In recent years our ability to produce information has been growing steadily, driven by an ever increasing computing power, communication rates, hardware and software sensors diffusion. The topic of Data Stream Processing (DaSP) is a recent and highly active research area dealing with the processing of this streaming data. Several important on-line and real-time applications can be modeled as DaSP, including network traffic analysis, financial trading, data mining, and many others.
Strong performance requirements are typical in DaSP scenarios: high-throughput and low-latency are unavoidable constraints that imply a careful design and the definition of novel cost models of parallel patterns supporting the parallelization of DaSP operators. One of the objective of the PPM group is to study innovative parallel programming techniques and run-time supports enabling High-Performance Data Stream Processing.