Skip to main navigation
Skip to search
Skip to main content
Princeton University Home
Help & FAQ
Link opens in a new tab
Search content at Princeton University
Home
Profiles
Research units
Facilities
Projects
Research output
Press/Media
Distributed Matrix Computations With Low-Weight Encodings
Anindya Bijoy Das
, Aditya Ramamoorthy
, David J. Love
,
Christopher G. Brinton
Research output
:
Contribution to journal
›
Article
›
peer-review
8
Link opens in a new tab
Scopus citations
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'Distributed Matrix Computations With Low-Weight Encodings'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Keyphrases
Amazon Web Services
25%
Common Strategies
25%
Communication Speed
25%
Computation Time
50%
Computational Approach
50%
Computational Efficiency
25%
Computational Speed
25%
Fast Encoding
25%
Heterogeneous Systems
25%
Input Matrix
50%
Linear Combination
25%
Low Weight
100%
Matrix Computation
100%
Maximum Distance Separable (MDS) Codes
25%
Numerical Experiments
25%
Numerical Stability
25%
Optimal number
25%
Partial Computations
25%
Random Coefficients
25%
Random Linear Combination
25%
Reed-Solomon
25%
Resilience
50%
Sparse Input
25%
Sparse Matrix Computation
25%
Stragglers
100%
Submatrices
75%
Worker Node
75%
Mathematics
Linear Combination
50%
Matrix (Mathematics)
75%
Matrix Computation
100%
Maximum Distance Separable Code
25%
Nonzero Entry
25%
Numerical Experiment
25%
Numerical Stability
25%
Optimal Number
25%
Random Coefficient
25%
Sparse Matrix
25%
Submatrix
75%
Computer Science
Amazon Web Services
33%
Computation Matrix
100%
Computation Time
66%
Heterogeneous System
33%
Input Sparse Matrix
33%
Linear Combination
33%
Partial Computation
33%
Random Linear Combination
33%
Sparse Matrix Computation
33%