Unsupervised Projection Networks for Generative Adversarial Networks. - Daiyaan Arfeen; Jesse Zhang (CoRR, 2019)

HAWQ-V2: Hessian Aware trace-Weighted Quantization of Neural Networks. - Zhen Dong 003; Zhewei Yao; Yaohui Cai; Daiyaan Arfeen; Amir Gholami; Michael W. Mahoney; Kurt Keutzer (CoRR, 2019)

HAWQ-V2: Hessian Aware trace-Weighted Quantization of Neural Networks. - Zhen Dong 003; Zhewei Yao; Daiyaan Arfeen; Amir Gholami; Michael W. Mahoney; Kurt Keutzer (NeurIPS, 2020)

Sia: Heterogeneity-aware, goodput-optimized ML-cluster scheduling. - Suhas Jayaram Subramanya; Daiyaan Arfeen; Shouxu Lin; Aurick Qiao; Zhihao Jia; Gregory R. Ganger (SOSP, 2023)

SpecInfer: Accelerating Generative LLM Serving with Speculative Inference and Token Tree Verification. - Xupeng Miao; Gabriele Oliaro; Zhihao Zhang 001; Xinhao Cheng; Zeyu Wang; Rae Ying Yee Wong; Zhuoming Chen; Daiyaan Arfeen; Reyna Abhyankar; Zhihao Jia (CoRR, 2023)

SpecInfer: Accelerating Large Language Model Serving with Tree-based Speculative Inference and Verification. - Xupeng Miao; Gabriele Oliaro; Zhihao Zhang 001; Xinhao Cheng; Zeyu Wang; Zhengxin Zhang; Rae Ying Yee Wong; Alan Zhu 001; Lijie Yang 003; Xiaoxiang Shi; Chunan Shi; Zhuoming Chen; et al. (ASPLOS (3), 2024)

PipeFill: Using GPUs During Bubbles in Pipeline-parallel LLM Training. - Daiyaan Arfeen; Zhen Zhang; Xinwei Fu; Gregory R. Ganger; Yida Wang (CoRR, 2024)

GraphPipe: Improving Performance and Scalability of DNN Training with Graph Pipeline Parallelism. - Byungsoo Jeon; Mengdi Wu; Shiyi Cao; Sunghyun Kim; Sunghyun Park 004; Neeraj Aggarwal; Colin Unger; Daiyaan Arfeen; Peiyuan Liao; Xupeng Miao; Mohammad Alizadeh; Gregory R. Ganger; et al. (ASPLOS (1), 2025)

Nonuniform-Tensor-Parallelism: Mitigating GPU failure impact for Scaled-up LLM Training. - Daiyaan Arfeen; Dheevatsa Mudigere; Ankit More; Bhargava Gopireddy; Ahmet Inci; Gregory R. Ganger (CoRR, 2025)