15 citations · 52 across the 9 of their papers we have counts for
3 papers · 1 filter
Improving the performance of the linear systems solvers using CUDA
Bogdan Oancea, Tudorel Andrei, Raluca Mariana Dragoescu
Parallel computing can offer an enormous advantage regarding the performance for very large applications in almost any field: scientific computing, computer vision, databases, data…
Developing a High Performance Software Library with MPI and CUDA for Matrix Computations
Bogdan Oancea, Tudorel Andrei
Nowadays, the paradigm of parallel computing is changing. CUDA is now a popular programming model for general purpose computations on GPUs and a great number of applications were p…
Accelerating R with high performance linear algebra libraries
Bogdan Oancea, Tudorel Andrei, Raluca Mariana Dragoescu
Linear algebra routines are basic building blocks for the statistical software. In this paper we analyzed how can we can improve R performance for matrix computations. We benchmark…