Abbrevation
CPHPCA
City
Paris
Country
France
Deadline Paper
Start Date
End Date
Abstract

The main proposal of CPHPCA is to provide a scenario to discuss how those problems compromising important challenges and high computational requirements can be mapped over current and upcoming high performance architectures&#046; CPHPCA will be a part (in conjunction) with the 18th IEEE International Conference on Computational Science and Engineering (CSE&#8242;16)&#046;<br>The importance of high performance computing is increasing and has become as one of the foremost fields of computing research&#046; This raise brings up many issues, in form of new network topologies and technologies (fast accessing data), new low&#8211;consumption architectures, new programming models, etc&#046; It forces us to adapt our codes or create new ones to take advantages of the last computational features&#046;<br>This workshop focuses on the challenges that suppose how to adapt/implement complex and big problems over those platforms composed by a high number of cores, dealing with communication, programming, heterogeneous architectures, load balancing, benchmarking, etc&#046; Today, the difficulty of the problems to be implemented is increasing considerably, large data and computational requirements, dynamic behavior, numerical simulations, automatic modeling, are just a few examples of this kind of problems&#046;<br>The goal of this workshop is to bridge the gap between the theory of complex problems (computational fluid dynamics, bio&#8211;informatics, linear algebra, big data computing, deep&#8211;learning, data mining, &#046;&#046;&#046;) and high performance computing platforms by proposing new trends/directions in programming&#046;<br>Topics<br>Authors are invited to submit manuscripts that present original and unpublished research in all areas related with programming of complex problems via parallel and distributed processing&#046; Works focused on emerging architectures and big computing challenges are especially welcome&#046;<br>Relevant topics include, but are not limited to:<br>· New strategies to improve performance<br>· Code adapting to take advantages of lastest features<br>· Numerical modeling for complex problems<br>· Communication, synchronization, load balancing<br>· Benchmarking, performance and numerical accuracy analysis<br>· Scalability of algorithms and data structures<br>· New programming models<br>· Auto&#8211;Tunning Computing Systems<br>· High level abstraction tools<br>