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 …

Despite recent increase in research on improvement of non-functional properties of
software, such as energy usage or program size, there is a lack of standard benchmarks for …

Futhark is a purely functional data-parallel array language that offers a machine-neutral
programming model and an optimising compiler that generates OpenCL code for GPUs …

This paper presents a comprehensive performance comparison between CUDA and
OpenCL. We have selected 16 benchmarks ranging from synthetic applications to real-world …

Tuning code for GPGPU and other emerging many-core platforms is a challenge because
few models or tools can precisely pinpoint the root cause of performance bottlenecks. In this …

Branch divergence has a significant impact on the performance of GPU programs. We
propose two novel software-based optimizations, called iteration delaying and branch …

Leveraging large data sets, deep Convolutional Neural Networks (CNNs) achieve state-of-
the-art recognition accuracy. Due to the substantial compute and memory operations …

The power-efficient massively parallel Graphics Processing Units (GPUs) have become
increasingly influential for general-purpose computing over the past few years. However …

We consider the problem of how to improve memory latency tolerance in massively
multithreaded GPGPUs when the thread-level parallelism of an application is not sufficient to …

Initially introduced as special-purpose accelerators for games and graphics code, graphics
processing units (GPUs) have emerged as widely-used high-performance parallel …