3 citations · 7 across the 3 of their papers we have counts for
4 papers
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…
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…
NeuMMU: Architectural Support for Efficient Address Translations in Neural Processing Units
Bongjoon Hyun, Youngeun Kwon, Yujeong Choi +2
To satisfy the compute and memory demands of deep neural networks, neural processing units (NPUs) are widely being utilized for accelerating deep learning algorithms. Similar to ho…
MGSim + MGMark: A Framework for Multi-GPU System Research
Yifan Sun, Trinayan Baruah, Saiful A. Mojumder +10
The rapidly growing popularity and scale of data-parallel workloads demand a corresponding increase in raw computational power of GPUs (Graphics Processing Units). As single-GPU sy…