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IEEE International Conference on Big Data

作者： Mohamed Elzohairy Mohak Chadha Anshul Jindal Andreas Grafberger Jianfeng Gu Michael Gerndt Osama Abboud Chair of Computer Architecture and Parallel Systems Technische Universität München Garching (near Munich) Germany Huawei Technologies Munich Germany

ISBN: (纸本)9781665480468

Federated Learning (FL) is a machine learning paradigm that enables the training of a shared global model across distributed clients while keeping the training data local. While most prior work on designing systems for FL has focused on using stateful always running components, recent work has shown that components in an FL system can greatly benefit from the usage of serverless computing and Function-as-a-Service technologies. To this end, distributed training of models with severless FL systems can be more resource-efficient and cheaper than conventional FL systems. However, serverless FL systems still suffer from the presence of stragglers, i.e., slow clients due to their resource and statistical heterogeneity. While several strategies have been proposed for mitigating stragglers in FL, most methodologies do not account for the particular characteristics of serverless environments, i.e., cold-starts, performance variations, and the ephemeral stateless nature of the function instances. Towards this, we propose FedLesScan, a novel clustering-based semi-asynchronous training strategy, specifically tailored for serverless F L. FedLesScan dynamically adapts to the behavior of clients and minimizes the effect of stragglers on the overall system. We implement our strategy by extending an open-source serverless FL system called FedLess. Moreover, we comprehensively evaluate our strategy using the 2 nd generation Google Cloud Functions with four datasets and varying percentages of stragglers. Results from our experiments show that compared to other approaches FedLesScan reduces training time and cost by an average of 8% and 20% respectively while utilizing clients better with an average increase in the effective update ratio of 17.75%.

关键词： Training Costs Federated learning Computational modeling Training data Serverless computing Big Data

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Economy-based Greedy Bidding for Resources for CAE Workflows in Hybrid Cloud Infrastructure

Economy-based Greedy Bidding for Resources for CAE Workflows...

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IEEE International Conference on e-Science and Grid Computing

作者： Srishti Dasgupta Tähvend Uustalu Michael Gerndt Babak Gholami Chair of Computer Architecture and Parallel Systems Technische Universität München Garching (near Munich) Germany BMW Group Munich Germany

ISBN: (数字)9798350365610

ISBN: (纸本)9798350365627

The advent of generative design in the automotive sector, characterised by the automatic and iterative exploration of expansive solution spaces to discover optimal design configurations, has significantly increased the demand for computational resources to run intensive computer-aided engineering (CAE) simulations within constrained time frames. The inherent limitations of static high-performance computing (HPC) clusters have necessitated the adoption of cloud resources due to their flexible and elastic nature, thereby enhancing the capacity to accommodate the computational demands of these iterative workflows. These workflows, represented as Directed Acyclic Graphs (DAGs), involve the serial and parallel execution of tasks, which can dynamically share resources with other workflows during idle periods. In this paper, we propose an economy-based approach to exploit the gaps generated by these idle periods through a bidding system, thereby enabling more efficient resource utilisation and reducing the average wait time, makespan, cost and deadline miss by more than 40%, 6%, 13% and 45%respectively against certain infrastructures and baselines. Furthermore, we explore the potential for generating revenue by renting out idle resources in a hybrid cloud setup. This approach not only aims to optimise the use of computational resources but also seeks to provide cost-effective solutions to meet the escalating demands of generative design in the automotive sector.

