TY - JOUR A1 - Wende, Florian A1 - Marsman, Martijn A1 - Kim, Jeongnim A1 - Vasilev, Fedor A1 - Zhao, Zhengji A1 - Steinke, Thomas T1 - OpenMP in VASP: Threading and SIMD JF - International Journal of Quantum Chemistry N2 - The Vienna Ab initio Simulation Package (VASP) is a widely used electronic structure code that originally exploits process-level parallelism through the Message Passing Interface (MPI) for work distribution within and across nodes. Architectural changes of modern parallel processors urge programmers to address thread- and data-level parallelism as well to benefit most from the available compute resources within a node. We describe for VASP how to approach for an MPI + OpenMP parallelization including data-level parallelism through OpenMP SIMD constructs together with a generic high-level vector coding scheme. We can demonstrate an improved scalability of VASP and more than 20% gain over the MPI-only version, as well as a 2x increased performance of collective operations using the multiple-endpoint MPI feature. The high-level vector coding scheme applied to VASP's general gradient approximation routine gives up 9x performance gain on AVX512 platforms with the Intel compiler. Y1 - 2018 U6 - https://doi.org/10.1002/qua.25851 IS - Emerging Architectures in Computational Chemistry SP - e25851 PB - Wiley Online Library ER - TY - JOUR A1 - Salem, Farouk A1 - Schintke, Florian A1 - Schütt, Thorsten A1 - Reinefeld, Alexander T1 - Data-flow scheduling for a scalable FLESnet JF - CBM Progress Report 2017 Y1 - 2018 SN - 978-3-9815227-5-4 U6 - https://doi.org/10.15120/GSI-2018-00485 SP - 130 EP - 131 ER - TY - CHAP A1 - Gholami, Masoud A1 - Schintke, Florian A1 - Schütt, Thorsten T1 - Checkpoint Scheduling for Shared Usage of Burst-Buffers in Supercomputers T2 - Proceedings of the 47th International Conference on Parallel Processing Companion; SRMPDS 2018: The 14th International Workshop on Scheduling and Resource Management for Parallel and Distributed Systems N2 - User-defined and system-level checkpointing have contrary properties. While user-defined checkpoints are smaller and simpler to recover, system-level checkpointing better knows the global system's state and parameters like the expected mean time to failure (MTTF) per node. Both approaches lead to non-optimal checkpoint time, intervals, sizes, or I/O bandwidth when concurrent checkpoints conflict and compete for it. We combine user-defined and system-level checkpointing to exploit the benefits and avoid the drawbacks of each other. Thus, applications frequently offer to create checkpoints. The system accepts such offers according to the current status and implied costs to recalculate from the last checkpoint or denies them, i.e., immediately lets continue the application without checkpoint creation. To support this approach, we develop economic models for multi-application checkpointing on shared I/O resources that are dedicated for checkpointing (e.g. burst-buffers) by defining an appropriate goal function and solving a global optimization problem. Using our models, the checkpoints of applications on a supercomputer are scheduled to effectively use the available I/O bandwidth and minimize the failure overhead (checkpoint creations plus recalculations). Our simulations show an overall reduction in failure overhead of all nodes of up to 30% for a typical supercomputer workload (HLRN). We can also derive the most cost effective burst-buffer bandwidth for a given node's MTTF and application workload. Y1 - 2018 U6 - https://doi.org/10.1145/3229710.3229755 SP - 44:1 EP - 44:10 ER - TY - GEN A1 - Gholami, Masoud A1 - Schintke, Florian A1 - Schütt, Thorsten A1 - Reinefeld, Alexander T1 - Modeling Checkpoint Schedules for Concurrent HPC Applications T2 - CoSaS 2018 International Symposium on Computational Science at Scale Y1 - 2018 ER - TY - CHAP A1 - Schmidtke, Robert A1 - Schintke, Florian A1 - Schütt, Thorsten T1 - From Application to Disk: Tracing I/O Through the Big Data Stack T2 - High Performance Computing ISC High Performance 2018 International Workshops, Frankfurt/Main, Germany, June 24 - 28, 2018, Revised Selected Papers, Workshop on Performance and Scalability of Storage Systems (WOPSSS) N2 - Typical applications in data science consume, process and produce large amounts of data, making disk I/O one of the dominating — and thus worthwhile optimizing — factors of their overall performance. Distributed processing frameworks, such as Hadoop, Flink and Spark, hide a lot of complexity from the programmer when they parallelize these applications across a compute cluster. This exacerbates reasoning about I/O of both the application and the framework, through the distributed file system, such as HDFS, down to the local file systems. We present SFS (Statistics File System), a modular framework to trace each I/O request issued by the application and any JVM-based big data framework involved, mapping these requests to actual disk I/O. This allows detection of inefficient I/O patterns, both by the applications and the underlying frameworks, and builds the basis for improving I/O scheduling in the big data software stack. Y1 - 2018 U6 - https://doi.org/10.1007/978-3-030-02465-9_6 SP - 89 EP - 102 ER - TY - THES A1 - Steininger, Lennart T1 - Atomarer Datenzugriff auf verteilten persistenten Arbeitsspeicher N2 - Nicht flüchtiger Arbeitsspeicher bzw. Non-volatile Random Access Memory oder auch Persistent Memory befindet sich im frühen Markteintritt. Diese Art von Speicher nimmt eine Stellung zwischen bisherigem flüchtigen Arbeitsspeicher (Memory) und bisherigem Permanentspeicher (Storage) ein. Im Zusammenspiel mit verteilten Algorithmen und Systemen sowie dem Zugriff auf entfernte Speicherbereiche durch die Netzwerkinterfaces per Remote Direct Memory Access sind die Konzepte zum Umgang mit Durability und allen einhergehenden Herausforderungen bisher nicht ausgereift. Diese Arbeit untersucht, wie sich in Rechnernetzen mit persistentem Speicher und möglichst passivem Zugriff auf entfernten Speicher performante verteilte Systeme implementieren lassen. Es werden Anforderungen und Voraussetzungen eines solchen Systems bestimmt und daraufhin Lösungsmöglichkeiten aufgezeigt, wie sich diese Anforderungen mit Nutzung nicht flüchtigen Arbeitsspeichers umsetzen lassen. Die notwendigen Eigenschaften der Hard- und Software sowie der eingesetzten Netzwerkprotokolle werden beschrieben. Y1 - 2018 ER - TY - JOUR A1 - Seibert, Felix A1 - Peters, Mathias A1 - Schintke, Florian T1 - Improving I/O Performance Through Colocating Interrelated Input Data and Near-Optimal Load Balancing JF - Proceedings of the IPDPSW; Fourth IEEE International Workshop on High-Performance Big Data, Deep Learning, and Cloud Computing (HPBDC) N2 - Most distributed file systems assign new files to storage servers randomly. While working well in some situations, this does not help to optimize the input performance for most MapReduce computations’ data access patterns. In this work, we consider an access pattern where input files are partitioned into groups of heterogeneous size. Each group is accessed by exactly one process. We design and implement a data placement strategy that places these file groups together on the same storage server. This colocation approach is combined with near-optimal storage load balancing. To do so, we use a classical scheduling approximation algorithm to solve the NP hard group assignment problem. We argue that local processing is not only beneficial because of reduced network traffic, but especially because it imposes an even resource schedule. Our experiments, based on the parallel processing of remote sensing images, reveal an enormous reduction of network traffic and up to 39 % faster input read times. Further, simulations show that our approximate assignments limit storage server imbalances to less than 5 % above the theoretical minimum, in contrast to more than 85 % with random assignment. Y1 - 2018 U6 - https://doi.org/10.1109/IPDPSW.2018.00081 