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ORCIDMartin Schulz 0001
Person information
- affiliation: Technical University Munich, Germany
- affiliation (former): Lawrence Livermore National Laboratory, Computer Science Group
Other persons with the same name
- Martin Schulz 0002 — German Graduate School of Management and Law
- Martin Schulz 0003 — RWTH Aachen, Department of Computer Science
- Martin Schulz 0004 — University of British Columbia, Faculty of Commerce & Business Administration
- Martin Schulz 0005 — science + computing ag (and 1 more)
- Martin Schulz 0006 — Infineon Technologies, Warstein, German
- Martin Schulz 0007 — Philipps-Universität Marburg, Faculty of Geography, Marburg, Germany
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2020 – today
- 2023
[c232]David Hildenbrand, Martin Schulz, Nadav Amit
:
Copy-on-Pin: The Missing Piece for Correct Copy-on-Write. ASPLOS (2) 2023: 176-191- [c231]Rui Song, Dai Liu, Dave Zhenyu Chen, Andreas Festag, Carsten Trinitis, Martin Schulz, Alois Knoll:
Federated Learning via Decentralized Dataset Distillation in Resource-Constrained Edge Environments. IJCNN 2023: 1-10 - [c230]Dominik Huber, Martin Schreiber, Martin Schulz:
A Case Study on PMIx-Usage for Dynamic Resource Management. ISC Workshops 2023: 42-55 - [c229]Isaías Comprés, Eishi Arima, Martin Schulz, Tiberiu Rotaru, Rui Machado:
Probabilistic Job History Conversion and Performance Model Generation for Malleable Scheduling Simulations. ISC Workshops 2023: 82-94 - [c228]Amir Raoofy, Roman Karlstetter, Martin Schreiber, Carsten Trinitis, Martin Schulz:
Overcoming Weak Scaling Challenges in Tree-Based Nearest Neighbor Time Series Mining. ISC 2023: 317-338 - [i14]Xiaorang Guo, Kun Qin, Martin Schulz:
HiSEP-Q: A Highly Scalable and Efficient Quantum Control Processor for Superconducting Qubits. CoRR abs/2308.16776 (2023) - [i13]Philipp Seitz, Amr Elsharkawy, Xiao-Ting Michelle To, Martin Schulz:
Toward a Unified Hybrid HPCQC Toolchain. CoRR abs/2309.01661 (2023) - [i12]Amr Elsharkawy, Xiao-Ting Michelle To, Philipp Seitz, Yanbin Chen, Yannick Stade, Manuel Geiger, Qunsheng Huang, Xiaorang Guo, Muhammad Arslan Ansari, Christian B. Mendl, Dieter Kranzlmüller, Martin Schulz:
Integration of Quantum Accelerators with High Performance Computing - A Review of Quantum Programming Tools. CoRR abs/2309.06167 (2023) - 2022
- [j43]Martin Schulz, Martin Ruefenacht, Dieter Kranzlmüller, Laura Brandon Schulz:
Accelerating HPC With Quantum Computing: It Is a Software Challenge Too. Comput. Sci. Eng. 24(4): 60-64 (2022) - [j42]Emmanuel Agullo, Mirco Altenbernd, Hartwig Anzt, Leonardo Bautista-Gomez, Tommaso Benacchio, Luca Bonaventura, Hans-Joachim Bungartz, Sanjay Chatterjee, Florina M. Ciorba, Nathan DeBardeleben, Daniel Drzisga, Sebastian Eibl, Christian Engelmann, Wilfried N. Gansterer, Luc Giraud, Dominik Göddeke, Marco Heisig, Fabienne Jézéquel, Nils Kohl, Xiaoye Sherry Li, Romain Lion, Miriam Mehl, Paul Mycek, Michael Obersteiner, Enrique S. Quintana-Ortí, Francesco Rizzi, Ulrich Rüde, Martin Schulz, Fred Fung, Robert Speck, Linda Stals, Keita Teranishi, Samuel Thibault, Dominik Thönnes, Andreas Wagner, Barbara I. Wohlmuth:
