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SEMI-LAGRANGIAN EXPONENTIAL INTEGRATION WITH APPLICATION TO THE ROTATING SHALLOW WATER EQUATIONS ∗

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arXiv 2019年

作者： Peixoto, Pedro S. Schreiber, Martin Instituto de Matemática e Estatística Universidade de São Paulo Brazil Chair of Computer Architecture and Parallel Systems Technical University of Munich Germany

In this paper we propose a novel way to integrate time-evolving partial differential equations that contain nonlinear advection and stiff linear operators, combining exponential integration techniques and semi-Lagrangian methods. The general formulation is built from the solution of an integration factor problem with respect to the problem written with a material derivative, so that the exponential integration scheme naturally incorporates the nonlinear advection. Semi-Lagrangian techniques are used to treat the dependence of the exponential integrator on the flow trajectories. The formulation is general, as many exponential integration techniques could be combined with different semi-Lagrangian methods. This formulation allows an accurate solution of the linear stiff operator, a property inherited by the exponential integration technique. It also provides a sufficiently accurate representation of the nonlinear advection, even with large time-step sizes, a property inherited by the semi-Lagrangian method. Aiming for application in weather and climate modeling, we discuss possible combinations of well established exponential integration techniques and state-of-the-art semi-Lagrangian methods used operationally in the application. We show experiments for the planar rotating shallow water equations. When compared to traditional exponential integration techniques, the experiments reveal that the coupling with semi-Lagrangian allows stabler integration with larger time-step sizes. From the application perspective, which already uses semi-Lagrangian methods, the exponential treatment could improve the solution of wave-dispersion when compared to semi-implicit schemes. Copyright © 2019, The Authors. All rights reserved.

关键词： Advection

An Optical Transceiver Reliability Study based on SFP Monitoring and OS-level Metric Data

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An Optical Transceiver Reliability Study based on SFP Monito...

IEEE/ACM International Symposium on Cluster Computing and the Grid (CCGRID)

作者： Paolo Notaro Qiao Yu Soroush Haeri Jorge Cardoso Michael Gerndt Huawei Technologies Duesseldorf GmbH Munich Germany Chair of Computer Architecture and Parallel Systems Technical University of Munich Germany Chair of Distributed and Operating Systems Technical University of Berlin Germany Department of Informatics Engineering/CISUC University of Coimbra Portugal

The increasing demand for cloud computing drives the expansion in scale of datacenters and their internal optical network, in a strive for increasing bandwidth, high reliability, and lower latency. Optical transceivers are essential elements of optical networks, whose reliability has not been well-studied compared to other hardware components. In this paper, we leverage high quantities of monitoring data from optical transceivers and OS-level metrics to provide statistical insights about the occurrence of optical transceiver failures. We estimate transceiver failure rates and normal operating ranges for monitored attributes, correlate early-observable patterns to known failure symptoms, and finally develop failure prediction models based on our analyses. Our results enable network administrators to deploy early-warning systems and enact predictive maintenance strategies, such as replacement or traffic re-routing, reducing the number of incidents and their associated costs.

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Calibration and Performance Evaluation of a Superconducting Quantum Processor in an HPC Center

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Calibration and Performance Evaluation of a Superconducting ...

ISC High Performance 2024 Research Paper Proceedings (39th International Conference)

作者： Xiaolong Deng Stefan Pogorzalek Florian Vigneau Ping Yang Martin Schulz Laura Schulz QCT Department Leibniz Supercomputing Centre Garching Germany Technology Department IQM Quantum Computers Munich Germany Chair of Computer Architecture and Parallel Systems Technical University of Munich Munich Germany

As quantum computers mature, they migrate from laboratory environments to HPC centers. This movement enables large-scale deployments, greater access to the technology, and deep integration into HPC in the form of quantum acceleration. In laboratory environments, specialists directly control the systems' environments and operations at any time with hands-on access, while HPC centers require remote and autonomous operations with minimal physical contact. The requirement for automation of the calibration process needed by all current quantum systems relies on maximizing their coherence times and fidelities and, with that, their best performance. It is, therefore, of great significance to establish a standardized and automatic calibration process alongside unified evaluation standards for quantum computing performance to evaluate the success of the calibration and operation of the system. In this work, we characterize our in-house superconducting quantum computer, establish an automatic calibration process, and evaluate its performance through quantum volume and an application-specific algorithm. We also analyze readout errors and improve the readout fidelity, leaning on error mitigation.

