To support their massively-multithreaded architecture, GPUs use very large register file (RF)
which has a capacity higher than even L1 and L2 caches. In total contrast, traditional CPUs …

Tensor Core Unit (TCU) is increasingly integrated into modern high-performance processors
to enhance matrix multiplication performance. However, constrained to its over-specification …

Heterogeneous computing, which combines devices with different architectures, is rising in
popularity, and promises increased performance combined with reduced energy …

With the unprecedented development of compute capability and extension of memory
bandwidth on modern GPUs, parallel communication and synchronization soon becomes a …

Heterogeneous computing, combining devices with different architectures such as CPUs
and GPUs, is rising in popularity and promises increased performance combined with …

Spatial blocking is a critical memory-access optimization to efficiently exploit the computing
resources of parallel processors, such as many-core GPUs. By reusing cache-loaded data …

Stencil computations play a pivotal role in numerous scientific and industrial applications,
yet their efficient execution on specialized hardware accelerators like Tensor Core Units …

Stencil computation is one of the most universal computation motifs in scientific applications
such as weather prediction. Due to the complexity of scientific simulation, the stencil …

Batched dense linear algebra kernels are becoming ubiquitous in scientific applications,
ranging from tensor contractions in deep learning to data compression in hierarchical low …

Stencils computations are a class of computations commonly found in scientific and
engineering applications. They have relatively lower arithmetic intensity. Therefore, their …