[hpc-announce] Call for papers: Special Issue for Advances in Software Engineering Journal

[Lee, Seyong]

Advanced Software Development of GPU Cluster Computing
Call for Papers

General purpose GPU recently has successfully drawn attention from high-performance computing due to higher core density and lower EPI value than CPU. The newest report of Top500 shows that there are thirty-nine supercomputing systems using GPUs to accelerate data computation: two Chinese systems called Tianhe-1A and Nebulaeare at No. 2 and No. 4 and one Japanese system called Tsubame 2.0 at No. 5 are on this list. Amazon has announced the availability of Cluster GPU Instances for Amazon EC2 to deliver the computational power of GPUs in Clouds. More and more researchers have used GPU clusters instead of CPU clusters for resolving their massive-computation problems such as high energy physics, scientific simulation, data mining, climate forecast, and earthquake prediction. As the impact of GPU on both of the academic and engineering areas is increasing rapidly, many issues of GPU cluster computing have to be addressed further in order for improving and enriching the user experience and applications of GPU cluster computing. For example, the complexity of the GPU programming such as CUDA and OpenCL is too high for users to move their applications towards this new computing platform since these programming interfaces and models are quite different from MPI or OpenMP, which are popularly used in CPU cluster computing. In addition, users lack friendly and efficient tools such as debugger and performance analyzer during the period of program development. On the other hand, the computing systems built on GPU clusters require useful tools in emergence to effectively monitor and manage GPU resources for system throughput and to maintain the QoS and reliability of the execution of user applications. As previously described, this special issue is aimed at providing a forum for researchers to present their innovative design, implementation, and experience in software of GPU cluster computing. We encourage authors to submit high-quality, original, unpublished papers. Potential topics include, but are not limited to:

 *   Programming models: thread- and task-based models, data parallel models, and stream programming
 *   Language extensions for GPU programming, such as CUDA, OpenCL, OpenMP, MPI, CAL, HMPP, and PGI
 *   Program development tools such as compiler, debugger, and performance analyzer
 *   Runtime systems for supporting shared memory abstraction, load balance, and resource reallocation
 *   Resource monitor and manager and job scheduler
 *   QoS and fault tolerance of GPU cluster computing
 *   Applications or problem-resolving environment based on GPU clusters
 *   Measurement and profile of energy consumption of GPU clusters
 *   Power-aware software, middleware, runtime system for GPU cluster computing
 *   Service-oriented architecture of GPU cluster computing
 *   Software engineering methodology and solutions for GPU cluster computing

Before submission authors should carefully read over the journal's Author Guidelines, which are located at http://www.hindawi.com/journals/ase/guidelines/. Prospective authors should submit an electronic copy of their complete manuscript through the journal Manuscript Tracking System athttp://mts.hindawi.com/ according to the following timetable:

Manuscript Due  Friday, 27 July 2012
First Round of Reviews  Friday, 19 October 2012
Publication Date        Friday, 14 December 2012
Lead Guest Editor

 *   Tyngyeu Liang<mailto:lty at mail.ee.kuas.edu.tw>, Department of Electrical Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung City, Taiwan

Guest Editors

 *   Qiong Luo<mailto:luo at cse.ust.hk>, Department of Computer Science and Engineering, Hong Kong University of Science and Technology, Hong Kong
 *   Seyong Lee<mailto:lees2 at ornl.gov>, Future Technologies Group, Oak Ridge National Laboratory, P.O. Box 2008, Oak Ridge, TN 37831, USA