One-sided dense matrix decompositions (e.g., Cholesky, LU, and QR) are t...
Data compression is becoming critical for storing scientific data becaus...
Sparse linear algebra kernels play a critical role in numerous applicati...
The applications being developed within the U.S. Exascale Computing Proj...
Rapid growth in scientific data and a widening gap between computational...
Designing efficient and scalable sparse linear algebra kernels on modern...
Today's high-performance computing (HPC) applications are producing vast...
Data management is becoming increasingly important in dealing with the l...
Testing is one of the most important steps in software development. It
e...
In natural language processing (NLP), the "Transformer" architecture was...
Rapid growth in scientific data and a widening gap between computational...
Convolutional neural networks (CNNs) are becoming more and more importan...
Linear algebra operations have been widely used in big data analytics an...
High performance multi-GPU computing becomes an inevitable trend due to ...
Variations in High Performance Computing (HPC) system software configura...