N1 - Best Paper Award VL - 2018 SP - 448 EP - 457 ER - TY - CHAP A1 - Noack, Matthias A1 - Reinefeld, Alexander A1 - Kramer, Tobias A1 - Steinke, Thomas T1 - DM-HEOM: A Portable and Scalable Solver-Framework for the Hierarchical Equations of Motion T2 - 2018 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), 19th IEEE Int. Workshop on Parallel and Distributed Scientific and Engineering Computing (PDSEC 2018) N2 - Computing the Hierarchical Equations of Motion (HEOM) is by itself a challenging problem, and so is writing portable production code that runs efficiently on a variety of architectures while scaling from PCs to supercomputers. We combined both challenges to push the boundaries of simulating quantum systems, and to evaluate and improve methodologies for scientific software engineering. Our contributions are threefold: We present the first distributed memory implementation of the HEOM method (DM-HEOM), we describe an interdisciplinary development workflow, and we provide guidelines and experiences for designing distributed, performance-portable HPC applications with MPI-3, OpenCL and other state-of-the-art programming models. We evaluated the resulting code on multi- and many-core CPUs as well as GPUs, and demonstrate scalability on a Cray XC40 supercomputer for the PS I molecular light harvesting complex. Y1 - 2018 SN - 978-1-5386-5555-9 U6 - https://doi.org/10.1109/IPDPSW.2018.00149 N1 - Best Paper Award SP - 947 EP - 956 ER - TY - JOUR A1 - Kramer, Tobias A1 - Noack, Matthias A1 - Reinefeld, Alexander A1 - Rodríguez, Mirta A1 - Zelinskyi, Yaroslav T1 - Efficient calculation of open quantum system dynamics and time-resolved spectroscopy with Distributed Memory HEOM (DM-HEOM) JF - Journal of Computational Chemistry N2 - Time- and frequency resolved optical signals provide insights into the properties of light harvesting molecular complexes, including excitation energies, dipole strengths and orientations, as well as in the exciton energy flow through the complex. The hierarchical equations of motion (HEOM) provide a unifying theory, which allows one to study the combined effects of system-environment dissipation and non-Markovian memory without making restrictive assumptions about weak or strong couplings or separability of vibrational and electronic degrees of freedom. With increasing system size the exact solution of the open quantum system dynamics requires memory and compute resources beyond a single compute node. To overcome this barrier, we developed a scalable variant of HEOM. Our distributed memory HEOM, DM-HEOM, is a universal tool for open quantum system dynamics. It is used to accurately compute all experimentally accessible time- and frequency resolved processes in light harvesting molecular complexes with arbitrary system-environment couplings for a wide range of temperatures and complex sizes. Y1 - 2018 U6 - https://doi.org/doi:10.1002/jcc.25354 VL - 39 IS - 22 SP - 1779 EP - 1794 PB - Wiley Periodicals, Inc. ER - TY - JOUR A1 - Kramer, Tobias A1 - Noack, Matthias A1 - Reimers, Jeffrey R. A1 - Reinefeld, Alexander A1 - Rodríguez, Mirta A1 - Yin, Shiwei T1 - Energy flow in the Photosystem I supercomplex: comparison of approximative theories with DM-HEOM JF - Chemical Physics N2 - We analyze the exciton dynamics in PhotosystemI from Thermosynechococcus elongatus using the distributed memory implementation of the hierarchical equation of motion (DM-HEOM) for the 96 Chlorophylls in the monomeric unit. The exciton-system parameters are taken from a first principles calculation. A comparison of the exact results with Foerster rates and Markovian approximations allows one to validate the exciton transfer times within the complex and to identify deviations from approximative theories. We show the optical absorption, linear, and circular dichroism spectra obtained with DM-HEOM and compare them to experimental results. Y1 - 2018 U6 - https://doi.org/10.1016/j.chemphys.2018.05.028 VL - 515 SP - 262 EP - 271 PB - Elsevier B.V. ER -