Resiliency in numerical algorithm design for extreme scale simulations. Int. J. High Perform. Comput. Appl. 36(2): 251-285 (2022) - [j41]Alessio Netti, Michael Ott, Carla Guillén, Daniele Tafani, Martin Schulz:
Operational Data Analytics in practice: Experiences from design to deployment in production HPC environments. Parallel Comput. 113: 102950 (2022) - [c227]Karlo Kraljic, Daniel Kerger, Martin Schulz:
Energy Efficient Frequency Scaling on GPUs in Heterogeneous HPC Systems. ARCS 2022: 3-16 - [c226]Issa Saba, Eishi Arima, Dai Liu, Martin Schulz:
Orchestrated Co-scheduling, Resource Partitioning, and Power Capping on CPU-GPU Heterogeneous Systems via Machine Learning. ARCS 2022: 51-67 - [c225]Roman Karlstetter, Robert Josef Widhopf-Fenk, Martin Schulz:
Querying Distributed Sensor Streams in the Edge-to-Cloud Continuum. EDGE 2022: 192-197 - [c224]Maron Schlemon, Martin Schulz, Rolf Scheiber:
Resource-Constrained Optimizations For Synthetic Aperture Radar On-Board Image Processing. HPEC 2022: 1-8 - [c223]Eishi Arima, Minjoon Kang, Issa Saba, Josef Weidendorfer, Carsten Trinitis, Martin Schulz:
Optimizing Hardware Resource Partitioning and Job Allocations on Modern GPUs under Power Caps. ICPP Workshops 2022: 9:1-9:10 - [c222]Yi Ju, Amir Raoofy, Dai Yang, Erwin Laure, Martin Schulz:
Exploiting Reduced Precision for GPU-based Time Series Mining. IPDPS 2022: 124-134 - [c221]Dominik Huber, Maximilian Streubel, Isaías Comprés, Martin Schulz, Martin Schreiber, Howard Pritchard:
Towards Dynamic Resource Management with MPI Sessions and PMIx. EuroMPI 2022: 57-67 - [c220]Jan Fecht, Martin Schreiber, Martin Schulz, Howard Pritchard, Daniel J. Holmes:
An Emulation Layer for Dynamic Resources with MPI Sessions. ISC Workshops 2022: 147-161 - [c219]Eishi Arima, Isaías Comprés, Martin Schulz:
On the Convergence of Malleability and the HPC PowerStack: Exploiting Dynamism in Over-Provisioned and Power-Constrained HPC Systems. ISC Workshops 2022: 206-217 - [e9]Martin Schulz, Carsten Trinitis, Nikela Papadopoulou, Thilo Pionteck:
Architecture of Computing Systems - 35th International Conference, ARCS 2022, Heilbronn, Germany, September 13-15, 2022, Proceedings. Lecture Notes in Computer Science 13642, Springer 2022, ISBN 978-3-031-21866-8 [contents] - [i11]Rui Song, Dai Liu, Dave Zhenyu Chen, Andreas Festag, Carsten Trinitis, Martin Schulz, Alois C. Knoll:
Federated Learning via Decentralized Dataset Distillation in Resource-Constrained Edge Environments. CoRR abs/2208.11311 (2022) - 2021
- [j40]Dominik Huber, Martin Schreiber, Martin Schulz:
Graph-based multi-core higher-order time integration of linear autonomous partial differential equations. J. Comput. Sci. 53: 101349 (2021) - [j39]Benjamin Zanger, Christian B. Mendl, Martin Schulz, Martin Schreiber:
Quantum Algorithms for Solving Ordinary Differential Equations via Classical Integration Methods. Quantum 5: 502 (2021) - [j38]Shinobu Miwa, Ignacio Laguna, Martin Schulz:
PredCom: A Predictive Approach to Collecting Approximated Communication Traces. IEEE Trans. Parallel Distributed Syst. 32(1): 45-58 (2021) - [j37]Martin Schulz, Kento Sato:
