We propose a coded distributed computing scheme based on Raptor codes to address the straggler problem. In particular, we consider a scheme where each server computes intermediate values, referred to as droplets, that are either stored locally or sent over the network. Once enough droplets are collected, the computation can be completed. Compared to previous schemes in the literature, our proposed scheme achieves lower computational delay when the decoding time is taken into account
The overall execution time of distributed matrix computations is often dominated by slow worker node...
Distributed computing systems are well-known to suffer from the problem of slow or failed nodes; the...
Abstract—In this paper, we propose a distributed network cod-ing (DNC) scheme based on the Raptor co...
We propose two coded schemes for the distributed computing problem of multiplying a matrix by a set ...
Coded computation techniques provide robustness against straggling workers in distributed computing....
Coded computation techniques provide robustness against straggling workers in distributed computing....
In this paper, we address the problem of distributed Raptor code design over information packets loc...
In this project, we investigate the performance of Raptor codes as candidatesfor channel coding for ...
International audiencePlacement delivery arrays for distributed computing (Comp-PDAs) have recently ...
Data and analytics capabilities have made a leap forward in recent years. The volume of available da...
When gradient descent (GD) is scaled to many parallel workers for large-scale machine learning appli...
We consider the distributed computing problem of multiplying a set of vectors with a matrix. For thi...
In distributed computing systems, it is well recognized that worker nodes that are slow (called stra...
Large matrix multiplications commonly take place in large-scale machine-learning applications. Often...
Abstract—LT-codes are a new class of codes introduced by Luby for the purpose of scalable and fault-...
The overall execution time of distributed matrix computations is often dominated by slow worker node...
Distributed computing systems are well-known to suffer from the problem of slow or failed nodes; the...
Abstract—In this paper, we propose a distributed network cod-ing (DNC) scheme based on the Raptor co...
We propose two coded schemes for the distributed computing problem of multiplying a matrix by a set ...
Coded computation techniques provide robustness against straggling workers in distributed computing....
Coded computation techniques provide robustness against straggling workers in distributed computing....
In this paper, we address the problem of distributed Raptor code design over information packets loc...
In this project, we investigate the performance of Raptor codes as candidatesfor channel coding for ...
International audiencePlacement delivery arrays for distributed computing (Comp-PDAs) have recently ...
Data and analytics capabilities have made a leap forward in recent years. The volume of available da...
When gradient descent (GD) is scaled to many parallel workers for large-scale machine learning appli...
We consider the distributed computing problem of multiplying a set of vectors with a matrix. For thi...
In distributed computing systems, it is well recognized that worker nodes that are slow (called stra...
Large matrix multiplications commonly take place in large-scale machine-learning applications. Often...
Abstract—LT-codes are a new class of codes introduced by Luby for the purpose of scalable and fault-...
The overall execution time of distributed matrix computations is often dominated by slow worker node...
Distributed computing systems are well-known to suffer from the problem of slow or failed nodes; the...
Abstract—In this paper, we propose a distributed network cod-ing (DNC) scheme based on the Raptor co...