yang, Gennady Pekhimenko

Proceedings of the 2024 International Conference on Parallel Architectures and Compilation Techniques, 2024

2023

The Synergy of Speculative Decoding and Batching in Serving Large Language Models.

Qidong Su, Christina Giannoula, Gennady Pekhimenko

CoRR, 2023

TorchProbe: Fuzzing Dynamic Deep Learning Compilers.

Qidong Su, Chuqin Geng, Gennady Pekhimenko, Xujie Si

Proceedings of the Programming Languages and Systems - 21st Asian Symposium, 2023

2021

Distributed Hybrid CPU and GPU training for Graph Neural Networks on Billion-Scale Graphs.

Da Zheng, Xiang Song, Chengru Yang, Dominique LaSalle, Qidong Su, Minjie Wang, Chao Ma, George Karypis

CoRR, 2021

2020

DistDGL: Distributed Graph Neural Network Training for Billion-Scale Graphs.

Da Zheng, Chao Ma, Minjie Wang, Jinjing Zhou, Qidong Su, Xiang Song, Quan Gan, Zheng Zhang, George Karypis

Proceedings of the 10th IEEE/ACM Workshop on Irregular Applications: Architectures and Algorithms, 2020