关键词： Directed acyclic graph Costs High performance computing Computational modeling Hybrid power systems Iterative methods Time factors

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Online memory leak detection in the cloud-based infrastructures

arXiv

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arXiv 2021年

作者： Jindal, Anshul Staab, Paul Cardoso, Jorge Gerndt, Michael Podolskiy, Vladimir Chair of Computer Architecture and Parallel Systems Technical University of Munich Garching Germany Huawei Munich Research Center Huawei Technologies Munich Germany

A memory leak in an application deployed on the cloud can affect the availability and reliability of the application. Therefore, to identify and ultimately resolve it quickly is highly important. However, in the production environment running on the cloud, memory leak detection is a challenge without the knowledge of the application or its internal object allocation details. This paper addresses this challenge of online detection of memory leaks in cloud-based infrastructure without having any internal application knowledge by introducing a novel machine learning based algorithm Precog. This algorithm solely uses one metric i.e the system’s memory utilization on which the application is deployed for the detection of a memory leak. The developed algorithm’s accuracy was tested on 60 virtual machines manually labeled memory utilization data provided by our industry partner Huawei Munich Research Center and it was found that the proposed algorithm achieves the accuracy score of 85% with less than half a second prediction time per virtual machine. © 2021, CC BY.

关键词： Machine learning

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Windsurfing with APPA: Automating Computational Fluid Dynamics Simulations of Wind Flow using Cloud Computing

Windsurfing with APPA: Automating Computational Fluid Dynami...

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Euromicro Conference on parallel, Distributed and Network-Based Processing

作者： Anshul Jindal Benedikt Strahm Vladimir Podolskiy Michael Gerndt Chair of Computer Architecture and Parallel Systems Technical University of Munich Garching (near Munich) Germany Independent Researcher Garching (near Munich) Germany

ISBN: (数字)9781728165820

ISBN: (纸本)9781728165837

Computational fluid dynamics (CFD) can serve as a complementary approach to conventional wind tunnel testing to assess the wind flow around tall buildings. Being a clear High Performance Computing (HPC) task, CFD simulations conventionally run on supercomputers and compute clusters using specialized software such as OpenFOAM. The limited availability and high maintenance costs of supercomputers and clusters force small and medium companies to search for the cost-efficient infrastructure to conduct their simulations with the appropriate performance. The on-demand offer of compute capacity by cloud service providers are well suited this task. However, engineers and researchers require extensive expertise and experience in working with cloud computing in order to benefit from running CFD simulations on a *** contribution of the paper to the outlined problem is two-fold: 1) a unique Automated parallel Processing Application (APPA) tool that hides the cloud management details from the wind engineer and provides an intuitive user interface; 2) the estimation of the optimal number of cores (vCPUs) for virtual machine instances provided by AWS and Google Cloud based on average run time and total cost metrics for a given number of cells of a CFD-simulation. n1-highcpu-96 Google Cloud VM met both goals: low cost and low runtime per timestep. For the number of vCPUs below 16, the c4.8xlarge AWS VM type has the least runtime per timestep in all the cases. Google Cloud instances with high vCPUs are recommended to run the simulations if budget is a big concern.

关键词： Cloud computing Computational modeling Google Containers Buildings Tools Numerical models

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Comparison of Atom Detection Algorithms for Neutral Atom Quantum Computing

arXiv

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arXiv 2024年

作者： Winklmann, Jonas Alberti, Andrea Schulz, Martin Chair of Computer Architecture and Parallel Systems Technical University of Munich Munich Germany Quantum Many-Body Systems Division Max Planck Institute of Quantum Optics Garching Germany

In neutral atom quantum computers, readout and preparation of the atomic qubits are usually based on fluorescence imaging and subsequent analysis of the acquired image. For each atom site, the brightness or some comparable metric is estimated and used to predict the presence or absence of an atom. Across different setups, we can see a vast number of different approaches used to analyze these images. Often, the choice of detection algorithm is either not mentioned at all or it is not justified. We investigate several different algorithms and compare their performance in terms of both precision and execution run time. To do so, we rely on a set of synthetic images across different simulated exposure times with known occupancy states, which we generated using a previously validated imaging simulation. Since the use of simulation provides us with the ground truth of atom site occupancy, we can easily state precise error rates and variances of the reconstructed property. However, knowing the relative performance of these algorithms is not sufficient to justify their use, since better ones can exist that were not compared. To investigate this possibility, we calculated the Cramér-Rao bound in order to establish an upper limit that even a perfect estimator cannot outperform. As the metric of choice, we used the number of photonelectrons that can be contributed to a specific atom site. Every estimator that reconstructs a different property can simply be scaled accordingly. Since the bound depends on the occupancy of neighboring sites, we provide the best and worst cases, as well as a half filled one, which should represent an averaged bound best. Our comparison shows that of our tested algorithms, a global non-linear least-squares solver that uses the optical system’s point spread function (PSF) to return a global bias and each sites’ number of photoelectrons performed the best, on average crossing the worst-case bound for longer exposure times. Its main drawback is its hug

