Query processing on GPU-style coprocessors is severely limited by the movement of data.
With teraflops of compute throughput in one device, even high-bandwidth memory cannot …

The huge demand for computation in artificial intelligence (AI) is driving unparalleled
investments in hardware and software systems for AI. This leads to an explosion in the …

Graphics Processing Units (GPUs) have evolved as a powerful query co-processor for main
memory On-Line Analytical Processing (OLAP) databases. However, existing GPU-based …

With the rise of Big Data, providing high-performance query processing capabilities through
the acceleration of the database analytic has gained significant attention. Leveraging Field …

Heterogeneous computing with GPUs integrated on the same chip as CPUs is ubiquitous,
and to increase programmability many of these systems support virtual address accesses …

Currently, we face the next major shift in processor designs that arose from the physical
limitations known as the" dark silicon effect". Due to thermal limitations and shrinking …

The impending end of Moore's Law has generated a surge of interest within the database
community in exploring alternative hardware solutions for efficiently handling database …

As large scale data processing becomes an ever more prominent component of modern
computing tasks, databases now exist as a fundamental necessity of most computational …

Multicore CPUs and cheap co-processors such as GPUs create opportunities for vastly
accelerating database queries. However, given the differences in their threading models …

As the rate of annual data generation grows exponentially, there is a demand to aggregate
and summarise vast amounts of information quickly. In the past, frequency scaling was relied …