51 citations · 99 across the 4 of their papers we have counts for
5 papers
Dr. Top-k: Delegate-Centric Top-k on GPUs
Anil Gaihre, Da Zheng, Scott Weitze +5
Recent top- computation efforts explore the possibility of revising various sorting algorithms to answer top- queries on GPUs. These endeavors, unfortunately, perform signifi…
SimNet: Accurate and High-Performance Computer Architecture Simulation using Deep Learning
Lingda Li, Santosh Pandey, Thomas Flynn +3
While discrete-event simulators are essential tools for architecture research, design, and development, their practicality is limited by an extremely long time-to-solution for real…
TRUST: Triangle Counting Reloaded on GPUs
Santosh Pandey, Zhibin Wang, Sheng Zhong +8
Triangle counting is a building block for a wide range of graph applications. Traditional wisdom suggests that i) hashing is not suitable for triangle counting, ii) edge-centric tr…
C-SAW: A Framework for Graph Sampling and Random Walk on GPUs
Santosh Pandey, Lingda Li, Adolfy Hoisie +2
Many applications require to learn, mine, analyze and visualize large-scale graphs. These graphs are often too large to be addressed efficiently using conventional graph processing…
A Graph-based Model for GPU Caching Problems
Lingda Li, Ari B. Hayes, Stephen A. Hackler +3
Modeling data sharing in GPU programs is a challenging task because of the massive parallelism and complex data sharing patterns provided by GPU architectures. Better GPU caching e…