The multi-core architectures of today's computer systems make parallelism a necessity for
performance critical applications. Writing such applications in a generic, hardware-oblivious …

Modern graphics cards bundle high-bandwidth memory with a massively parallel processor,
making them an interesting platform for running data-intensive operations. Consequently …

In this paper, we show how we use Nvidia GPUs and host CPU cores for faster query
processing in a DB2 database using BLU Acceleration (DB2's column store technology) …

Since a decade, the database community researches opportunities to exploit graphics
processing units to accelerate query processing. While the developed GPU algorithms often …

Column-store in-memory databases have received a lot of attention because of their fast
query processing response times on modern multi-core machines. Among different …

To achieve scalable data intensive analytics, we investigate methods to integrate general
purpose analytic computation into a query pipeline using User Defined Functions (UDFs) …

Modern high-performance server systems with their wide variety of compute resources (ie
multi-core CPUs, GPUs, FPGAs, etc.) bring vast computing power to the fingertips of …

This thesis first maps the relational computation onto Graphics Processing Units (GPU) s by
designing a series of tools and then explores the different opportunities of reducing the …

Deconvolution is a key operation for the post-processing of ultra-wideband (UWB) channel
modeling. Due to the wideband of the radio channel sounding pulse, the nature of the UWB …

Computing hardware is changing from systems with homogeneous CPUs to systems with
heterogeneous computing units like GPUs, Many Integrated Cores, or FPGAs. This trend is …