activity
20182021
most citedMGPU-TSM: A Multi-GPU System with Truly Shared Memory

3 citations · 7 across the 5 of their papers we have counts for

collaborators

10 papers

cs.DC20211 cited

Daisen: A Framework for Visualizing Detailed GPU Execution

Yifan Sun, Yixuan Zhang, Ali Mosallaei +3

Graphics Processing Units (GPUs) have been widely used to accelerate artificial intelligence, physics simulation, medical imaging, and information visualization applications. To im…

stat.AP2020

Using Undersampling with Ensemble Learning to Identify Factors Contributing to Preterm Birth

Shi Dong, Zlatan Feric, Guangyu Li +10

In this paper, we propose Ensemble Learning models to identify factors contributing to preterm birth. Our work leverages a rich dataset collected by a NIEHS P42 Center that is tryi…

cs.AR20203 cited

MGPU-TSM: A Multi-GPU System with Truly Shared Memory

Saiful A. Mojumder, Yifan Sun, Leila Delshadtehrani +6

The sizes of GPU applications are rapidly growing. They are exhausting the compute and memory resources of a single GPU, and are demanding the move to multiple GPUs. However, the p…

cs.CR2020

Hardware/Software Obfuscation against Timing Side-channel Attack on a GPU

Elmira Karimi, Yunsi Fei, David Kaeli

GPUs are increasingly being used in security applications, especially for accelerating encryption/decryption. While GPUs are an attractive platform in terms of performance, the sec…

cs.AR20203 cited

HALCONE : A Hardware-Level Timestamp-based Cache Coherence Scheme for Multi-GPU systems

Saiful A. Mojumder, Yifan Sun, Leila Delshadtehrani +6

While multi-GPU (MGPU) systems are extremely popular for compute-intensive workloads, several inefficiencies in the memory hierarchy and data movement result in a waste of GPU reso…

cs.DC2020

A Smart Background Scheduler for Storage Systems

Maher Kachmar, David Kaeli

In today's enterprise storage systems, supported data services such as snapshot delete or drive rebuild can cause tremendous performance interference if executed inline along with…