This seminar was held February 1-6, 2009, at Schloß Dagstuhl in Wadern, Germany. The Dagstuhl seminars are small scale events. Attendance is by invitation only. The goal is to not only exchange information, but also to encourage discussions and to get to know the attendees better. This approach worked out really well. Below my impressions on the scientific aspects of this event.
All the seminar information can be found at the workshop web site. This is also where you can find all the presentation material. I've posted my slides, but will also write an extended abstract for the proceedings. This will be more like a short paper.
The two major new things I learned at this event were in how many areas combinatorial analysis is used, and that many of the algorithms are characterized by random memory access on large data sets.
Regarding the former, I was for example surprised to hear that the analysis of social networks boils down to a combinatorial problem. When you think about it though, there is a natural link between these two. A new aspect is however that these networks, like LinkedIn or Hives, are so huge. Nobody really knows what they look like, and a deeper analysis of their structure can be revealing.
The computational aspects are quite interesting and challenging. In particular, traditional cache based architectures do not perform very well at all, due to the irregular memory access patterns, combined with the ever growing size of the data set. For the same reason, it is also a challenge for a cc-NUMA architecture to perform well.
Instead, heavily threaded architectures using latency hiding techniques shine on these kind of applications. Even an old system like the Tera MTA performs relatively well, despite its low clock rate. Several presenters reported excellent results on Niagara 2 and Victoria Falls based systems. For more details I can highly recommend the talk given by Prof. David Bader from the Georgia Institute of Technology. The slides can be found here.