Next generation architectures and systems being deployed are characterized by high concurrency, low memory per-core, and multiple levels of hierarchy and heterogeneity. These characteristics bring out new challenges in energy efficiency, fault-tolerance and, scalability. It is commonly believed that software has the biggest share of the responsibility to tackle these challenges. In other words, this responsibility is delegated to the next generation programming models and their associated middleware/runtimes. This workshop focuses on different aspects of programming models such as task-based parallelism (Charm++, OCR, Habanero, Legion, X10, HPX, etc), PGAS (OpenSHMEM, UPC, CAF, Chapel, UPC++, etc.), BigData (Hadoop, Spark, etc), Deep Learning (Caffe, Microsoft CNTK, Google TensorFlow), directive-based languages (OpenMP, OpenACC) and Hybrid MPI+X, etc. It also focuses on their associated middleware (unified runtimes, interoperability for hybrid programming, tight integration of MPI+X, and support for accelerators) for next generation systems and architectures.
The ultimate objective of the ESPM2 workshop is to serve as a forum that brings together researchers from academia and industry working in the areas of programming models, runtime systems, compilation and languages, and application developers.
Intel has generously offered to sponsor the Best Paper Award. This award will be given to the author(s) of the paper selected by the Technical Program Committee and the Program Chairs. The award will be determined from viewpoints of the technical and scientific merits, impact on the science and engineering of the research work and the clarity of presentation of the research contents in the paper.
We are happy to announce that Prof. William D. Gropp, Interim Director and Chief Scientist at the National Center for Supercomputing Applications and the Thomas M. Siebel Chair in Computer Science at the University of Illinois Urbana-Champaign will deliver the keynote address at ESPM2'17.
Panel: Effective Programming Models for Deep Learning at scale
Panel Moderator : Daniel Holmes, EPCC, The University of Edinburgh, UK.
The workshop does not have a separate registration site. All attendees need to use the registration system provided by SC'17. Please remember to select the workshop option when registering. Details about registration can be found on the main conference website.