504 citations · 2k across the 109 of their papers we have counts for
4 papers · 2 filters
knor: A NUMA-Optimized In-Memory, Distributed and Semi-External-Memory k-means Library
Disa Mhembere, Da Zheng, Carey E. Priebe +2
k-means is one of the most influential and utilized machine learning algorithms. Its computation limits the performance and scalability of many statistical analysis and machine lea…
FlashR: R-Programmed Parallel and Scalable Machine Learning using SSDs
Da Zheng, Disa Mhembere, Joshua T. Vogelstein +2
R is one of the most popular programming languages for statistics and machine learning, but the R framework is relatively slow and unable to scale to large datasets. The general ap…
An SSD-based eigensolver for spectral analysis on billion-node graphs
Da Zheng, Randal Burns, Joshua Vogelstein +2
Many eigensolvers such as ARPACK and Anasazi have been developed to compute eigenvalues of a large sparse matrix. These eigensolvers are limited by the capacity of RAM. They run in…
Semi-External Memory Sparse Matrix Multiplication for Billion-Node Graphs
Da Zheng, Disa Mhembere, Vince Lyzinski +3
Sparse matrix multiplication is traditionally performed in memory and scales to large matrices using the distributed memory of multiple nodes. In contrast, we scale sparse matrix m…