关键词： Quantum computers

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Realistic Neutral Atom Image Simulation

Realistic Neutral Atom Image Simulation

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

作者： Jonas Winklmann Dimitrios Tsevas Martin Schulz Chair of Computer Architecture and Parallel Systems Technical University of Munich Munich Germany Quantum Many-Body Systems Division Max Planck Institute of Quantum Optics Garching Germany

Neutral atom quantum computers require accurate single atom detection for the preparation and readout of their qubits. This is usually done using fluorescence imaging. The occupancy of an atom site in these images is often somewhat ambiguous due to the stochastic nature of the imaging process. Further, the lack of ground truth makes it difficult to rate the accuracy of reconstruction algorithms. We introduce a bottom-up simulator that is capable of generating sample images of neutral atom experiments from a description of the actual state in the simulated system. Possible use cases include the creation of exemplary images for demonstration purposes, fast training iterations for deconvolution algorithms, and generation of labeled data for machine-learning-based atom detection approaches. The implementation is available through our GitHub as a C library or wrapped Python package. We show the modeled effects and implementation of the simulations at different stages of the imaging process. Not all real-world phenomena can be reproduced perfectly. The main discrepancies are that the simulator allows for only one characterization of optical aberrations across the whole image, supports only discrete atom locations, and does not model all effects of complementary metal-oxide-semiconductor (CMOS) cameras perfectly. Nevertheless, our experiments show that the generated images closely match real-world pictures to the point that they are practically indistinguishable and can be used as labeled data for training the next generation of detection algorithms.

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Flexible hardware acceleration for instruction-grain lifeguards

Flexible hardware acceleration for instruction-grain lifegua...

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作者： Chen, Shimin Kozuch, Michael Gibbons, Phillip B. Ryan, Michael Strigkos, Theodoros Mowry, Todd C. Ruwase, Olatunji Vlachos, Evangelos Falsafi, Babak Ramachandran, Vijaya Intel Research Pittsburgh 4720 Forbes Ave. Pittsburgh PA 15213 United States Computer Science Department Carnegie Mellon University Pittsburgh PA United States Parallel Systems Architecture Laboratory École Polytechnique Fédérale de Lausanne Lausanne Switzerland Deartment of Computer Science University of Texas at Austin Austin TX United States

Instruction-grain lifeguards monitor executing programs at the granularity of individual instructions to quickly detect bugs and security attacks, but their fine-grain nature incurs high monitoring overheads. This article identifies three common sources of these overheads and proposes three techniques that together constitute a general-purpose hardware acceleration framework for lifeguards. © 2009 IEEE.

