Article

Galea, Daniel, Kunkel, Julian and Lawrence, Bryan N. (2023) TCDetect: a new method of detecting the presence of tropical cyclones using deep learning. Artificial Intelligence for the Earth Systems, 2 (3). ISSN 2769-7525 doi: https://doi.org/10.1175/aies-d-22-0045.1 (In Press)

Zaznov, Ilia ORCID: https://orcid.org/0000-0003-1229-5515, Kunkel, Julian, Dufour, Alfonso ORCID: https://orcid.org/0000-0003-0519-648X and Badii, Atta (2022) Predicting stock price changes based on the limit order book: a survey. Mathematics, 10 (8). 1234. ISSN 2227-7390 doi: https://doi.org/10.3390/math10081234

Kunkel, Julian, Filinger, Weronika, Meesters, Christian and Gerbes, Anja (2020) The HPC certification forum: toward a globally acknowledged HPC certification. Computing in Science and Engineering, 22 (4). ISSN 1521-9615 doi: https://doi.org/10.1109/MCSE.2020.2996073

Wang, Tiejun, Zhuang, Liu, Kunkel, Julian, Xiao, Shu and Zhao, Changming (2020) Parallelization and I/O performance optimization of a global nonhydrostatic dynamical core using MPI. Computers, Materials & Continua, 63 (3). pp. 1399-1413. ISSN 1546-2226 doi: https://doi.org/10.32604/cmc.2020.09701

Kunkel, Julian, Himstedt, Kai, Filinger, Weronika, Acquaviva, Jean-Thomas, Gerbes, Anja and Lafayette, Lev (2020) One year HPC certification forum in retrospective. Journal of Computational Science Education, 11 (1). pp. 29-35. ISSN 2153-4136 doi: https://doi.org/10.22369/issn.2153-4136/11/1/6

Kunkel, Julian, Jumah, Nabeeh, Novikova, Anastasiia, Ludwig, Thomas, Yashiro, Hisashi, Maruyama, Naoya, Wahib, Mohamed and Thuburn, John (2020) AIMES: advanced computation and I/O methods for earth-system simulations. Software for Exascale Computing - SPPEXA 2016-2019. Lectures Notes in Computational Science and Engineering (136). pp. 61-102. ISSN 1439-7358 doi: https://doi.org/10.1007/978-3-030-47956-5_5

Kunkel, Julian M. and Pedro, Luciana R. (2020) Potential of I/O aware workflows in climate and weather. Supercomputing Frontiers and Innovations, 7 (2). pp. 35-53. ISSN 2313-8734 doi: https://doi.org/10.14529/jsfi200203

Torres, Raul, Kunkel, Julian M., Dolz, Manuel F. and Ludwig, Thomas (2019) A similarity study of I/O traces via string kernels. The Journal of Supercomputing, 75 (12). pp. 7814-7826. ISSN 0920-8542 doi: https://doi.org/10.1007/s11227-018-2471-x

Kunkel, Julian M., Shoukourian, Hayk, Heidari, Reza and Wilde, Torsten (2019) Interference of billing and scheduling strategies for energy and cost savings in modern data centers. Sustainable Computing: Informatics and Systems, 23. pp. 49-66. ISSN 2210-5379 doi: https://doi.org/10.1016/j.suscom.2019.04.003

Kunkel, Julian, Himstedt, Kai, Hübbe, Nathanael, Stüben, Hinnerk, Schröder, Sandra, Kuhn, Michael, Riebisch, Matthias, Olbrich, Stephan, Ludwig, Thomas, Filinger, Weronika, Acquaviva, Jean-Thomas, Gerbes, Anja and Lafayette, Lev (2019) Towards an HPC certification program. Journal of Computational Science Education, 10 (1). pp. 88-89. ISSN 2153-4136 doi: https://doi.org/10.22369/issn.2153-4136/10/1/14

Kunkel, Julian and Dolz, Manuel F. (2018) Understanding hardware and software metrics with respect to power consumption. Sustainable Computing: Informatics and Systems, 17. pp. 43-54. ISSN 2210-5379 doi: https://doi.org/10.1016/j.suscom.2017.10.016

Lüttgau, Jakob, Kuhn, Michael, Duwe, Kira, Alforov, Yevhen, Betke, Eugen, Kunkel, Julian and Ludwig, Thomas (2018) Survey of storage systems for high-performance computing. Supercomputing Frontiers and Innovations, 5 (1). ISSN 2313-8734 doi: https://doi.org/10.14529/jsfi180103

Jumah, Nabeeh, Kunkel, Julian M., Zängl, Günther, Yashiro, Hisashi, Dubos, Thomas and Meurdesoif, Thomas (2017) GGDML: icosahedral models language extensions. Journal of Computer Science Technology Updates, 4 (1). pp. 1-10. ISSN 2410-2938 doi: https://doi.org/10.15379/2410-2938.2017.04.01.01

Kunkel, Julian Martin, Novikova, Anastasiia and Betke, Eugen (2017) Towards decoupling the selection of compression algorithms from quality constraints – an investigation of lossy compression efficiency. Supercomputing Frontiers and Innovations, 4 (4). pp. 17-33. ISSN 2313-8734 doi: https://doi.org/10.14529/jsfi170402

