Triangle Counting and Truss Decomposition using FPGA. - Sitao Huang; Mohamed El-Hadedy 001; Cong Hao; Qin Li; Vikram S. Mailthody; Ketan Date; Jinjun Xiong; Deming Chen; Rakesh Nagi; Wen-Mei Hwu (HPEC, 2018)

Collaborative (CPU + GPU) Algorithms for Triangle Counting and Truss Decomposition. - Vikram S. Mailthody; Ketan Date; Zaid Qureshi; Carl Pearson; Rakesh Nagi; Jinjun Xiong; Wen-Mei Hwu (HPEC, 2018)

FlatFlash: Exploiting the Byte-Accessibility of SSDs within a Unified Memory-Storage Hierarchy. - Ahmed H. M. O. Abulila; Vikram Sharma Mailthody; Zaid Qureshi; Jian Huang 006; Nam Sung Kim; Jinjun Xiong; Wen-Mei W. Hwu (ASPLOS, 2019)

Update on k-truss Decomposition on GPU. - Mohammad Almasri; Omer Anjum; Carl Pearson; Zaid Qureshi; Vikram S. Mailthody; Rakesh Nagi; Jinjun Xiong; Wen-Mei W. Hwu (HPEC, 2019)

Update on Triangle Counting on GPU. - Carl Pearson; Mohammad Almasri; Omer Anjum; Vikram S. Mailthody; Zaid Qureshi; Rakesh Nagi; Jinjun Xiong; Wen-Mei W. Hwu (HPEC, 2019)

DeepStore: In-Storage Acceleration for Intelligent Queries. - Vikram Sharma Mailthody; Zaid Qureshi; Weixin Liang; Ziyan Feng; Simon Garcia De Gonzalo; Youjie Li; Hubertus Franke; Jinjun Xiong; Jian Huang 006; Wen-Mei Hwu (MICRO, 2019)

At-Scale Sparse Deep Neural Network Inference With Efficient GPU Implementation. - Mert Hidayetoglu; Carl Pearson; Vikram Sharma Mailthody; Eiman Ebrahimi; Jinjun Xiong; Rakesh Nagi; Wen-Mei Hwu (HPEC, 2020)

I-BERT: Inductive Generalization of Transformer to Arbitrary Context Lengths. - Hyoungwook Nam; Seung Byum Seo; Vikram Sharma Mailthody; Noor Michael; Lan Li (CoRR, 2020)

Efficient Inference on GPUs for the Sparse Deep Neural Network Graph Challenge 2020. - Mert Hidayetoglu; Carl Pearson; Vikram Sharma Mailthody; Eiman Ebrahimi; Jinjun Xiong; Rakesh Nagi; Wen-mei W. Hwu (CoRR, 2020)

Tearing Down the Memory Wall. - Zaid Qureshi; Vikram Sharma Mailthody; Seungwon Min; I-Hsin Chung; Jinjun Xiong; Wen-Mei W. Hwu (CoRR, 2020)

EMOGI: Efficient Memory-access for Out-of-memory Graph-traversal In GPUs. - Seungwon Min; Vikram Sharma Mailthody; Zaid Qureshi; Jinjun Xiong; Eiman Ebrahimi; Wen-Mei Hwu (Proc. VLDB Endow., 2020)

Towards an Accurate Latency Model for Convolutional Neural Network Layers on GPUs. - Jinyang Li 004; Runyu Ma; Vikram Sharma Mailthody; Colin Samplawski; Benjamin M. Marlin; Songqing Chen; Shuochao Yao; Tarek F. Abdelzaher (MILCOM, 2021)

Safer Illinois and RokWall: Privacy Preserving University Health Apps for COVID-19. - Vikram Sharma Mailthody; James Wei; Nicholas Chen; Mohammad Behnia; Ruihao Yao; Qihao Wang; Vedant Agrawal; Churan He; Lijian Wang; Leihao Chen; Amit Agarwal; Edward Richter; et al. (CoRR, 2021)

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)

FSSD: FPGA-Based Emulator for SSDs. - Luyang Yu; Yizhen Lu; Meghna Mandava; Edward Richter; Vikram Sharma Mailthody; Seungwon Min; Wen-Mei W. Hwu; Deming Chen (FPL, 2023)

IGB: Addressing The Gaps In Labeling, Features, Heterogeneity, and Size of Public Graph Datasets for Deep Learning Research. - Arpandeep Khatua; Vikram Sharma Mailthody; Bhagyashree Taleka; Tengfei Ma 001; Xiang Song 003; Wen-Mei Hwu (KDD, 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)

GMT: GPU Orchestrated Memory Tiering for the Big Data Era. - Chia-Hao Chang; Jihoon Han; Anand Sivasubramaniam; Vikram Sharma Mailthody; Zaid Qureshi; Wen-Mei Hwu (ASPLOS (3), 2024)

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)