4 papers
ByzShield: An Efficient and Robust System for Distributed Training
Konstantinos Konstantinidis, Aditya Ramamoorthy
Training of large scale models on distributed clusters is a critical component of the machine learning pipeline. However, this training can easily be made to fail if some workers b…
Resolvable Designs for Speeding up Distributed Computing
Konstantinos Konstantinidis, Aditya Ramamoorthy
Distributed computing frameworks such as MapReduce are often used to process large computational jobs. They operate by partitioning each job into smaller tasks executed on differen…
Erasure coding for distributed matrix multiplication for matrices with bounded entries
Li Tang, Konstantinos Konstantinidis, Aditya Ramamoorthy
Distributed matrix multiplication is widely used in several scientific domains. It is well recognized that computation times on distributed clusters are often dominated by the slow…
Leveraging Coding Techniques for Speeding up Distributed Computing
Konstantinos Konstantinidis, Aditya Ramamoorthy
Large scale clusters leveraging distributed computing frameworks such as MapReduce routinely process data that are on the orders of petabytes or more. The sheer size of the data pr…