Title: Proceedings of the first workshop on Parallel programming for analytics applications
Abstract: "Necessity is the mother of invention". That premise motivated the organizers of this workshop and the program committee to bring together communities that need vast amounts of computingresources for big analytics problems and the communities that can build computing platforms to solve those problems. It is our great pleasure to welcome you to the First Workshop on Parallel Programming for Analytics Applications (PPAA). Analytics applications are scaling rapidly in terms of the size and variety of data analyzed, the complexity of models explored and tested, and the number of analytics professionals or data scientists supported concurrently. At the same time hardware systems are embracing new technologies like on-chip and off-chip accelerators, vector extensions to instruction sets, and solid state disks. New programming methodologies and run-times to support them are emerging to facilitate the development of new analytics applications, and to leverage emerging systems. This workshop provides a forum for the applications community, runtime and development environment community and systems community to exchange the outlook for progress in each of these areas and exchange ideas on how to cross leverage the progress. We especially encourage attendees to attend the keynote and invited talk presentations. These valuable and insightful talks can and will guide us to a better understanding of the future: Future Directions in Analytic Applications, Dr. Edward J. Baranoski (currently Director of the Office of Smart Collection at Intelligence Advanced Research Projects Activity (IARPA) where the focus is on dramatically improving the value of collected data from all sources.)Cognitive Computing Journey, David Nahamoo (currently at IBM Research, focusing on cognitive computing.)Graphs & Networks: Computing and Analytics at Lincoln Laboratory, Robert A. Bond (currently with IBM Lincoln Labs architectures, conducting research that support graph analytics as data sets scale to million-node graphs and beyond.)High-speed Graph Analytics with the Galois System, Dr. Keshav Pingali (Professor in the Department of Computer Science at the University of Texas at Austin, research is focused on programming languages and tools for multicore and manycore processors.)
Publication Year: 2014
Publication Date: 2014-02-16
Language: en
Type: paratext
Indexed In: ['crossref']
Access and Citation
Cited By Count: 6
AI Researcher Chatbot
Get quick answers to your questions about the article from our AI researcher chatbot