4th International Workshop on Legacy HPC Application Migration
To be held in conjunction with CANDAR'16, Hiroshima, Japan, November 22-25, 2016.
In HPC software development, a high priority is given to performance. As system-specific optimizations are almost always required to fully exploit the potential of a system, application programmers usually optimize their application programs for particular systems. Whenever the target system of an application program is changed to a new one, thus, they need to adapt the program to the new system. This is so-called legacy HPC application migration. The migration cost increases with the hardware complexity of target systems. Since future HPC systems are expected to be extremely massive and heterogeneous, migration will require more efforts and will be essential for performance in the upcoming extreme-scale computing era. Therefore, this International Workshop on Legacy HPC Application Migration (LHAM) offers an opportunity to share practices and experience of legacy HPC application migration, and also discuss coming and developing technologies and research directions to reduce the migration cost.
Previous LHAM workshops:
Topics of interest include, but are not limited to
- Programming models, languages and frameworks for supporting HPC application migration.
- Algorithms and implementation schemes for future-generation computing systems.
- Runtime systems for hiding the complexity of underlying system architectures.
- Practices and experience of HPC application migration.
Prof. Vladimir Voevodin
- Deputy Director, Research Computing Center, Lomonosov Moscow State University;
- Head of the Department on Supercomputers and Quantum Informatics, Computational Mathematics and Cybernetics Faculty, MSU.
Title of the talk
Algorithmic Challenges of Legacy HPC Application Migration
High performance computing clusters, SMP-machines, GPU- or Phi-based computing systems, vector computers, FPGA accelerators, small, medium or petascale supercomputers… Diversity of modern computing systems is great and their huge potential allows complex problems, previously thought impossible, to be solved. By now, computing community has developed highly valuable and wide spectrum of software with a hope to use this wealth of codes on the next generation computers for a long time. At the same time, the efficient usage of all opportunities offered by modern computing systems through a large number of applications represents a global challenge and requires new knowledge, skills and abilities, where one of the main roles belongs to understanding of key properties of parallel algorithms. The talk will address the urgent need for theoretical and practical technologies of an accurate and concerted design of highly parallel algorithms and extreme scaled applications to be able to solve large problems through a variety of different computing platforms. Deep understanding of algorithmic structures will provide a key to successful application migration while preserving a high level of efficiency.
Vladimir Voevodin is Deputy Director of the Research Computing Center at Lomonosov Moscow State University. He is Head of the Department “Supercomputers and Quantum Informatics” at the Computational Mathematics and Cybernetics Faculty of MSU, professor, corresponding member of Russian academy of sciences. Vl. Voevodin specializes in parallel computing, supercomputing, extreme computing, program tuning and optimization, fine structure of algorithms and programs, parallel programming technologies, scalability and efficiency of supercomputers and applications, supercomputing co-design technologies, software tools for parallel computers, and supercomputing education. His research, experience and knowledge became a basis for the supercomputing center of Moscow State University, which was founded in 1999 and is currently the largest supercomputing center in Russia. He has contributed to the design and implementation of the following tools, software packages, systems and online resources: V- Ray, X-Com, AGORA, Parallel.ru, hpc-education.ru, hpc-russia.ru, LINEAL, Sigma, Top50, OctoShell, Octotron, AlgoWiki. He has published over 100 scientific papers with 4 books among them. Vl.Voevodin is one of the founders of Supercomputing Consortium of Russian Universities established in 2008, which currently comprises more than 60 members. He is a leader of the major national activities on Supercomputing Education in Russia and General Chair of the two largest Russian supercomputing conferences.
- Regular paper: 5-7 pages
- Poster paper: 3-4 pages
Please see Workshop Paper Submission Instruction.
See details at: http://is-candar.org/schedule/
The conference and workshop proceedings will be published by Conference Publishing Service and submitted to IEEE Xplore and CSDL digital libraries. Also they are submitted for indexing through INSPEC, EI (Compendex), Thomson ISI, and other indexing services.
We plan to publish extended versions of selected papers from CANDAR'16 main conference and workshops. Please see Special Issue for the details.
- Ryusuke Egawa, Tohoku University, Japan.
- Hiroyuki Takizawa, Tohoku University, Japan.
- Reiji Suda, The University of Tokyo, Japan.
- Daisuke Takahashi, University of Tsukuba, Japan.
- Kazuhiko Komatsu, Tohoku University, Japan.
- Shoichi Hirasawa, Tohoku University, Japan.
- Wen-mei Hwu, The University of Illinois at Urbana-Champaign, USA.
- Chisachi Kato, The University of Tokyo, Japan.
- Michael Resch, The High Performance Computing Center Stuttgart, Germany.
- Ryusuke Egawa (PC chair) (Tohoku University)
- Ritu Arora (The Texas Advanced Computing Center)
- Carlo Cavazzoni (Cineca)
- Toshio Endo (Tokyo Institute of Technology)
- Keiichiro Fukazawa (Kyoto University)
- Edgar Gabriel (University of Houston)
- JosE Gracia (High Performance Computing Center Stuttgart)
- Mary Hall (University of Utah)
- Masamoto Hashimoto (RIKEN)
- Shoichi Hirasawa (Tohoku University)
- Fumihiko Ino (Osaka University)
- Harald Klimach (Universitat Siegen)
- Kazuhiko Komatsu (Tohoku University)
- Atsushi Kubota (Hiroshima City University)
- Kiyoshi Kumahata (RIKEN)
- Seyong Lee (ORNL)
- Shirley Moore (The University of Texas at El Paso)
- Masahiro Nakao (RIKEN)
- Takeshi Nanri (Kyushu University)
- Kamil Rocki (IBM)
- Reiji Suda (The University of Tokyo)
- Hiroyuki Takizawa (Tohoku University)
- Michele Weiland (EPCC)