Entangled polynomial codes for secure, private, and batch distributed matrix multiplication: Breaking the" cubic" barrier
In distributed matrix multiplication, a common scenario is to assign each worker a fraction of
the multiplication task, by partitioning the input matrices into smaller submatrices. In …
the multiplication task, by partitioning the input matrices into smaller submatrices. In …
Coded computing for resilient, secure, and privacy-preserving distributed matrix multiplication
Coded computing is a new framework to address fundamental issues in large scale
distributed computing, by injecting structured randomness and redundancy. We first provide …
distributed computing, by injecting structured randomness and redundancy. We first provide …
Communication-efficient gradient coding for straggler mitigation in distributed learning
Distributed implementations of gradient-based methods, wherein a server distributes
gradient computations across worker machines, need to overcome two limitations: delays …
gradient computations across worker machines, need to overcome two limitations: delays …
Efficient Node Selection for Coding-based Timely Computation over Heterogeneous Systems
In large-scale distributed systems, computational nodes often experience random slowdown
which can degrade the performance of timely computation tasks significantly. Recently …
which can degrade the performance of timely computation tasks significantly. Recently …