General Sparse Matrix-Matrix Multiplication (SpGEMM) has attracted much attention from
researchers in graph analyzing, scientific computing, and deep learning. Many optimization …

State-of-the-art engineering and science codes have grown in complexity dramatically over
the last two decades. Application teams have adopted more sophisticated development …

We explore the performance and portability of the high-level programming models: the
LLVM-based Julia and Python/Numba, and Kokkos on high-performance computing (HPC) …

Triangle counting is a building block for a wide range of graph applications. Traditional
wisdom suggests that i) hashing is not suitable for triangle counting, ii) edge-centric triangle …

Kokkos is a programming model for writing performance portable applications for all major
high performance computing platforms. It provides abstractions for data management and …

Template metaprogramming is gaining popularity as a high-level solution for achieving
performance portability on heterogeneous computing resources. Kokkos is a representative …

This paper presents software advances to easily exploit computer architectures consisting of
a multi-core CPU and CPU+ GPU to accelerate diverse types of high-performance …

In the near future, Exascale systems will need to bridge three technology gaps to achieve
high performance while remaining under tight power constraints: energy efficiency and …

Visualization is an important tool for scientists to extract understanding from complex
scientific data. Scientists need to understand the uncertainty inherent in all scientific data in …

Solving large number of small linear systems is increasingly becoming a bottleneck in
computational science applications. While dense linear solvers for such systems have been …