no code implementations • 25 Oct 2023 • Lingda Li, Thomas Flynn, Adolfy Hoisie
This paper proposes PerfVec, a novel deep learning-based performance modeling framework that learns high-dimensional, independent/orthogonal program and microarchitecture representations.
1 code implementation • 16 Sep 2021 • Anil Gaihre, Da Zheng, Scott Weitze, Lingda Li, Shuaiwen Leon Song, Caiwen Ding, Xiaoye S Li, Hang Liu
Recent top-$k$ computation efforts explore the possibility of revising various sorting algorithms to answer top-$k$ queries on GPUs.
1 code implementation • 12 May 2021 • Lingda Li, Santosh Pandey, Thomas Flynn, Hang Liu, Noel Wheeler, Adolfy Hoisie
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 realistic applications under investigation.
BIG-bench Machine Learning Vocal Bursts Intensity Prediction
1 code implementation • 18 Sep 2020 • Santosh Pandey, Lingda Li, Adolfy Hoisie, Xiaoye S. Li, Hang Liu
In this paper, we propose, to the best of our knowledge, the first GPU-based framework for graph sampling/random walk.
Graph Sampling Distributed, Parallel, and Cluster Computing