Sparse linear algebra includes the fundamental and important operations in various large-
scale scientific computing and real-world applications. There exists performance bottleneck …

In computational biology, biological database search has been playing a very important role.
Since the COVID-19 outbreak, it has provided significant help in identifying common …

Molecular dynamics (MD) is one of the most crucial computer simulation methods for
understanding real-world processes at the atomic level. Reactive potentials based on the …

Sparse Tensor-Times-Matrix (SpTTM) is the core calculation in tensor analysis. The sparse
distributions of different tensors vary greatly, which poses a big challenge to designing …

As an essential mathematical operation, GEneral Matrix Multiplication (GEMM) plays a vital
role in many applications, such as high-performance computing, machine learning, etc. In …

Although GPUs can offer higher computing power at low power consumption, their low-level
programming can be relatively complex and consume programming time. For this reason …

Sparse Matrix and Vector multiplication (SpMV) is one of the core algorithms in various large-
scale scientific computing and real-world applications. With the rapid development of AI and …

Convolutional neural networks (CNNs) are widely utilized in intelligent edge computing
applications such as computational vision and image processing. However, as the number …

Sparse Matrix and Vector multiplication (SpMV) is one of the core algorithms in various large-
scale scientific computing and real-world applications. With the rapid development of AI and …