22 citations · 73 across the 9 of their papers we have counts for
11 papers
Zeus: Understanding and Optimizing GPU Energy Consumption of DNN Training
Jie You, Jae-Won Chung, Mosharaf Chowdhury
Training deep neural networks (DNNs) is becoming increasingly more resource- and energy-intensive every year. Unfortunately, existing works primarily focus on optimizing DNN traini…
Elastic Model Aggregation with Parameter Service
Juncheng Gu, Mosharaf Chowdhury, Kang G. Shin +1
Model aggregation, the process that updates model parameters, is an important step for model convergence in distributed deep learning (DDL). However, the parameter server (PS), a p…
Treehouse: A Case For Carbon-Aware Datacenter Software
Thomas Anderson, Adam Belay, Mosharaf Chowdhury +2
The end of Dennard scaling and the slowing of Moore's Law has put the energy use of datacenters on an unsustainable path. Datacenters are already a significant fraction of worldwid…
Memtrade: A Disaggregated-Memory Marketplace for Public Clouds
Hasan Al Maruf, Yuhong Zhong, Hongyi Wang +3
We present Memtrade, the first memory disaggregation system for public clouds. Public clouds introduce a set of unique challenges for resource disaggregation across different tenan…
BoPF: Mitigating the Burstiness-Fairness Tradeoff in Multi-Resource Clusters
Tan N. Le, Xiao Sun, Mosharaf Chowdhury +1
Simultaneously supporting latency- and throughout-sensitive workloads in a shared environment is an increasingly more common challenge in big data clusters. Despite many advances,…
Effectively Prefetching Remote Memory with Leap
Hasan Al Maruf, Mosharaf Chowdhury
Memory disaggregation over RDMA can improve the performance of memory-constrained applications by replacing disk swapping with remote memory accesses. However, state-of-the-art mem…