33 citations · 139 across the 42 of their papers we have counts for
7 papers · 1 filter
Numerically stable coded matrix computations via circulant and rotation matrix embeddings
Aditya Ramamoorthy, Li Tang
Polynomial based methods have recently been used in several works for mitigating the effect of stragglers (slow or failed nodes) in distributed matrix computations. For a system wi…
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…
Efficient and Robust Distributed Matrix Computations via Convolutional Coding
Anindya B. Das, Aditya Ramamoorthy, Namrata Vaswani
Distributed matrix computations -- matrix-matrix or matrix-vector multiplications -- are well-recognized to suffer from the problem of stragglers (slow or failed worker nodes). Muc…
Asynchronous Coded Caching with Uncoded Prefetching
Hooshang Ghasemi, Aditya Ramamoorthy
Coded caching is a technique that promises huge reductions in network traffic in content-delivery networks. However, the original formulation and several subsequent contributions i…
Universally Decodable Matrices for Distributed Matrix-Vector Multiplication
Aditya Ramamoorthy, Li Tang, Pascal O. Vontobel
Coded computation is an emerging research area that leverages concepts from erasure coding to mitigate the effect of stragglers (slow nodes) in distributed computation clusters, es…
Distributed Matrix-Vector Multiplication: A Convolutional Coding Approach
Anindya Bijoy Das, Aditya Ramamoorthy
Distributed computing systems are well-known to suffer from the problem of slow or failed nodes; these are referred to as stragglers. Straggler mitigation (for distributed matrix c…