CFP - Special Issue on High Performance Computing Solutions for Complex Problems


Scalable Computing: Practice and Experience

Special Issue: 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, information 
retrieval, or big data analysis 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, 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unpublished research in all areas related with complex problems solving 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, etc
- Code adapting to take advantages of latest computational features.
- New strategies to improve performance.
- Adaptive self-tuning computing systems.
- New transparent, portable, and hardware diagnostic programming paradigms.
- Advances in current or upcoming HPC tools.
- Communication, synchronization, load balancing.


- Submission: September 19, 2015
- Author notification: January 31, 2016
- Revised papers: February 15, 2016
- Author notification: March 1, 2016
- Camera Ready papers due: March 15, 2016
- Publication: March 31, 2016


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:


- Dr. Pedro Valero Lara, Basque Center for Applied Mathematics (BCAM), 
Bilbao, Spain.
- Prof. Dr. Fernando L. Pelayo, University of Castilla-La Mancha, 
Albacete, Spain.
- Prof. Dr. Johan Jansson, Basque Center for Applied Mathematics (BCAM), 
Bilbao, Spain and KTH, Royal Institute of Technology, Stockholm, Sweden.


The journal focus on algorithm development, implementation and execution 
on parallel and distributed architectures, as well on application of 
parallel and distributed computing to the solution of real-life 
problems. SCPE provides immediate open access to its content. The 
journal is submitted for indexation in Scopus SciVerse, The Collection 
of Computer Science Bibliographies, Directory of Open Access Journals 
(DOAJ), EBSCO, dblp - Computer Science Bibliography, CiteFactor, Index 
Copernicus, Open Access Library, J-Gate, ZDB, AcademicKeys, BibNet 
Project at University of Utah, ZENODO, Journal Click. In 2013, the 
SCPE's SNIP (Scopus Source Normalized Impact per Paper) was 0.619 and 
SCPE's SJR (Scimago Journal Ranking) was 0.151 (previous year values 
where: SNIP 0.376 and SJR 0.105). SCPE's SJIF factor was 2.785 in 2012.

Received on Saturday, 23 May 2015 19:39:55 UTC