Presentations by group members at external events

We present the implementation of a deconvolution algorithm for brain perfusion quantification on GPGPU (General Purpose Graphics Processor Units) using the CUDA programming model. GPUs originated as graphics generation dedicated co-processors, but the modern GPUs have evolved to become a more general processor capable of executing scientific computations. It provides a highly parallel computing environment due to its huge number of computing cores and constitutes an affordable high performance computing method.

The Data-Intensive Process Engineering Language (DISPEL) has been developed in the ADMIRE project to encourage partitioning of data-intensive process design and development. It manipulates processing elements and data streams to generate graphs that represent the requested processes. Some of the features of the language designed to make this possible will be introduced

Not every user knows how to submit a compute job by a remote login or to adapt to different job- submission systems when switching between facilities. In recognition, a recent trend is to provide web portals as an interface, which come in two types, each with its own major drawback. The first type consists of generic job-submission portals, which still require many technical specifics to be supplied by the user and much manual handling of data and results. The second type consists of domain-specific portals, which are expensive and time-consuming to build and maintain.

It is evident that data-intensive research is transforming computing landscape. We are facing the challenge of handling the deluge of data generated by sensors and modern instruments that are widely used in all domains. The number of sources of data is increasing, while, at the same time, the diversity, complexity and scale of these data resources are also growing dramatically. To survive the data tsunami, we need to improve our apparatus for the exploration and exploitation of the growing wealth of data.