关键词： Data mining

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Exploring the Use of WebAssembly in HPC

arXiv

引用

arXiv 2023年

作者： Chadha, Mohak Krueger, Nils John, Jophin Jindal, Anshul Gerndt, Michael Benedict, Shajulin Chair of Computer Architecture and Parallel Systems Technische Universität München Germany Department of Computer Science and Engg. Indian Institute of Information Technology Kerala Kottayam India

Containerization approaches based on namespaces offered by the Linux kernel have seen an increasing popularity in the HPC community both as a means to isolate applications and as a format to package and distribute them. However, their adoption and usage in HPC systems faces several challenges. These include difficulties in unprivileged running and building of scientific application container images directly on HPC resources, increasing heterogeneity of HPC architectures, and access to specialized networking libraries available only on HPC systems. These challenges of container-based HPC application development closely align with the several advantages that a new universal intermediate binary format called WebAssembly (Wasm) has to offer. These include a lightweight userspace isolation mechanism and portability across operating systems and processor architectures. In this paper, we explore the usage of Wasm as a distribution format for MPI-based HPC applications. To this end, we present MPIWasm, a novel Wasm embedder for MPI-based HPC applications that enables high-performance execution of Wasm code, has low-overhead for MPI calls, and supports high-performance networking interconnects present on HPC systems. We evaluate the performance and overhead of MPIWasm on a production HPC system and AWS Graviton2 nodes using standardized HPC benchmarks. Results from our experiments demonstrate that MPIWasm delivers competitive native application performance across all scenarios. Moreover, we observe that Wasm binaries are 139.5x smaller on average as compared to the statically-linked binaries for the different standardized benchmarks. Copyright © 2023, The Authors. All rights reserved.

关键词： Containers

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Quantifying the quality of indoor maps 4

Quantifying the quality of indoor maps

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4th ISPRS Geospatial Week 2019

作者： Assali, M. Pipelidis, G. Podolskiy, V. Iwaszczuk, D. Heinen, L. Gerndt, M. Dept. of Computer Architecture and Parallel Systems Dept. of Informatics Technical University of Munich Munich Germany Software and Systems Engineering Research Group Dept. of Informatics Technical University of Munich Munich Germany Remote Sensing and Image Analysis Group Dept. of Civil and Environmental Engineering Science Technische Universität Darmstadt Germany BMW Group IT Munich Germany

Indoor maps are required for multiple applications, such as, navigation, building maintenance and robotics. One of common methods for map generation is laser scanning. In such maps, not only geometry of the map is of interest, but also its quality. This study aims at developing methods for real-time generation of indoor maps using features extracted from pointclouds obtained by a robot with their simultaneous quality assessment. We investigate, how this quality can be quantified for feature-based maps. First, we introduce a method for modeling 2D maps into 3D models that enable their usage for localization. Second, we review and evaluate a number of algorithms that can enable us to address features in a map. Hence, we enable the generation of objects from a pointcloud that has been sensed. Finally, we study several aspects of the map quality and we formalize them into metrics that can be applied to quantify their quality. © Authors 2019.

关键词： Robots

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Evaluation of Autoscaling Metrics for (stateful) IoT Gateways

Evaluation of Autoscaling Metrics for (stateful) IoT Gateway...

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IEEE International Conference on Service-Oriented Computing and Applications (SOCA)

作者： Helge Dickel Vladimir Podolskiy Michael Gerndt Chair of Computer Architecture and Parallel Systems Technical University of Munich Garching Germany Industrie 4.0 & Digital Supply Chain Innovation SAP SE Hallbergmoos Germany

Wide adoption of Internet of Things solutions in the industry requires IoT platforms to support long-running, stateful protocols with numerous connections to ingest the measurements, and at the same time to provide the highest throughput possible to achieve service level objectives (SLOs). The challenge of providing sufficient throughput can be solved via automated horizontal scalability for IoT platforms' gateways. Firstly, to address this challenge, a study of the state-of-the-art solutions and approaches adopted in the industry to ensure predictable throughput at IoT gateways was conducted. Secondly, the following three gateways autoscaling metrics were studied on the in-house developed cloud-native IoT Platform: CPU utilization, the number of concurrent active connections, and the absolute throughput per gateway. The results of the experimental evaluation suggest the combination of rate limiting and active connection monitoring as a prerequisite for high throughput at IoT gateways.

关键词： Logic gates Protocols Quality of service Measurement Throughput Cloud computing Sensors

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