Search Results for author: Nikhil Devanur

Found 4 papers, 1 papers with code

Blink: Fast and Generic Collectives for Distributed ML

no code implementations11 Oct 2019 Guanhua Wang, Shivaram Venkataraman, Amar Phanishayee, Jorgen Thelin, Nikhil Devanur, Ion Stoica

Model parameter synchronization across GPUs introduces high overheads for data-parallel training at scale.

Image Classification

PipeDream: Fast and Efficient Pipeline Parallel DNN Training

1 code implementation8 Jun 2018 Aaron Harlap, Deepak Narayanan, Amar Phanishayee, Vivek Seshadri, Nikhil Devanur, Greg Ganger, Phil Gibbons

PipeDream is a Deep Neural Network(DNN) training system for GPUs that parallelizes computation by pipelining execution across multiple machines.

Distributed, Parallel, and Cluster Computing

Truth and Regret in Online Scheduling

no code implementations1 Mar 2017 Shuchi Chawla, Nikhil Devanur, Janardhan Kulkarni, Rad Niazadeh

The service provider's goal is to implement a truthful online mechanism for scheduling jobs so as to maximize the social welfare of the schedule.


Budget Constraints in Prediction Markets

no code implementations7 Oct 2015 Nikhil Devanur, Miroslav Dudík, Zhiyi Huang, David M. Pennock

We give a detailed characterization of optimal trades under budget constraints in a prediction market with a cost-function-based automated market maker.

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