3 papers
cs.NI2020
Caramel: Accelerating Decentralized Distributed Deep Learning with Computation Scheduling
Sayed Hadi Hashemi, Sangeetha Abdu Jyothi, Brighten Godfrey +1
The method of choice for parameter aggregation in Deep Neural Network (DNN) training, a network-intensive task, is shifting from the Parameter Server model to decentralized aggrega…
cs.NI2018
cISP: A Speed-of-Light Internet Service Provider
Debopam Bhattacherjee, Sangeetha Abdu Jyothi, Ilker Nadi Bozkurt +8
Low latency is a requirement for a variety of interactive network applications. The Internet, however, is not optimized for latency. We thus explore the design of cost-effective wi…
cs.DC2018
TicTac: Accelerating Distributed Deep Learning with Communication Scheduling
Sayed Hadi Hashemi, Sangeetha Abdu Jyothi, Roy H. Campbell
State-of-the-art deep learning systems rely on iterative distributed training to tackle the increasing complexity of models and input data. The iteration time in these communicatio…