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QDMI - Quantum Device Management Interface: Hardware-Software Interface for the Munich Quantum Software Stack

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QDMI - Quantum Device Management Interface: Hardware-Softwar...

Quantum Computing and Engineering (QCE), IEEE International Conference on

作者： Robert Wille Ludwig Schmid Yannick Stade Jorge Echavarria Martin Schulz Laura Schulz Lukas Burgholzer Chair for Design Automation Technical University of Munich Munich Germany Software Competence Center Hagenberg GmbH Hagenberg Austria Leibniz Supercomputing Centre Garching Germany Chair of Computer Architecture and Parallel Systems Technical University of Munich Munich Germany

ISBN: (数字)9798331541378

ISBN: (纸本)9798331541385

Quantum computing is a promising technology that requires a sophisticated software stack to connect end users to the wide range of possible quantum backends. However, current software tools are usually hard-coded for single platforms and lack a dynamic interface that can automatically retrieve and adapt to changing physical characteristics and constraints of different platforms. With new hardware platforms frequently introduced and their performance changing on a daily basis, this constitutes a serious limitation. In this paper, we show-case a concept and a prototypical realization of an interface, called the Quantum Device Management Interface (QDMI), that addresses this problem by explicitly connecting the software and hardware developers, mediating between their competing interests. QDMI allows hardware platforms to provide their physical characteristics in a standardized way, and software tools to query that data to guide the compilation process accordingly. This enables software tools to automatically adapt to different platforms and to optimize the compilation process for the specific hardware constraints. QDMI is a central part of the Munich Quantum Software Stack (MQSS)-a sophisticated software stack to connect end users to the wide range of possible quantum backends. QDMI is publicly available as open source at https://***/Munich-Quantum-Software-Stack/QDMI.

关键词： Performance evaluation Quantum computing Full stack Hardware Software tools

A systematic mapping study in AIOps

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arXiv 2020年

作者： Notaro, Paolo Cardoso, Jorge Gerndt, Michael Chair of Computer Architecture and Parallel Systems Technical University of Munich Germany Ultra-scale AIOps Lab Huawei Munich Research Center Germany Department of Informatics Engineering/CISUC University of Coimbra Portugal

IT systems of today are becoming larger and more complex, rendering their human supervision more difficult. Artificial Intelligence for IT Operations (AIOps) has been proposed to tackle modern IT administration challenges thanks to AI and Big Data. However, past AIOps contributions are scattered, unorganized and missing a common terminology convention, which renders their discovery and comparison impractical. In this work, we conduct an in-depth mapping study to collect and organize the numerous scattered contributions to AIOps in a unique reference index. We create an AIOps taxonomy to build a foundation for future contributions and allow an efficient comparison of AIOps papers treating similar problems. We investigate temporal trends and classify AIOps contributions based on the choice of algorithms, data sources and the target components. Our results show a recent and growing interest towards AIOps, specifically to those contributions treating failure-related tasks (62%), such as anomaly detection and root cause analysis. © 2020, CC BY.

关键词： Artificial intelligence

parallel-in-Time Multi-Level Integration of the Shallow-Water Equations on the Rotating Sphere

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arXiv 2019年

作者： Hamon, François P. Schreiber, Martin Minion, Michael L. Center for Computational Sciences and Engineering Lawrence Berkeley National Laboratory Berkeley United States Chair of Computer Architecture and Parallel Systems Technical University of Munich Germany Department of Applied Mathematics Lawrence Berkeley National Laboratory Berkeley United States

The modeling of atmospheric processes in the context of weather and climate simulations is an important and computationally expensive challenge. The temporal integration of the underlying PDEs requires a very large number of time steps, even when the terms accounting for the propagation of fast atmospheric waves are treated implicitly. Therefore, the use of parallel-in-time integration schemes to reduce the time-to-solution is of increasing interest, particularly in the numerical weather forecasting field. We present a multi-level parallel-in-time integration method combining the parallel Full Approximation Scheme in Space and Time (PFASST) with a spatial discretization based on Spherical Harmonics (SH). The iterative algorithm computes multiple time steps concurrently by interweaving parallel high-order fine corrections and serial corrections performed on a coarsened problem. To do that, we design a methodology relying on the spectral basis of the SH to coarsen and interpolate the problem in space. The methods are evaluated on the shallow-water equations on the sphere using a set of tests commonly used in the atmospheric flow community. We assess the convergence of PFASST-SH upon refinement in time. We also investigate the impact of the coarsening strategy on the accuracy of the scheme, and specifically on its ability to capture the high-frequency modes accumulating in the solution. Finally, we study the computational cost of PFASST-SH to demonstrate that our scheme resolves the main features of the solution multiple times faster than the serial schemes. Copyright © 2019, The Authors. All rights reserved.

