At the International Research Workshop on Advanced High Performance Computing Systems in Cetraro in June 2012, two of the main workshop topics were High Performance Computing (HPC) in the Cloud and Big Data.

Cloud computing offers many advantages to researchers and engineers who need access to high performance computing facilities for solving particular compute intensive and/or large scale problems, but whose overall HPC needs do not justify the acquisition and operation of dedicated HPC facilities. The questions surrounding the efficient and effective utilization of HPC cloud facilities are, however, numerous, with perhaps the most fundamental issues being the limitations imposed by accessibility, security and communication speeds.

Therefore, in order to mobilize the full potential of cloud computing as an HPC platform a number of fundamental problems must be addressed. On the one hand it must be identified which classes of problems are amenable to the cloud computing paradigm with its limitations. On the other hand it must be clarified which technologies, techniques and tools are needed to enable a widely acceptable use of cloud computing for HPC.

The second topic, big data, is nothing new. Large scientific organizations have been collecting large amounts of data for decades. What is new, however, is that the focus has now broadened to almost all sectors – be it business analytics in enterprises, financial analyses, Internet service providers, oil and gas, medicine, automotive, and a long list of others.

This book presents three chapters with together 14 contributions, selected from the International Research Workshop on Advanced High Performance Computing Systems in Cetraro in June 2012. The five contributions of the first chapter on “Cloud Infrastructures” discuss several important topics of High Performance Computing in the cloud, covering automatic clouds with an open-source and deployable Platform-as-a-Service; QoS-aware cloud application management; building secure and transparent inter-cloud infrastructure for scientific applications; cloud adoption issues such as interoperability and security; and semantic technology for supporting software portability and interoperability in the cloud.

Chapter two discusses “Cloud Applications”, with a focus on using clouds for technical computing; dynamic job scheduling of parametric computational mechanics studies; the bulk synchronous parallel model; and executing multi-workflow simulations on clouds.

Finally, the articles in chapter three are dealing with “Big Data” problems such as ephemeral materialization points in stratosphere data management on the cloud; a cloud framework for big data analytics workflows; high performance big data clustering; scalable visualization and interactive analysis using massive data streams; and mammoth data in the cloud from clustering social images. The editors wish to thank all the authors for preparing their contributions as well as the many reviewers who supported this effort with their constructive recommendations.

Charlie Catlett, USA

Wolfgang Gentzsch, Germany

Lucio Grandinetti, Italy

Gerhard Joubert, Netherlands/Germany

José Luis Vazquez-Poletti, Spain

14 July 2013