Dolz, Manuel F., Kunkel, Julian, Chasapis, Konstantinos and Catalán, Sandra (2016) An analytical methodology to derive power models based on hardware and software metrics. Computer Science - Research and Development, 31 (4). pp. 165-174. ISSN 1865-2034 doi: https://doi.org/10.1007/s00450-015-0298-8

Kunkel, Julian M. (2016) Analyzing data properties using statistical sampling: illustrated on scientific file formats. Supercomputing Frontiers and Innovations, 3 (3). pp. 34-39. ISSN 2409-6008 doi: https://doi.org/10.14529/jsfi160304

Schmidt, Jan F. and Kunkel, Julian M. (2016) Predicting I/O performance in HPC using artificial neural networks. Supercomputing Frontiers and Innovations, 3 (3). pp. 19-33. ISSN 2313-8734 doi: https://doi.org/10.14529/jsfi160303

Kuhn, Michael, Kunkel, Julian M. and Ludwig, Thomas (2016) Data compression for climate data. Supercomputing Frontiers and Innovations, 3 (1). pp. 75-94. ISSN 2313-8734 doi: https://doi.org/10.14529/jsfi160105

Kunkel, Julian M., Aguilera, Alvaro, Hübbe, Nathanael, Wiedemann, Marc and Zimmer, Michaela (2015) Monitoring energy consumption with SIOX. Computer Science - Research and Development, 30 (2). pp. 125-133. ISSN 1865-2034 doi: https://doi.org/10.1007/s00450-014-0271-y

Kunkel, Julian Martin, Kuhn, Michael and Ludwig, Thomas (2014) Exascale storage systems: an analytical study of expenses. Supercomputing Frontiers and Innovations, 1 (1). pp. 116-134. ISSN 2409-6008 doi: https://doi.org/10.14529/jsfi140106

Book or Report Section

Kunkel, Julian and Betke, Eugen (2017) An MPI-IO In-Memory driver for non-volatile pooled memory of the Kove XPD. In: Kunkel, Julian, Yokota, R., Taufer, M. and Shalf, J. (eds.) High Performance Computing. Lecture Notes in Computer Science, 10524 (10524). Springer, Cham, pp. 679-690. ISBN 9783319676296 doi: https://doi.org/10.1007/978-3-319-67630-2_48

Luettgau, Jakob and Kunkel, Julian (2017) Simulation of hierarchical storage systems for TCO and QoS. In: Kunkel, Julian, Yokota, R., Taufer, M. and Shalf, J. (eds.) High Performance Computing. Lecture Notes in Computer Science, 10524 (10524). Springer, Cham, pp. 132-144. ISBN 9783319676296 doi: https://doi.org/10.1007/978-3-319-67630-2_12

Kunkel, Julian, Novikova, A., Betke, E. and Schaare, A. (2017) Toward decoupling the selection of compression algorithms from quality constraints. In: Kunkel, Julian M., Yokota, Rio, Taufer, Michela and Shalf, John (eds.) High Performance Computing. Lecture Notes in Computer Science (10524). Springer, pp. 3-14. ISBN 9783319676296 doi: https://doi.org/10.1007/978-3-319-67630-2_1

Torres, Raul, Kunkel, Julian M., Dolz, Manuel F. and Ludwig, Thomas (2017) A novel string representation and kernel function for the comparison of I/O access patterns. In: Malyshkin, V. (ed.) Parallel Computing Technologies: 14th International Conference, PaCT 2017, Nizhny Novgorod, Russia, September 4-8, 2017, Proceedings. Lecture Notes in Computer Science, 10421 (10421 2017). Springer, Cham, pp. 500-512. ISBN 9783319629315 doi: https://doi.org/10.1007/978-3-319-62932-2_48

Kunkel, Julian M. (2016) Analyzing data properties using statistical sampling techniques – illustrated on scientific file formats and compression features. In: Taufer, M., Mohr, B. and Kunkel, J. (eds.) High Performance Computing. Lecture Notes in Computer Science, 9945. Springer, Cham, pp. 130-141. ISBN 9783319460796 doi: https://doi.org/10.1007/978-3-319-46079-6_10

Kunkel, Julian, Zimmer, Michaela and Betke, Eugen (2015) Predicting performance of non-contiguous I/O with machine learning. In: Kunkel, Julian M. and Ludwig, Thomas (eds.) High Performance Computing. Lecture Notes in Computer Science (9137). Springer, pp. 257-273. ISBN 9783319201184 doi: https://doi.org/10.1007/978-3-319-20119-1_19

Kunkel, Julian M., Zimmer, Michaela, Hübbe, Nathanael, Aguilera, Alvaro, Mickler, Holger, Wang, Xuan, Chut, Andriy, Bönisch, Thomas, Lüttgau, Jakob, Michel, Roman and Weging, Johann (2014) The SIOX architecture – coupling automatic monitoring and optimization of parallel I/O. In: Kunkel, Julian Martin, Ludwig, Thomas and Meuer, Hans Werner (eds.) Supercomputing. Lecture Notes in Computer Science (8488). Springer, pp. 245-260. ISBN 9783319075174 doi: https://doi.org/10.1007/978-3-319-07518-1_16

