BaM: A Case for Enabling Fine-grain High Throughput GPU-Orchestrated Access to Storage. - Zaid Qureshi; Vikram Sharma Mailthody; Isaac Gelado; Seungwon Min; Amna Masood; Jeongmin Brian Park; Jinjun Xiong; Chris J. Newburn; Dmitri Vainbrand; I-Hsin Chung; Michael Garland; William J. Dally; et al. (CoRR, 2022)

GPU-Initiated On-Demand High-Throughput Storage Access in the BaM System Architecture. - Zaid Qureshi; Vikram Sharma Mailthody; Isaac Gelago; Seungwon Min; Amna Masood; Jeongmin Brian Park; Jinjun Xiong; Chris J. Newburn; Dmitri Vainbrand; I-Hsin Chung; Michael Garland; William J. Dally; et al. (Zenodo, 2022)

GPU-Initiated On-Demand High-Throughput Storage Access in the BaM System Architecture. - Zaid Qureshi; Vikram Sharma Mailthody; Isaac Gelado; Seungwon Min; Amna Masood; Jeongmin Brian Park; Jinjun Xiong; Chris J. Newburn; Dmitri Vainbrand; I-Hsin Chung; Michael Garland; William J. Dally; et al. (ASPLOS (2), 2023)

CODAG: Characterizing and Optimizing Decompression Algorithms for GPUs. - Jeongmin Brian Park; Zaid Qureshi; Vikram S. Mailthody; Andrew Gacek; Shunfan Shao; Mohammad Almasri; Isaac Gelado; Jinjun Xiong; Chris J. Newburn; I-Hsin Chung; Michael Garland; Nikolay Sakharnykh; et al. (CoRR, 2023)

LSM-GNN: Large-scale Storage-based Multi-GPU GNN Training by Optimizing Data Transfer Scheme. - Jeongmin Brian Park; Kun Wu 002; Vikram Sharma Mailthody; Zaid Qureshi; Scott A. Mahlke; Wen-Mei W. Hwu (CoRR, 2024)

TBA: Faster Large Language Model Training Using SSD-Based Activation Offloading. - Kun Wu 002; Jeongmin Brian Park; Xiaofan Zhang 001; Mert Hidayetoglu; Vikram Sharma Mailthody; Sitao Huang; Steven S. Lumetta; Wen-Mei W. Hwu (CoRR, 2024)

Accelerating Sampling and Aggregation Operations in GNN Frameworks with GPU Initiated Direct Storage Accesses. - Jeongmin Brian Park; Vikram Sharma Mailthody; Zaid Qureshi; Wen-Mei Hwu (Proc. VLDB Endow., 2024)