关键词： Harmonic analysis

An Accurate and Hardware-Efficient Dual Spike Detector for Implantable Neural Interfaces

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arXiv 2022年

作者： Guo, Xiaorang Shaeri, MohammadAli Shoaran, Mahsa Institute of Electrical and Micro Engineering Center for Neuroprosthetics EPFL Geneva1202 Switzerland Faculty of Electrical and Computer Engineering Technische Universität Dresden Dresden01069 Germany Chair of Computer Architecture and Parallel Systems Technische Universität München Garching85748 Germany

Spike detection plays a central role in neural data processing and brain-machine interfaces (BMIs). A challenge for future-generation implantable BMIs is to build a spike detector that features both low hardware cost and high performance. In this work, we propose a novel hardware-efficient and high-performance spike detector for implantable BMIs. The proposed design is based on a dual-detector architecture with adaptive threshold estimation. The dual-detector comprises two separate TEO-based detectors that distinguish a spike occurrence based on its discriminating features in both high and low noise scenarios. We evaluated the proposed spike detection algorithm on the Wave_Clus dataset. It achieved an average detection accuracy of 98.9%, and over 95% in high-noise scenarios, ensuring the reliability of our method. When realized in hardware with a sampling rate of 16kHz and 7-bits resolution, the detection accuracy is 97.4%. Designed in 65nm TSMC process, a 256-channel detector based on this architecture occupies only 682µm2/Channel and consumes 0.07µW/Channel, improving over the state-of-the-art spike detectors by 39.7% in power consumption and 78.8% in area, while maintaining a high accuracy. © 2022, CC BY.

关键词： Data handling

Leveraging Hybrid Classical-Quantum Methods for Efficient Load Rebalancing in HPC

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Leveraging Hybrid Classical-Quantum Methods for Efficient Lo...

High Performance Computing, Networking, Storage and Analysis, SC-W: Workshops of the International Conference for

作者： Justyna Zawalska Minh Chung Katarzyna Rycerz Laura Schulz Martin Schulz Dieter Kranzlmüller Institute of Computer Science AGH University of Krakow Krakow Poland Academic Computer Center CYFRONET AGH Krakow Poland Leibniz Supercomputing Centre (LRZ) Garching bei München Germany MNM-Team Ludwig-Maximilians-Universität München (LMU) Germany Chair for Computer Architecture and Parallel Systems Technical University of Munich (TUM) Germany

ISBN: (数字)9798350355543

ISBN: (纸本)9798350355550

Load imbalance is a challenge for parallel applications in High Performance Computing (HPC). It is caused by processes having different execution times or load values, leading to idle or wait times at synchronization points, where faster processes must wait for the slowest process to catch up. To mitigate this issue, applications can employ load balancing (LB) strategies, which migrate load between processes to even out load. This is often referred to as the Load Rebalancing Problem (LRP). While many approaches solving the LRP exist, they can only be heuristics and hence further optimization potential exists. In our work, we turn to a novel approach by using hybrid classical-quantum approaches and present two versions of the constrained quadratic model for solving the LRP; the two differ in how they balance the number of qubits required with the types of applied constraints. We compare the quantum-based methods with classical methods using heuristic algorithms Greedy, Karmarkar–Karp, and ProactLB. We evaluate our approaches using imbalance ratio and speedup as metrics, as well as the number of migrated tasks to indicate overhead caused by migrations. Our results show that the quantum-based methods outperform the classic methods. For example, we need only 1/4 of the number of migrated tasks in a realistic use case compared with classical methods, particularly Greedy and KK, to balance the load.

关键词： Measurement Upper bound NP-hard problem High performance computing Heuristic algorithms Qubit Load management Synchronization Optimization Load modeling