87 citations · 93 across the 4 of their papers we have counts for
5 papers
-Approximate Coded Matrix Multiplication is Nearly Twice as Efficient as Exact Multiplication
Haewon Jeong, Ateet Devulapalli, Viveck R. Cadambe +1
We study coded distributed matrix multiplication from an approximate recovery viewpoint. We consider a system of computation nodes where each node stores of each multipli…
An Application of Storage-Optimal MatDot Codes for Coded Matrix Multiplication: Fast k-Nearest Neighbors Estimation
Utsav Sheth, Sanghamitra Dutta, Malhar Chaudhari +5
We propose a novel application of coded computing to the problem of the nearest neighbor estimation using MatDot Codes [Fahim. et.al. 2017], that are known to be optimal for matrix…
A Unified Coded Deep Neural Network Training Strategy Based on Generalized PolyDot Codes for Matrix Multiplication
Sanghamitra Dutta, Ziqian Bai, Haewon Jeong +2
This paper has two contributions. First, we propose a novel coded matrix multiplication technique called Generalized PolyDot codes that advances on existing methods for coded matri…
Coded FFT and Its Communication Overhead
Haewon Jeong, Tze Meng Low, Pulkit Grover
We propose a coded computing strategy and examine communication costs of coded computing algorithms to make distributed Fast Fourier Transform (FFT) resilient to errors during the…
On the Optimal Recovery Threshold of Coded Matrix Multiplication
Sanghamitra Dutta, Mohammad Fahim, Farzin Haddadpour +3
We provide novel coded computation strategies for distributed matrix-matrix products that outperform the recent "Polynomial code" constructions in recovery threshold, i.e., the req…