16 citations · 16 across the 2 of their papers we have counts for
2 papers
cs.LG2023
Surrogate-based Autotuning for Randomized Sketching Algorithms in Regression Problems
Younghyun Cho, James W. Demmel, Michał Dereziński +4
Algorithms from Randomized Numerical Linear Algebra (RandNLA) are known to be effective in handling high-dimensional computational problems, providing high-quality empirical perfor…
cs.DC2016★ 16 cited
Matrix Factorization at Scale: a Comparison of Scientific Data Analytics in Spark and C+MPI Using Three Case Studies
Alex Gittens, Aditya Devarakonda, Evan Racah +14
We explore the trade-offs of performing linear algebra using Apache Spark, compared to traditional C and MPI implementations on HPC platforms. Spark is designed for data analytics…