|Maxim Naumov, Ph.D.
Sr. Research Scientist
Maxim Naumov joined NVIDIA Research in January 2015. His interests include parallel numerical linear algebra and related topics. Previously, he has spent 5 years working on different NVIDIA libraries, such as cuBLAS, cuSPARSE, and cuSOLVER(RF), focusing on developing methods for sparse triangular solve, incomplete LU factorization, and LU re-factorization. He also co-lead the development of the AmgX library, which provides distributed Algebraic Multigrid, Krylov, and Relaxation-based schemes. In the past, Maxim held positions at the Intel Corporation Microprocessor Technology Lab and Computational Software Lab, and was awarded 2008-09 Intel Foundation Ph.D. Fellowship during his graduate studies. He received his Ph.D. in Computer Science (with specialization in Computational Science and Engineering) in 2009 and his B.Sc. in Computer Science and Mathematics in 2003, all from Purdue University - West Lafayette.
|Research Interests: |
Parallel Algorithms, Numerical Linear Algebra, Numerical Optimization, Graphs
Preconditioned Block-Iterative Methods on GPUs|
Incomplete-LU and Cholesky Factorization in the Preconditioned Iterative Methods on the GPU
Parallel Solution of Sparse Triangular Linear Systems in the Preconditioned Iterative Methods on the GPU