High Performance Computing Solutions for Complex Problems

In the last decades, the complexity of the current and upcoming scientific/engineering problems has increased considerably. Computations involved in numerical and physical simulations, molecular dynamics, fluid dynamics, bio-informatics, image processing, deep-learning, information retrieval, linear algebra or big-data computing are just a few examples of such problems.

At the same time, improvements in high performance computing (HPC) systems are mainly associated with an increased complexity of computer architectures, resulting in increasing challenges in code optimization. This results in an increasing gap between the general scientific / engineering user community (in need of easy access to efficient high performance computations) and the HPC programmers community (who design codes for narrow sub-classes of problems). As a result, the development of user-friendly codes for non-HPC-trained user community becomes a big challenge. As a matter of fact, effective use of HPC centers requires specialized / individual training for each user group. The aim of this special issue report on efforts to reduce this gap by means of bringing new ways to face the growing complexity of problems that are to be solved. Specifically, we would like to address challenges involved in implementing large and complex problems on current and upcoming platforms, composed of a high number of computational cores. Thus, the issues to be addressed should deal with communication, programming, heterogeneous architectures, load balancing, benchmarking, etc. However, the overall goal should be development of solutions that are going to be usable by non-HPC-trained domain specialists.



Authors are invited to submit manuscripts which present original and unpublished research in all areas related with complex problems solving via parallel and distributed processing, i.e., works focused on emerging solutions to face with big computing challenges on HPC systems are specially welcome. Relevant topics include, but are not limited to:

  • Benchmarking, performance and scalability of algorithms, data structures, tools.
  • Code adapting to take advantages of latest computational features.
  • New strategies to improve performance.
  • Auto-tuning computing systems.
  • New transparent, portable, and hardware diagnostic programming paradigms.
  • Advances in current or upcoming HPC platforms.
  • Communication, synchronization, load balancing.


Important dates:

  • Submission: December 23, 2016, January 14, 2017
  • Author notification: April 28, 2017
  • Revised papers: May 19, 2017
  • Author notification: June 2, 2017
  • Camera Ready papers due: June 16, 2017
  • Publication: June 30, 2017


Submission guidelines:

Original and unpublished works on any of the topics aforementioned or related are welcome. The SCPE journal has a rigorous peer-reviewing process and papers will be reviewed by at least three S.C. referees. All submitted papers must be formatted according to the journal's instructions, which can be found at: 



Special issue editors:

  • Dr. Pedro Valero Lara, University of Manchester, UK.
  • Prof. Dr. Fernando L. Pelayo, University of Castilla-La Mancha, Spain.
  • Dr. Mawussi Zounon, University of Manchester, UK.    
  • Dr. Maxim Abalenkov, University of Manchester, UK.