Conference or Workshop Item

Gadban, Frank, Kunkel, Julian and Ludwig, Thomas (2020) Investigating the overhead of the REST protocol to reveal the potential for using cloud services for HPC storage. In: HPC I/O in the Data Center Workshop, 21-25 June 2020. doi: https://doi.org/10.1007/978-3-030-59851-8_10 (High Performance Computing. ISC High Performance 2020. Lecture Notes in Computer Science)

Jumah, Nabeeh and Kunkel, Julian (2020) Optimizing memory bandwidth efficiency with user-preferred kernel merge. In: Euro-Par 2019: Parallel Processing Workshops, 26–30 Aug 2019, Göttingen, Germany, pp. 69-81. doi: https://doi.org/10.1007/978-3-030-48340-1_6

Betke, Eugen and Kunkel, Julian (2020) Semi-automatic assessment of I/O behavior by inspecting the individual client-node timelines— an explorative study on 10^6 jobs. In: ISC HPC, 21-25 Jun 2020, Frankfurt, Germany, pp. 166-184. doi: https://doi.org/10.1007/978-3-030-50743-5_9

Turner, Andrew, Sloan-Murphy, Dominic, Sivalingam, Karthee, Richardson, Harvey and Kunkel, Julian (2019) Analysis of parallel I/O use on the UK national supercomputing service, ARCHER using Cray's LASSi and EPCC SAFE. In: Memory Bound Computing. Cray User Group, 5-9 May 2019, Montréal, Canda.

Jumah, Nabeeh and Kunkel, Julian (2019) Automatic vectorization of stencil codes with the GGDML language extensions. In: Workshop on Programming Models for SIMD/Vector Processing, 2019/02/16, Washington DC, USA, pp. 1-7. doi: https://doi.org/10.1145/3303117.3306160

Betke, Eugen and Kunkel, Julian (2019) Footprinting parallel I/O – machine learning to classify application’s I/O behavior. In: HPC IODC workshop, pp. 214-226. doi: https://doi.org/10.1007/978-3-030-34356-9_18

Jum'ah, Nabeeh and Kunkel, Julian (2019) Performance portability of Earth system models with user-controlled GGDML code translation. In: Third International Workshop on Performance Portable Programming Models for Accelerators, 24-28 June 2018, Frankfurt, Germany, pp. 693-710. (ISBN 9783030024642)

Jumah, Nabeeh and Kunkel, Julian (2019) Scalable parallelization of stencils using MODA. In: P^3MA workshop, pp. 142-154. doi: https://doi.org/10.1007/978-3-030-34356-9_13

Kunkel, Julian and Betke, Eugen (2019) Tracking user-perceived I/O slowdown via probing. In: HPC-IODC workshop, Frankfurt, Germany, pp. 169-182. doi: https://doi.org/10.1007/978-3-030-34356-9_15

Betke, Eugen and Kunkel, Julian (2018) Benefit of DDN's IME-FUSE for I/O intensive HPC applications. In: Workshop on Performance and Scalability of Storage Systems, 24-28 June 2018, Frankfurt, Germany, pp. 131-144. (ISBN 9783030024642)

Torres, Raul, Kunkel, Julian M., Dolz, Manuel F. and Ludwig, Thomas (2018) Comparison of Clang Abstract Syntax Trees using string kernels. In: CADO 2018, 16-20 July, Orleans, France, pp. 106-113.

Lüttgau, Jakob and Kunkel, Julian (2018) Cost and performance modeling for Earth system data management and beyond. In: HPC I/O in the Data Center Workshop, 24-28 June 2018, Frankfurt, Germany, pp. 23-35. (ISBN 9783030024642)

Kunkel, Julian Martin, Betke, Eugen, Bryson, Matt, Carns, Philip, Francis, Rosemary, Frings, Wolfgang, Laifer, Roland and Mendez, Sandra (2018) Tools for analyzing parallel I/O. In: HPC I/O in the Data Center Workshop, 24-28 June 2018, Frankfurt, Germany, pp. 49-70. (ISBN 9783030024642)

Lüttgau, Jakob, Snyder, Shane, Carns, Philip, Wozniak, Justin M., Kunkel, Julian and Ludwig, Thomas (2018) Toward understanding I/O behavior in HPC workflows. In: PDSW-DISCS, 12 November 2018, Dallas, Texas, pp. 64-75.

Alforov, Yevhen, Novikova, Anastasiia, Kuhn, Michael, Kunkel, Julian and Ludwig, Thomas (2018) Towards green scientific data compression through high-level I/O interfaces. In: SBAC-PAD 2018, 24-27 September, Lyon, France, pp. 209-216.

Kunkel, Julian Martin and Markomanolis, George S. (2018) Understanding metadata latency with MDWorkbench. In: Workshop on Performance and Scalability of Storage Systems, 24-28 June 2018, Frankfurt, Germany, pp. 75-88. (ISBN 9783030024642)