Maxim Naumov

Maxim Naumov is a Senior Research Scientist at NVIDIA. His interests include parallel algorithms, numerical linear algebra, optimization and graphs. He contributes to the nvGRAPH Data Analytics library, and he previously led the development of the AmgX library, which provides distributed Algebraic Multigrid, Krylov and Relaxation-based solvers. He has also worked on the cuBLAS, cuSPARSE and cuSOLVER(RF) libraries that are part of the CUDA Toolkit. In the past, Maxim held positions in the NVIDIA CUDA Platform team, and the Intel Microprocessor Technology Lab and Computational Software Lab. He was also awarded the 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.

Posts by Maxim Naumov

Accelerated Computing

Fast Spectral Graph Partitioning on GPUs

Graphs are mathematical structures used to model many types of relationships and processes in physical, biological, social and information systems. 15 MIN READ
Accelerated Computing

Graph Coloring: More Parallelism for Incomplete-LU Factorization

In this blog post I will briefly discuss the importance and simplicity of graph coloring and its application to one of the most common problems in sparse linear… 12 MIN READ