2024

Zaznov, I., Kunkel, J. M., Badii, A. and Dufour, A. ORCID: https://orcid.org/0000-0003-0519-648X (2024) The intraday dynamics predictor: a TrioFlow Fusion of Convolutional Layers and Gated Recurrent Units for high-frequency price movement forecasting. Applied Sciences, 14 (7). 2984. ISSN 2076-3417 doi: https://doi.org/10.3390/app14072984

2023

Galea, D., Kunkel, J. and Lawrence, B. N. ORCID: https://orcid.org/0000-0001-9262-7860 (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

2022

Zaznov, I. ORCID: https://orcid.org/0000-0003-1229-5515, Kunkel, J., Dufour, A. ORCID: https://orcid.org/0000-0003-0519-648X and Badii, A. (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

2020

Kunkel, J., Filinger, W., Meesters, C. and Gerbes, A. (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, T., Zhuang, L., Kunkel, J., Xiao, S. and Zhao, C. (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, J., Himstedt, K., Filinger, W., Acquaviva, J.-T., Gerbes, A. and Lafayette, L. (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, J., Jumah, N., Novikova, A., Ludwig, T., Yashiro, H., Maruyama, N., Wahib, M. and Thuburn, J. (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

Gadban, F., Kunkel, J. and Ludwig, T. (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, N. and Kunkel, J. (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

Kunkel, J. M. and Pedro, L. 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

Betke, E. and Kunkel, J. (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

2019

Torres, R., Kunkel, J. M., Dolz, M. F. and Ludwig, T. (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, J. M., Shoukourian, H., Heidari, R. and Wilde, T. (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, J., Himstedt, K., Hübbe, N., Stüben, H., Schröder, S., Kuhn, M., Riebisch, M., Olbrich, S., Ludwig, T., Filinger, W., Acquaviva, J.-T., Gerbes, A. and Lafayette, L. (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

Turner, A., Sloan-Murphy, D., Sivalingam, K., Richardson, H. and Kunkel, J. (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, N. and Kunkel, J. (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, E. and Kunkel, J. (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, N. and Kunkel, J. (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, N. and Kunkel, J. (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, J. and Betke, E. (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

2018

Kunkel, J. and Dolz, M. 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

Betke, E. and Kunkel, J. (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, R., Kunkel, J. M., Dolz, M. F. and Ludwig, T. (2018) Comparison of Clang Abstract Syntax Trees using string kernels. In: CADO 2018, 16-20 July, Orleans, France, pp. 106-113.

Lüttgau, J. and Kunkel, J. (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)

Lüttgau, J., Kuhn, M., Duwe, K., Alforov, Y., Betke, E., Kunkel, J. and Ludwig, T. (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

Kunkel, J. M., Betke, E., Bryson, M., Carns, P., Francis, R., Frings, W., Laifer, R. and Mendez, S. (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, J., Snyder, S., Carns, P., Wozniak, J. M., Kunkel, J. and Ludwig, T. (2018) Toward understanding I/O behavior in HPC workflows. In: PDSW-DISCS, 12 November 2018, Dallas, Texas, pp. 64-75.

Alforov, Y., Novikova, A., Kuhn, M., Kunkel, J. and Ludwig, T. (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, J. M. and Markomanolis, G. 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)

2017

Jumah, N., Kunkel, J. M., Zängl, G., Yashiro, H., Dubos, T. and Meurdesoif, T. (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, J. and Betke, E. (2017) An MPI-IO In-Memory driver for non-volatile pooled memory of the Kove XPD. In: Kunkel, J., 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, J. and Kunkel, J. (2017) Simulation of hierarchical storage systems for TCO and QoS. In: Kunkel, J., 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, J., Novikova, A., Betke, E. and Schaare, A. (2017) Toward decoupling the selection of compression algorithms from quality constraints. In: Kunkel, J. M., Yokota, R., Taufer, M. and Shalf, J. (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

Kunkel, J. M., Novikova, A. and Betke, E. (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

Torres, R., Kunkel, J. M., Dolz, M. F. and Ludwig, T. (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

2016

Dolz, M. F., Kunkel, J., Chasapis, K. and Catalán, S. (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, J. 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, J. F. and Kunkel, J. 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

Kunkel, J. 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

Kuhn, M., Kunkel, J. M. and Ludwig, T. (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

2015

Kunkel, J., Zimmer, M. and Betke, E. (2015) Predicting performance of non-contiguous I/O with machine learning. In: Kunkel, J. M. and Ludwig, T. (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, J. M., Aguilera, A., Hübbe, N., Wiedemann, M. and Zimmer, M. (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

2014

Kunkel, J. M., Kuhn, M. and Ludwig, T. (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

Kunkel, J. M., Zimmer, M., Hübbe, N., Aguilera, A., Mickler, H., Wang, X., Chut, A., Bönisch, T., Lüttgau, J., Michel, R. and Weging, J. (2014) The SIOX architecture – coupling automatic monitoring and optimization of parallel I/O. In: Kunkel, J. M., Ludwig, T. and Meuer, H. W. (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