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ORCIDSupercomputing Frontiers and Innovations, Volume 6
Volume 6, Number 1, 2019
- Alexander L. Pleshkevich, Anton V. Ivanov, Vadim D. Levchenko, Sergey A. Khilkov, Boris P. Moroz:
Efficient Parallel Implementation of Multi-Arrival 3D Prestack Seismic Depth Migration. 4-8 - Andrey A. Shemukhin, Anton V. Nazarov
, Anton V. Stepanov:
LAMMPS Code Simulation of the Defect Formation Induced by Ion Incidence in Carbon Nanotubes. 9-13 - Andrey D. Bulygin, Denis A. Vrazhnov:
A Fully Conservative Parallel Numerical Algorithm with Adaptive Spatial Grid for Solving Nonlinear Diffusion Equations in Image Processing. 14-18 - Philipp S. Orekhov, Ilya V. Kirillov, Vladimir A. Fedorov, Ilya B. Kovalenko, Nikita B. Gudimchuk, Artem A. Zhmurov:
Parametrization of the Elastic Network Model Using High-Throughput Parallel Molecular Dynamics Simulations. 19-22 - Chaoqun Sha, Jingfeng Zhang, Lei An, Yongsheng Zhang, Zhipeng Wang, Tomi Ilijas, Nejc Bat, Miha Verlic, Qing Ji:
Facilitating HPC Operation and Administration via Cloud. 23-35 - Kenta Yamaguchi, Takashi Soga, Yoichi Shimomura, Thorsten Reimann, Kazuhiko Komatsu, Ryusuke Egawa, Akihiro Musa, Hiroyuki Takizawa, Hiroaki Kobayashi:
Performance Evaluation of Different Implementation Schemes of an Iterative Flow Solver on Modern Vector Machines. 36-47 - Gleb I. Radchenko, Ameer B. A. Alaasam, Andrei Tchernykh:
Comparative Analysis of Virtualization Methods in Big Data Processing. 48-79
Volume 6, Number 2, 2019
- Vladimir V. Voevodin, Alexander S. Antonov, Dmitry A. Nikitenko, Pavel A. Shvets, Sergey I. Sobolev, Igor Yu. Sidorov, Konstantin S. Stefanov, Vadim V. Voevodin, Sergey A. Zhumatiy:
Supercomputer Lomonosov-2: Large Scale, Deep Monitoring and Fine Analytics for the User Community. 4-11 - Damian Kaliszan, Norbert Meyer, Sebastian Petruczynik, Michael Gienger, Sergiy Gogolenko:
HPC Processors Benchmarking Assessment for Global System Science Applications. 12-28 - Aamer Shah, Chih-Song Kuo, Akihiro Nomura, Satoshi Matsuoka, Felix Wolf:
How File-access Patterns Influence the Degree of I/O Interference between Cluster Applications. 29-55 - Grzegorz Korcyl, Piotr Korcyl:
Investigating the Dirac Operator Evaluation with FPGAs. 56-63 - Felix Kaiser, Stefan Kosnac, Ulrich Brüning:
Development of a RISC-V-Conform Fused Multiply-Add Floating-Point Unit. 64-74 - Brandon Cloutier, Benson K. Muite, Matteo Parsani:
Fully Implicit Time Stepping Can Be Efficient on Parallel Computers. 75-85 - Ilya S. Pershin, Vadim D. Levchenko, Anastasia Y. Perepelkina:
Performance Limits Study of Stencil Codes on Modern GPGPUs. 86-101 - Igor A. Ostanin:
Distinct Element Simulation of Mechanical Properties of Hypothetical CNT Nanofabrics. 102-111
Volume 6, Number 3, 2019
- Julian Hornich, Julian Hammer, Georg Hager, Thomas Gruber, Gerhard Wellein:
Collecting and Presenting Reproducible Intranode Stencil Performance: INSPECT. 4-25 - Alexey V. Sulimov, Danil C. Kutov, Vladimir B. Sulimov:
Supercomputer Docking. 26-50 - Valentin Clement, Philippe Marti, Xavier Lapillonne, Oliver Fuhrer, William B. Sawyer:
Automatic Port to OpenACC/OpenMP for Physical Parameterization in Climate and Weather Code Using the CLAW Compiler. 51-63 - Kunal Banerjee, Evangelos Georganas, Dhiraj D. Kalamkar, Barukh Ziv, Eden Segal, Cristina Anderson, Alexander Heinecke:
Optimizing Deep Learning RNN Topologies on Intel Architecture. 64-85 - Hikaru Takayashiki, Masayuki Sato, Kazuhiko Komatsu, Hiroaki Kobayashi:
A Skewed Multi-banked Cache for Many-core Vector Processors. 86-101
Volume 6, Number 4, 2019
- Masayuki Sato, Takuya Toyoshima, Hikaru Takayashiki, Ryusuke Egawa, Hiroaki Kobayashi:
An Energy-aware Dynamic Data Allocation Mechanism for Many-channel Memory Systems. 4-19 - Saad Alowayyed, Maxime Vassaux, Benjamin Czaja, Peter V. Coveney, Alfons G. Hoekstra:
Towards Heterogeneous Multi-scale Computing on Large Scale Parallel Supercomputers. 20-43 - Andrey V. Gorobets, Pavel A. Bakhvalov:
Improving Reliability of Supercomputer CFD Codes on Unstructured Meshes. 44-56 - Denis Shaikhislamov, Andrey Sozykin, Vadim V. Voevodin:
Survey on Software Tools that Implement Deep Learning Algorithms on Intel/x86 and IBM/Power8/Power9 Platforms. 57-83
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