In the past decade, Graphics Processing Units have played an important role in the field of
high-performance computing and they still advance new fields such as IoT, autonomous …

The Single Instruction Multiple Data (SIMD) architecture, supported by various high-
performance computing platforms, efficiently utilizes data-level parallelism. The SIMD model …

In recent years, the heterogeneity of both commodity and supercomputers hardware has
increased sharply. Accelerators, such as GPUs or Intel Xeon Phi co-processors, are often …

Nonuniform fast Fourier transforms dominate the computational cost in many applications
including image reconstruction and signal processing. We thus present a general-purpose …

Xmipp is an open-source software package consisting of multiple programs for processing
data originating from electron microscopy and electron tomography, designed and managed …

Automatic parallelization of sequential programs combined with auto-tuning is an alternative
to manual parallelization. With wider research directions and the increased number of …

Nowadays, GPU accelerators are commonly used to speed up general-purpose computing
tasks on a variety of hardware. However, due to the diversity of GPU architectures and …

Many state-of-the-art HPC applications rely on autotuning to maintain peak performance.
Autotuning allows a program to be re-optimized for new hardware, settings, or input–even …

Modern computers are typically heterogeneous devices—besides the standard central
processing unit (CPU), they commonly include an accelerator such as a graphics processing …

The fast development of biomolecular structure determination has enabled the fine-grained
study of objects in the micro-world, such as proteins and RNAs. The world is benefited …