Guest Editorial: Special Issue on Computing Frontiers. J. Signal Process. Syst. 93(4): 389-390 (2021) - [c218]Roman Karlstetter, Amir Raoofy, Martin Radev, Carsten Trinitis, Jakob Hermann, Martin Schulz:
Living on the Edge: Efficient Handling of Large Scale Sensor Data. CCGRID 2021: 1-10 - [c217]Martin Schulz, Dieter Kranzlmüller, Laura Brandon Schulz, Carsten Trinitis, Josef Weidendorfer:
On the Inevitability of Integrated HPC Systems and How they will Change HPC System Operations. HEART 2021: 2:1-2:6 - [c216]Alessio Netti, Daniele Tafani, Michael Ott, Martin Schulz:
Correlation-wise Smoothing: Lightweight Knowledge Extraction for HPC Monitoring Data. IPDPS 2021: 2-12 - [c215]Martin Kronbichler, Niklas Fehn, Peter Munch, Maximilian Bergbauer, Karl-Robert Wichmann, Carolin Geitner, Momme Allalen, Martin Schulz, Wolfgang A. Wall:
A next-generation discontinuous galerkin fluid dynamics solver with application to high-resolution lung airflow simulations. SC 2021: 21 - [c214]David Hildenbrand, Martin Schulz:
virtio-mem: paravirtualized memory hot(un)plug. VEE 2021: 1-14 - [c213]Alexis Engelke, Dominik Okwieka, Martin Schulz:
Efficient LLVM-based dynamic binary translation. VEE 2021: 165-171 - [i10]Alessio Netti, Michael Ott, Carla Guillén, Daniele Tafani, Martin Schulz:
Operational Data Analytics in Practice: Experiences from Design to Deployment in Production HPC Environments. CoRR abs/2106.14423 (2021) - [i9]Philip H. Carns, Julian M. Kunkel, Kathryn M. Mohror, Martin Schulz:
Understanding I/O Behavior in Scientific and Data-Intensive Computing (Dagstuhl Seminar 21332). Dagstuhl Reports 11(7): 16-75 (2021) - 2020
- [j36]David E. Bernholdt, Swen Boehm, George Bosilca, Manjunath Gorentla Venkata, Ryan E. Grant, Thomas J. Naughton, Howard Pritchard, Martin Schulz, Geoffroy R. Vallée:
A survey of MPI usage in the US exascale computing project. Concurr. Comput. Pract. Exp. 32(3) (2020) - [j35]Sourav Chakraborty, Ignacio Laguna, Murali Emani, Kathryn M. Mohror, Dhabaleswar K. Panda, Martin Schulz, Hari Subramoni:
EReinit: Scalable and efficient fault-tolerance for bulk-synchronous MPI applications. Concurr. Comput. Pract. Exp. 32(3) (2020) - [j34]Bengisu Elis, Dai Yang, Olga Pearce, Kathryn M. Mohror, Martin Schulz:
QMPI: A next generation MPI profiling interface for modern HPC platforms. Parallel Comput. 96: 102635 (2020) - [j33]Shinobu Miwa, Masaya Ishihara, Hayato Yamaki, Hiroki Honda, Martin Schulz:
Footprint-Based DIMM Hotplug. IEEE Trans. Computers 69(2): 172-184 (2020) - [c212]Alessio Netti, Micha Müller, Carla Guillén, Michael Ott, Daniele Tafani, Gence Ozer, Martin Schulz:
DCDB Wintermute: Enabling Online and Holistic Operational Data Analytics on HPC Systems. HPDC 2020: 101-112 - [c211]Dominik Huber, Martin Schreiber, Dai Yang, Martin Schulz:
Cache-Aware Matrix Polynomials. ICCS (1) 2020: 132-146 - [c210]Ilkay Altintas, Dorian C. Arnold, Martin Schulz, Matthew G. F. Dosanjh, Ryan E. Grant, Taylor L. Groves:
Workshop 16: SNACS Scalable Networks for Advanced Computing Systems. IPDPS Workshops 2020: 868 - [c209]Amir Raoofy, Roman Karlstetter, Dai Yang, Carsten Trinitis, Martin Schulz:
