Following the mass adoption of external accelerators for high performance computing, the
overall performance of many applications has become increasingly dependent on relatively …

Modern computing platforms are increasingly heterogeneous, most of them include
accelerators such as GPU. OpenMP as the de-facto standard to parallelize CPU …

Currently, offloading to accelerators requires users to identify which regions are to be
executed on the device, what memory needs to be transferred, and how synchronization is …

General-Purpose Computation on Graphics Processing Units (GPGPUs) are becoming
crucial in accelerating computing capacity. Due to the massive parallelism capabilities of …

In contemporary high-performance computing architectures, the integration of GPU
accelerators has become increasingly prevalent. To harness the full potential of these …

As the supercomputing landscape diversifies, solutions such as Kokkos to write vendor
agnostic applications and libraries have risen in popularity. Kokkos provides a programming …

Utilizing GPUs is critical for high performance on heterogeneous systems. However,
leveraging the full potential of GPUs for accelerating legacy CPU applications can be a …

Programming models for general purpose GPU (GPGPU) computing include grid and non-
grid languages. Grid languages like CUDA and HIP map directly to the GPU hardware and …

MPI+ X has been the de facto standard for distributed memory parallel programming. It is
widely used primarily as an explicit two-sided communication model, which often leads to …

GPGPUs are widely used in high-performance computing. Therefore, it is crucial to
experiment and discover how to better utilize their latest generations of relevant …