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Paper Detail

Paper IDD.2.2
Paper Title Product Lagrange Coded Computing
Authors Adarsh M. Subramaniam, Anoosheh Heidarzadeh, Asit Kumar Pradhan, Krishna R. Narayanan, Texas A&M University, United States
Session D.2: Coding for Specialized Computations
Presentation Lecture
Track Coded and Distributed Computation
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Abstract This work considers the distributed multivariate polynomial evaluation (DMPE) problem using a master-worker framework, which was originally considered by Yu et al., where Lagrange Coded Computing (LCC) was proposed as a coded computation scheme to provide resilience against stragglers for the DMPE problem. In this work, we propose a variant of the LCC scheme, termed Product Lagrange Coded Computing (PLCC), by combining ideas from classical product codes and LCC. The main advantage of PLCC is that they are more numerically stable than LCC; however, their resilience to stragglers is sub-optimal.

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2021 IEEE International Symposium on Information Theory

11-16 July 2021 | Melbourne, Victoria, Australia

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