Time Series Mining at Petascale Performance. ISC 2020: 104-123 - [c208]Gence Ozer, Alessio Netti, Daniele Tafani, Martin Schulz:
Characterizing HPC Performance Variation with Monitoring and Unsupervised Learning. ISC Workshops 2020: 280-292 - [c207]Eishi Arima, Toshihiro Hanawa, Carsten Trinitis, Martin Schulz:
Footprint-Aware Power Capping for Hybrid Memory Based Systems. ISC 2020: 347-369 - [c206]Eishi Arima, Martin Schulz:
Pattern-Aware Staging for Hybrid Memory Systems. ISC 2020: 474-495 - [c205]Alexis Engelke, Martin Schulz:
Instrew: leveraging LLVM for high performance dynamic binary instrumentation. VEE 2020: 172-184 - [i8]Alessio Netti, Daniele Tafani, Michael Ott, Martin Schulz:
Correlation-wise Smoothing: Lightweight Knowledge Extraction for HPC Monitoring Data. CoRR abs/2010.06186 (2020) - [i7]Emmanuel Agullo, Mirco Altenbernd, Hartwig Anzt, Leonardo Bautista-Gomez, Tommaso Benacchio, Luca Bonaventura, Hans-Joachim Bungartz, Sanjay Chatterjee, Florina M. Ciorba, Nathan DeBardeleben, Daniel Drzisga, Sebastian Eibl, Christian Engelmann, Wilfried N. Gansterer, Luc Giraud, Dominik Göddeke, Marco Heisig, Fabienne Jézéquel, Nils Kohl, Xiaoye Sherry Li, Romain Lion, Miriam Mehl, Paul Mycek, Michael Obersteiner, Enrique S. Quintana-Ortí, Francesco Rizzi, Ulrich Rüde, Martin Schulz, Fred Fung, Robert Speck, Linda Stals, Keita Teranishi, Samuel Thibault, Dominik Thönnes, Andreas Wagner, Barbara I. Wohlmuth:
Resiliency in Numerical Algorithm Design for Extreme Scale Simulations. CoRR abs/2010.13342 (2020)
2010 – 2019
- 2019
- [j32]Kento Sato, Ignacio Laguna, Gregory L. Lee, Martin Schulz, Christopher M. Chambreau, Simone Atzeni, Michael Bentley, Ganesh Gopalakrishnan, Zvonimir Rakamaric, Geof Sawaya, Joachim Protze, Dong H. Ahn:
Pruners. Int. J. High Perform. Comput. Appl. 33(5) (2019) - [j31]Marc-André Hermanns, Nathan T. Hjelm, Michael Knobloch, Kathryn M. Mohror, Martin Schulz:
The MPI_T events interface: An early evaluation and overview of the interface. Parallel Comput. 85: 119-130 (2019) - [c204]Alvaro Frank, Dai Yang, André Brinkmann, Martin Schulz, Tim Süß:
Reducing False Node Failure Predictions in HPC. HiPC 2019: 323-332 - [c203]Dimitrios Chasapis, Miquel Moretó, Martin Schulz, Barry Rountree, Mateo Valero, Marc Casas:
Power efficient job scheduling by predicting the impact of processor manufacturing variability. ICS 2019: 296-307 - [c202]Emilio Castillo, Nikhil Jain, Marc Casas, Miquel Moretó, Martin Schulz, Ramón Beivide, Mateo Valero, Abhinav Bhatele:
Optimizing computation-communication overlap in asynchronous task-based programs. ICS 2019: 380-391 - [c201]Giorgis Georgakoudis, Ignacio Laguna, Hans Vandierendonck, Dimitrios S. Nikolopoulos, Martin Schulz:
SAFIRE: Scalable and Accurate Fault Injection for Parallel Multithreaded Applications. IPDPS 2019: 890-899 - [c200]Dai Yang, Tilman Küstner, Rami G. Al Rihawi, Martin Schulz:
Exploring High Bandwidth Memory for PET Image Reconstruction. PARCO 2019: 219-228 - [c199]Emilio Castillo, Nikhil Jain, Marc Casas, Miquel Moretó, Martin Schulz, Ramón Beivide, Mateo Valero, Abhinav Bhatele:
Optimizing computation-communication overlap in asynchronous task-based programs: poster. PPoPP 2019: 415-416 - [c198]Bengisu Elis, Dai Yang, Martin Schulz:
QMPI: a next generation MPI profiling interface for modern HPC platforms. EuroMPI 2019: 4:1-4:10 - [c197]David Jauk, Dai Yang, Martin Schulz:
Predicting faults in high performance computing systems: an in-depth survey of the state-of-the-practice. SC 2019: 30:1-30:13 - [c196]Ian Karlin, Yoonho Park, Bronis R. de Supinski, Peng Wang, Bert Still, David Beckingsale, Robert Blake, Tong Chen, Guojing Cong, Carlos H. A. Costa, Johann Dahm, Giacomo Domeniconi, Thomas Epperly, Aaron Fisher, Sara Kokkila Schumacher, Steven H. Langer, Hai Le, Eun Kyung Lee, Naoya Maruyama, Xinyu Que, David F. Richards, Björn Sjögreen, Jonathan Wong, Carol S. Woodward, Ulrike Meier Yang, Xiaohua Zhang, Bob Anderson, David Appelhans, Levi Barnes, Peter D. Barnes Jr., Sorin Bastea, David Böhme, Jamie A. Bramwell, James M. Brase, José R. Brunheroto, Barry Chen, Charway R. Cooper, Tony Degroot, Robert D. Falgout, Todd Gamblin, David J. Gardner, James N. Glosli, John A. Gunnels, Max P. Katz, Tzanio V. Kolev, I-Feng W. Kuo, Matthew P. LeGendre, Ruipeng Li, Pei-Hung Lin, Shelby Lockhart, Kathleen McCandless, Claudia Misale, Jaime H. Moreno, Rob Neely, Jarom Nelson, Rao Nimmakayala, Kathryn M. O'Brien, Kevin O'Brien, Ramesh Pankajakshan, Roger Pearce, Slaven Peles, Phil Regier, Steven C. Rennich, Martin Schulz, Howard Scott, James C. Sexton, Kathleen Shoga, Shiv Sundram, Guillaume Thomas-Collignon, Brian Van Essen, Alexey Voronin, Bob Walkup, Lu Wang, Chris Ward, Hui-Fang Wen, Daniel A. White, Christopher Young, Cyril Zeller, Edward Zywicz:
Preparation and optimization of a diverse workload for a large-scale heterogeneous system. SC 2019: 32:1-32:17 - [c195]Alessio Netti, Micha Müller, Axel Auweter, Carla Guillén, Michael Ott, Daniele Tafani, Martin Schulz:
From facility to application sensor data: modular, continuous and holistic monitoring with DCDB. SC 2019: 64:1-64:27 - [e8]Francesca Palumbo, Michela Becchi, Martin Schulz, Kento Sato:
Proceedings of the 16th ACM International Conference on Computing Frontiers, CF 2019, Alghero, Italy, April 30 - May 2, 2019. ACM 2019, ISBN 978-1-4503-6685-4 [contents] - [e7]Abhinav Bhatele, David Böhme, Joshua A. Levine, Allen D. Malony, Martin Schulz:
Programming and Performance Visualization Tools - International Workshops, ESPT 2017 and VPA 2017, Denver, CO, USA, November 12 and 17, 2017, and ESPT 2018 and VPA 2018, Dallas, TX, USA, November 16 and 11, 2018, Revised Selected Papers. Lecture Notes in Computer Science 11027, Springer 2019, ISBN 978-3-030-17871-0 [contents] - [i6]Alessio Netti, Micha Mueller, Axel Auweter, Carla Guillén, Michael Ott, Daniele Tafani, Martin Schulz:
From Facility to Application Sensor Data: Modular, Continuous and Holistic Monitoring with DCDB. CoRR abs/1906.07509 (2019) - [i5]Alessio Netti, Micha Mueller, Carla Guillén, Michael Ott, Daniele Tafani, Gence Ozer, Martin Schulz:
DCDB Wintermute: Enabling Online and Holistic Operational Data Analytics on HPC Systems. CoRR abs/1910.06156 (2019) - 2018
