123 citations · 292 across the 18 of their papers we have counts for
29 papers
TransforMAP: Transformer for Memory Access Prediction
Pengmiao Zhang, Ajitesh Srivastava, Anant V. Nori +2
Data Prefetching is a technique that can hide memory latency by fetching data before it is needed by a program. Prefetching relies on accurate memory access prediction, to which ta…
Fine-Grained Address Segmentation for Attention-Based Variable-Degree Prefetching
Pengmiao Zhang, Ajitesh Srivastava, Anant V. Nori +2
Machine learning algorithms have shown potential to improve prefetching performance by accurately predicting future memory accesses. Existing approaches are based on the modeling o…
Design and Implementation of Knowledge Base for Runtime Management of Software Defined Hardware
Hongkuan Zhou, Ajitesh Srivastava, Rajgopal Kannan +1
Runtime-reconfigurable software coupled with reconfigurable hardware is highly desirable as a means towards maximizing runtime efficiency without compromising programmability. Comp…
Model-Architecture Co-Design for High Performance Temporal GNN Inference on FPGA
Hongkuan Zhou, Bingyi Zhang, Rajgopal Kannan +2
Temporal Graph Neural Networks (TGNNs) are powerful models to capture temporal, structural, and contextual information on temporal graphs. The generated temporal node embeddings ou…
Decoupling the Depth and Scope of Graph Neural Networks
Hanqing Zeng, Muhan Zhang, Yinglong Xia +6
State-of-the-art Graph Neural Networks (GNNs) have limited scalability with respect to the graph and model sizes. On large graphs, increasing the model depth often means exponentia…
Parallel Peeling of Bipartite Networks for Hierarchical Dense Subgraph Discovery
Kartik Lakhotia, Rajgopal Kannan, Viktor Prasanna
Wing and Tip decomposition construct a hierarchy of butterfly-dense edge and vertex induced bipartite subgraphs, respectively. They have applications in several domains including e…