Technical Program

Paper Detail

Paper Title Coded elastic computing
Paper IdentifierFR2.R2.4
Authors Yaoqing Yang, Carnegie Mellon University, United States; Matteo Interlandi, Microsoft, United States; Pulkit Grover, Soummya Kar, Carnegie Mellon University, United States; Saeed Amizadeh, Markus Weimer, Microsoft, United States
Session Coded Computation and Networks
Location Saint Germain, Level 3
Session Time Friday, 12 July, 11:40 - 13:00
Presentation Time Friday, 12 July, 12:40 - 13:00
Manuscript  Click here to download the manuscript
Abstract Cloud providers have recently introduced new offerings whereby spare computing resources are accessible at discounts compared to on-demand computing. Exploiting such opportunity is challenging inasmuch as such resources are accessed with low-priority and therefore can elastically leave (through preemption) and join the computation at any time. In this paper, we design a new technique called coded elastic computing enabling distributed computations over elastic resources. The proposed technique allows machines to leave the computation without sacrificing the algorithm-level performance, and, at the same time, flexibly reduce the workload at existing machines when new ones join the computation. Leveraging coded redundancy, our approach is able to achieve similar computational cost as the original (uncoded) method when all machines are present; the cost gracefully increases when machines are preempted and reduces when machines join. The performance of the proposed technique is evaluated on matrix-vector multiplication and linear regression tasks and shows improvements over existing techniques.