- [j30]Alfredo Giménez, Todd Gamblin, Ilir Jusufi, Abhinav Bhatele, Martin Schulz, Peer-Timo Bremer, Bernd Hamann:
MemAxes: Visualization and Analytics for Characterizing Complex Memory Performance Behaviors. IEEE Trans. Vis. Comput. Graph. 24(7): 2180-2193 (2018) - [c194]Koji Inoue, Takuya Araki, Takumi Maruyama, Pritish Narayanan, Takashi Oshima, Martin Schulz:
Panel discussions: "Challenges to the scaling limits: How can we achieve sustainable power-performance improvements?". COOL CHIPS 2018: 1-2 - [c193]Thomas Becker, Dai Yang, Tilman Küstner, Martin Schulz:
Co-Scheduling in a Task-Based Programming Model. COSH@HiPEAC 2018: 9-14 - [c192]Joachim Protze, Martin Schulz, Dong H. Ahn, Matthias S. Müller:
Thread-local concurrency: a technique to handle data race detection at programming model abstraction. HPDC 2018: 144-155 - [c191]Kevin A. Brown, Nikhil Jain, Satoshi Matsuoka, Martin Schulz, Abhinav Bhatele:
Interference between I/O and MPI Traffic on Fat-tree Networks. ICPP 2018: 7:1-7:10 - [c190]Ryuichi Sakamoto, Tapasya Patki, Thang Cao, Masaaki Kondo, Koji Inoue, Masatsugu Ueda, Daniel A. Ellsworth, Barry Rountree, Martin Schulz:
Analyzing Resource Trade-offs in Hardware Overprovisioned Supercomputers. IPDPS 2018: 526-535 - [c189]Marc-André Hermanns, Nathan T. Hjelm, Michael Knobloch, Kathryn M. Mohror, Martin Schulz:
Enabling callback-driven runtime introspection via MPI_T. EuroMPI 2018: 8:1-8:10 - [c188]Luanzheng Guo, Dong Li, Ignacio Laguna, Martin Schulz:
FlipTracker: understanding natural error resilience in HPC applications. SC 2018: 8:1-8:14 - [i4]Luanzheng Guo, Dong Li, Ignacio Laguna, Martin Schulz:
FlipTracker: Understanding Natural Error Resilience in HPC Applications. CoRR abs/1809.01362 (2018) - 2017
- [c187]David Böhme, David Beckingsale, Martin Schulz:
Flexible Data Aggregation for Performance Profiling. CLUSTER 2017: 419-428 - [c186]Ayush Patwari, Ignacio Laguna, Martin Schulz, Saurabh Bagchi:
Understanding the Spatial Characteristics of DRAM Errors in HPC Clusters. FTXS@HPDC 2017: 17-22 - [c185]Kevin A. Brown, Tianqi Xu, Keita Iwabuchi, Kento Sato, Adam Moody, Kathryn M. Mohror, Nikhil Jain, Abhinav Bhatele, Martin Schulz, Roger A. Pearce, Maya B. Gokhale, Satoshi Matsuoka:
Accelerating Big Data Infrastructure and Applications (Ongoing Collaboration). ICDCS Workshops 2017: 343-347 - [c184]Matthias Maiterth, Torsten Wilde, David K. Lowenthal, Barry Rountree, Martin Schulz, Jonathan Eastep, Dieter Kranzlmiiller:
Power Aware High Performance Computing: Challenges and Opportunities for Application and System Developers - Survey & Tutorial. HPCS 2017: 3-10 - [c183]Ryuichi Sakamoto, Thang Cao, Masaaki Kondo, Koji Inoue, Masatsugu Ueda, Tapasya Patki, Daniel A. Ellsworth, Barry Rountree, Martin Schulz:
Production Hardware Overprovisioning: Real-World Performance Optimization Using an Extensible Power-Aware Resource Management Framework. IPDPS 2017: 957-966 - [c182]Joachim Protze, Jonas Hahnfeld, Dong H. Ahn, Martin Schulz, Matthias S. Müller:
OpenMP Tools Interface: Synchronization Information for Data Race Detection. IWOMP 2017: 249-265 - [c181]Kento Sato, Dong H. Ahn, Ignacio Laguna, Gregory L. Lee, Martin Schulz, Christopher M. Chambreau:
Noise Injection Techniques to Expose Subtle and Unintended Message Races. PPoPP 2017: 89-101 - [c180]Daniel A. Ellsworth, Tapasya Patki, Martin Schulz, Barry Rountree, Allen D. Malony:
Simulating Power Scheduling at Scale. E2SC@SC 2017: 2:1-2:8 - [c179]Giorgis Georgakoudis, Ignacio Laguna, Dimitrios S. Nikolopoulos, Martin Schulz:
REFINE: realistic fault injection via compiler-based instrumentation for accuracy, portability and speed. SC 2017: 29 - [c178]Alfredo Giménez, Todd Gamblin, Abhinav Bhatele, Chad Wood, Kathleen Shoga, Aniruddha Marathe, Peer-Timo Bremer, Bernd Hamann, Martin Schulz:
ScrubJay: deriving knowledge from the disarray of HPC performance data. SC 2017: 35 - [e6]Jens Knoop, Wolfgang Karl, Martin Schulz, Koji Inoue, Thilo Pionteck:
Architecture of Computing Systems - ARCS 2017 - 30th International Conference, Vienna, Austria, April 3-6, 2017, Proceedings. Lecture Notes in Computer Science 10172, Springer 2017, ISBN 978-3-319-54998-9 [contents] - 2016
- [j29]Tanzima Z. Islam, Kathryn M. Mohror, Martin Schulz:
Exploring the MPI tool information interface: features and capabilities. Int. J. High Perform. Comput. Appl. 30(2): 212-222 (2016) - [j28]Ignacio Laguna, David F. Richards, Todd Gamblin, Martin Schulz, Bronis R. de Supinski, Kathryn M. Mohror, Howard Pritchard:
Evaluating and extending user-level fault tolerance in MPI applications. Int. J. High Perform. Comput. Appl. 30(3): 305-319 (2016) - [j27]Katherine E. Isaacs, Todd Gamblin, Abhinav Bhatele, Martin Schulz, Bernd Hamann, Peer-Timo Bremer:
Ordering Traces Logically to Identify Lateness in Message Passing Programs. IEEE Trans. Parallel Distributed Syst. 27(3): 829-840 (2016) - [j26]Aniruddha Marathe, Rachel Harris, David K. Lowenthal, Bronis R. de Supinski, Barry Rountree, Martin Schulz:
Exploiting Redundancy and Application Scalability for Cost-Effective, Time-Constrained Execution of HPC Applications on Amazon EC2. IEEE Trans. Parallel Distributed Syst. 27(9): 2574-2588 (2016) - [c177]Ignacio Laguna, Martin Schulz, David F. Richards, Jon Calhoun, Luke N. Olson:
IPAS: intelligent protection against silent output corruption in scientific applications. CGO 2016: 227-238 - [c176]Alexandru Calotoiu, David Beckingsale, Christopher W. Earl, Torsten Hoefler, Ian Karlin, Martin Schulz, Felix Wolf:
Fast Multi-parameter Performance Modeling. CLUSTER 2016: 172-181 - [c175]Dimitrios Chasapis, Marc Casas, Miquel Moretó, Martin Schulz, Eduard Ayguadé, Jesús Labarta, Mateo Valero:
Runtime-Guided Mitigation of Manufacturing Variability in Power-Constrained Multi-Socket NUMA Nodes. ICS 2016: 5:1-5:12 - [c174]Simone Atzeni, Ganesh Gopalakrishnan, Zvonimir Rakamaric, Dong H. Ahn, Ignacio Laguna, Martin Schulz, Gregory L. Lee, Joachim Protze, Matthias S. Müller:
ARCHER: Effectively Spotting Data Races in Large OpenMP Applications. IPDPS 2016: 53-62 - [c173]Matthias Weber, Ronny Brendel, Tobias Hilbrich, Kathryn M. Mohror, Martin Schulz, Holger Brunst:
Structural Clustering: A New Approach to Support Performance Analysis at Scale. IPDPS 2016: 484-493 - [c172]Lee Savoie, David K. Lowenthal, Bronis R. de Supinski, Tanzima Z. Islam, Kathryn M. Mohror, Barry Rountree, Martin Schulz:
I/O Aware Power Shifting. IPDPS 2016: 740-749 - [c171]Olga Pearce, Todd Gamblin, Bronis R. de Supinski, Martin Schulz, Nancy M. Amato:
MPMD Framework for Offloading Load Balance Computation. IPDPS 2016: 943-952 - [c170]Daniel A. Ellsworth, Tapasya Patki, Swann Perarnau, Sangmin Seo, Abdelhalim Amer, Judicael A. Zounmevo, Rinku Gupta, Kazutomo Yoshii, Henry Hoffmann, Allen D. Malony, Martin Schulz, Peter H. Beckman:
Systemwide Power Management with Argo. IPDPS Workshops 2016: 1118-1121 - [c169]Matthias Maiterth, Martin Schulz, Dieter Kranzlmüller, Barry Rountree:
Power Balancing in an Emulated Exascale Environment. IPDPS Workshops 2016: 1142-1149 - [c168]Joachim Protze, Dong H. Ahn, Ignacio Laguna, Martin Schulz, Matthias S. Müller:
Testing Infrastructure for OpenMP Debugging Interface Implementations. IWOMP 2016: 205-216 - [c167]Daniel J. Holmes, Kathryn M. Mohror, Ryan E. Grant, Anthony Skjellum, Martin Schulz, Wesley Bland, Jeffrey M. Squyres:
MPI Sessions: Leveraging Runtime Infrastructure to Increase Scalability of Applications at Exascale. EuroMPI 2016: 121-129 - [c166]Søren Rasmussen, Martin Schulz, Kathryn M. Mohror:
Allowing MPI tools builders to forget about Fortran. EuroMPI 2016: 208-211 - [c165]Tapasya Patki, David K. Lowenthal, Barry L. Rountree, Martin Schulz, Bronis R. de Supinski:
Economic Viability of Hardware Overprovisioning in Power-Constrained High Performance Computing. E2SC@SC 2016: 8-15 - [c164]Hormozd Gahvari, Veselin A. Dobrev, Robert D. Falgout, Tzanio V. Kolev, Jacob B. Schroder, Martin Schulz, Ulrike Meier Yang:
A Performance Model for Allocating the Parallelism in a Multigrid-in-Time Solver. PMBS@SC 2016: 22-31 - [c163]Daniel A. Ellsworth, Tapasya Patki, Martin Schulz, Barry Rountree, Allen D. Malony:
A Unified Platform for Exploring Power Management Strategies. E2SC@SC 2016: 24-30 - [c162]Huu Tan Nguyen, Lai Wei, Abhinav Bhatele, Todd Gamblin, David Böhme, Martin Schulz, Kwan-Liu Ma, Peer-Timo Bremer:
VIPACT: A Visualization Interface for Analyzing Calling Context Trees. VPA@SC 2016: 25-28 - [c161]Sandra Wienke, Julian Miller, Martin Schulz, Matthias S. Müller:
Development effort estimation in HPC. SC 2016: 107-118 - [c160]Ignacio Laguna, Martin Schulz:
Pinpointing scale-dependent integer overflow bugs in large-scale parallel applications. SC 2016: 216-227 - [c159]Tanzima Z. Islam, Jayaraman J. Thiagarajan, Abhinav Bhatele, Martin Schulz, Todd Gamblin:
A machine learning framework for performance coverage analysis of proxy applications. SC 2016: 538-549 - [c158]David Böhme, Todd Gamblin, David Beckingsale, Peer-Timo Bremer, Alfredo Giménez, Matthew P. LeGendre, Olga Pearce, Martin Schulz:
Caliper: performance introspection for HPC software stacks. SC 2016: 550-560 - 2015
- [j25]Ignacio Laguna, Dong H. Ahn, Bronis R. de Supinski, Todd Gamblin, Gregory L. Lee, Martin Schulz, Saurabh Bagchi, Milind Kulkarni, Bowen Zhou, Zhezhe Chen, Feng Qin:
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