RAOP: Recurrent Neural Network Augmented Offset Prefetcher. - Pengmiao Zhang; Ajitesh Srivastava; Benjamin Brooks; Rajgopal Kannan; Viktor K. Prasanna (MEMSYS, 2020)

MemMAP: Compact and Generalizable Meta-LSTM Models for Memory Access Prediction. - Ajitesh Srivastava; Ta-Yang Wang; Pengmiao Zhang; César Augusto Fonticielha De Rose; Rajgopal Kannan; Viktor K. Prasanna (PAKDD (2), 2020)

Fine-grained address segmentation for attention-based variable-degree prefetching. - Pengmiao Zhang; Ajitesh Srivastava; Anant V. Nori; Rajgopal Kannan; Viktor K. Prasanna (CF, 2022)

A2P: Attention-based Memory Access Prediction for Graph Analytics. - Pengmiao Zhang; Rajgopal Kannan; Anant V. Nori; Viktor K. Prasanna (DATA, 2022)

SHARP: Software Hint-Assisted Memory Access Prediction for Graph Analytics. - Pengmiao Zhang; Rajgopal Kannan; Xiangzhi Tong; Anant V. Nori; Viktor K. Prasanna (HPEC, 2022)

ReSemble: Reinforced Ensemble Framework for Data Prefetching. - Pengmiao Zhang; Rajgopal Kannan; Ajitesh Srivastava; Anant V. Nori; Viktor K. Prasanna (SC, 2022)

TransforMAP: Transformer for Memory Access Prediction. - Pengmiao Zhang; Ajitesh Srivastava; Anant V. Nori; Rajgopal Kannan; Viktor K. Prasanna (CoRR, 2022)

Phases, Modalities, Temporal and Spatial Locality: Domain Specific ML Prefetcher for Accelerating Graph Analytics. - Pengmiao Zhang; Rajgopal Kannan; Viktor K. Prasanna (CoRR, 2022)

C-MemMAP: clustering-driven compact, adaptable, and generalizable meta-LSTM models for memory access prediction. - Pengmiao Zhang; Ajitesh Srivastava; Ta-Yang Wang; César A. F. De Rose; Rajgopal Kannan; Viktor K. Prasanna (Int. J. Data Sci. Anal., 2022)

ME- ViT: A Single-Load Memory-Efficient FPGA Accelerator for Vision Transformers. - Kyle Marino; Pengmiao Zhang; Viktor K. Prasanna (HiPC, 2023)

G-MAP: A Graph Neural Network-Based Framework for Memory Access Prediction. - Abhiram Rao Gorle; Pengmiao Zhang; Rajgopal Kannan; Viktor K. Prasanna (HPEC, 2023)

PaCKD: Pattern-Clustered Knowledge Distillation for Compressing Memory Access Prediction Models. - Neelesh Gupta; Pengmiao Zhang; Rajgopal Kannan; Viktor K. Prasanna (HPEC, 2023)

Phases, Modalities, Spatial and Temporal Locality: Domain Specific ML Prefetcher for Accelerating Graph Analytics. - Pengmiao Zhang; Rajgopal Kannan; Viktor K. Prasanna (SC, 2023)

TabConv: Low-Computation CNN Inference via Table Lookups. - Neelesh Gupta; Narayanan Kannan; Pengmiao Zhang; Viktor K. Prasanna (CF, 2024)

Attention, Distillation, and Tabularization: Towards Practical Neural Network-Based Prefetching. - Pengmiao Zhang; Neelesh Gupta; Rajgopal Kannan; Viktor K. Prasanna (IPDPS, 2024)

Accelerating Graph Analytics Using Attention-Based Data Prefetcher. - Pengmiao Zhang; Rajgopal Kannan; Anant V. Nori; Viktor K. Prasanna (SN Comput. Sci., 2024)

GraFetch: Accelerating Graph Applications Through Domain Specific Hierarchical Hybrid Prefetching. - Pengmiao Zhang; Rajgopal Kannan; Viktor K. Prasanna (IEEE Trans. Parallel Distributed Syst., 2025)