September 21-26, 2014
University Residential Center
Bertinoro (Forlì-Cesena), Italy

ScalPerf aims at taking an integrated view of opportunities and constraints on the road to ever higher performance and productivity of computing systems. Distinguished researchers are invited to exchange their perspectives on different areas that can contribute to scalable computing.

The workshop will include invited talks and discussion sessions. The talks can cover established results as well as brain storm on future research directions. The discussion sessions are two, each consisting of a first part to sharpen the formulation of the issues and a second part to explore answers. This year, the topic of discussion is

High performance graph algorithms
and graph theoretic models for performance


Graph algorithms have always been considered important for computing; in the past few years there has been a renewed interest fueled by applications in the field of analytics, social networks, etc... A number of similarities to High Performance Computing (HPC) have emerged as well as significant overlaps with both data base technologies and HPC sparse matrix technologies.

Graphs have also been extensively used as models for both machines and computations, e.g., in the study of performance in hierarchical memory systems and in communication networks.

The workshop will focus on recent development concerning this dual role of graphs in high performance computing. On the one side, the topic is well aligned with the tradition of ScalPerf and the areas of interest of its participants; on the other side, the new applications pose new genuine research challenges, pretty much for all areas of computing.

Participants will be invited to submit suggestions for specific issues to include in the discussion a few weeks before the workshop.

In addition to the invited speakers, participation of other interested researchers, particularly graduate students and junior researchers, is welcome. An expression of interest can be sent to, including a brief CV.