14 citations · 23 across the 6 of their papers we have counts for
6 papers
TrustRate: A Decentralized Platform for Hijack-Resistant Anonymous Reviews
Rohit Dwivedula, Sriram Sridhar, Sambhav Satija +4
Reviews and ratings by users form a central component in several widely used products today (e.g., product reviews, ratings of online content, etc.), but today's platforms for mana…
Singularity: Planet-Scale, Preemptive and Elastic Scheduling of AI Workloads
Dharma Shukla, Muthian Sivathanu, Srinidhi Viswanatha +23
Lowering costs by driving high utilization across deep learning workloads is a crucial lever for cloud providers. We present Singularity, Microsoft's globally distributed schedulin…
Varuna: Scalable, Low-cost Training of Massive Deep Learning Models
Sanjith Athlur, Nitika Saran, Muthian Sivathanu +2
Systems for training massive deep learning models (billions of parameters) today assume and require specialized "hyper-clusters": hundreds or thousands of GPUs wired with specializ…
LRTuner: A Learning Rate Tuner for Deep Neural Networks
Nikhil Iyer, V Thejas, Nipun Kwatra +2
One very important hyperparameter for training deep neural networks is the learning rate schedule of the optimizer. The choice of learning rate schedule determines the computationa…
Blockene: A High-throughput Blockchain Over Mobile Devices
Sambhav Satija, Apurv Mehra, Sudheesh Singanamalla +5
We introduce Blockene, a blockchain that reduces resource usage at member nodes by orders of magnitude, requiring only a smartphone to participate in block validation and consensus…
Wide-minima Density Hypothesis and the Explore-Exploit Learning Rate Schedule
Nikhil Iyer, V Thejas, Nipun Kwatra +2
Several papers argue that wide minima generalize better than narrow minima. In this paper, through detailed experiments that not only corroborate the generalization properties of w…