Bridging the gap between high-performance, cloud and service-oriented computing - Ditter, Alexander; Tielemann, Michael; Fey, Dietmar (Proceedings - 2019 IEEE 4th International Workshops on Foundations and Applications of Self* Systems, FAS*W 2019, 2019)
Modern large-scale computing systems are often naturally assumed to be based on the cloud provisioning paradigm. While this model is very flexible and often more cost effective than the actual ownership of physical servers, it also comes at a price, i.e., abstraction by virtualization. Even today, there are many fields of application in which any kind of performance degradation would be considered harmful. These types of applications are what we consider to be the core of classical high-performance computing. Bridging the gap between this low level performance optimization oriented execution model, higher level but more flexible cloud-based Infrastructure-as-a-Service provisioning and finally service-oriented execution models on the same physical hardware is a very challenging task. It requires tailor-made solutions to connect and combine the various independent software layers and abstraction stacks into a single manageable platform. In this paper we present our approach for the integration of all three tiers into one large scale hardware and software framework. Based on our existing solution for the simultaneous operation of cluster and cloud infrastructure on the same physical hardware, we provide an outlook on our current work-in-progress and vision for the coupling of two remote locations into a single distributed system for service-oriented applications.
CRIS-Team Scopus Importer:2019-10-22
Keywords: Cloud Computing; Cluster Computing; Services Computing

Cache Aware Instruction Accurate Simulation of a 3-D Coastal Ocean Model on Low Power Hardware - Schönwetter, Dominik; Ditter, Alexander; Aizinger, Vadym; Reuter, Balthasar; Fey, Dietmar (6th International Conference on Simulation and Modeling Methodologies, Technologies and Applications, 2016)

C++ Classes and Templates for OpenCL Kernels with PATOS - Richter-Gottfried, Franz; Kreutzer, Patrick; Ditter, Alexander; Schneider, Max; Fey, Dietmar (Proceedings of the 4th International Workshop on OpenCL, 2016)

Distributed Asynchronous Jacobi Methods - Schwarzmeier, Christoph; Ditter, Alexander; Fey, Dietmar (International Symposium on Computational Science at Scale, 2018)
We present the implementation and evaluation of distributed asynchronous Jacobi methods with focus on cluster and cloud infrastructure. Asynchronous iterative methods intend to decrease the time needed for solving systems of linear equations by optimizing, i.e., reducing the amount of communication between processes. Two different versions of each the synchronous and asynchronous Jacobi method are implemented to solve the discretized Laplace's equation on a two-dimensional rectangular domain. The asynchronous implementations are observed to be superior in both scalability and runtime on any tested hardware environmen

Fe2vCl2: From Bare Metal to High Performance Computing on Virtual Clusters and Cloud Infrastructure - Ditter, Alexander; Graf, Gabriel; Fey, Dietmar (Proceedings of the 4th Workshop on CrossCloud Infrastructures & Platforms, 2017)
UnivIS-Import:2019-08-15:Pub.2017.tech.IMMD.IMMD3.fe2vcl
Keywords: Cloud computing; Container; High Performance Computing; Software as a Service

i3sched Ein OpenNebula Scheduler für die Oracle Grid Engine - Ditter, Alexander; Limmer, Steffen; Fey, Dietmar (Grid-, Cloud und Big-Data Technologien für Systementwurf und -analyse, 2013)
UnivIS-Import:2015-04-16:Pub.2013.tech.IMMD.IMMD3.i3sche

Improving instruction accurate simulation for parallel automotive applications - Schönwetter, Dominik; Ditter, Alexander; Fey, Dietmar; Mader, Ralph (11th IEEE Symposium on Industrial Embedded Systems, SIES 2016, Krakow, Poland, May 23-25, 2016, 2016)
UnivIS-Import:2019-08-15:Pub.2016.tech.IMMD.IMMD3.improv

Memory Analysis and Performance Modeling for HPC Applications on Embedded Hardware via Instruction Accurate Simulation - Ditter, Alexander; Schönwetter, Dominik; Kuzmin, Anton; Fey, Dietmar; Aizinger, Vadym (Proceedings of the 2015 Federated Conference on Software Development and Object Technologies, 2017)
UnivIS-Import:2019-08-15:Pub.2017.tech.IMMD.IMMD3.memory

Modellzentrierter Test in virtualisierten Testumgebungen - Ditter, Alexander; Limmer, Steffen; Fey, Dietmar; Pruksch, Matthias (2013)
UnivIS-Import:2015-03-09:Pub.2013.tech.IMMD.IMMD3.modell

Multi-GPU Based Evaluation and Analysis of Prehistoric Ice Cores Using OpenCL - Ditter, Alexander; Schaffert, Roman; Fey, Dietmar; Schön, Tobias; Gruber, Roland (IST 2015 Proceedings, 2015)
UnivIS-Import:2017-12-18:Pub.2015.tech.IMMD.IMMD3.multig
Keywords: climate research; Computed tomography; connected-component analysis; non-destructive testing

On Parallel Software Verification using Boolean Equation Systems - Ditter, Alexander; Ceska, Milan; Lüttgen, Gerald (Lecture Notes in Computer Science, 2012)
Multi- and many-core hardware platforms are today widely accessible and used to significantly accelerate many computationally demanding tasks. In this paper we describe a parallel approach to solve Boolean Equation Systems (BESs) in the context of model checking. We focus on the applicability of state-of-the-art, shared-memory parallel hardware - multi-core CPUs and many-core GPUs - to speed up the resolution procedure for BESs. In this setting, we experimentally show the scalability and competitiveness of our approach, compared to an optimized sequential implementation, based on a large benchmark suite containing models of software systems and protocols from industry and academi
UnivIS-Import:2015-04-16:Pub.2012.tech.IMMD.IMMD3.onpara
Keywords: boolean equation systems; formal verification; parallel model checking

On the Way to Big Data Applications in Industrial Computed Tomography - Ditter, Alexander; Fey, Dietmar; Schön, Tobias; Steven, Oeckl (Proceedings of BigData Congress 2014, 2014)
Computed Tomography (CT) has been around, especially in the medical field, for more than 20 years. Although, the mathematical foundations for CT were known more than a century ago, technical limitations delayed its practical application for more than 70 years. Today, we can build CT systems large enough to scan an entire car, yet, for the processing of the resulting data we are facing a 'Big (sensor) Data Problem'. We currently do not have suitable methods and tools and cannot handle the large amount of data with conventional state-of-the-art techniques. As industrial CT became more and more prevalent over the last few years, especially due its unique features in the field of non destructive testing, we are proposing and evaluating the use of new methods, work flows and technologies, such as Cloud Computing, in order to provide suitable solutions for handling the steadily growing amount of data and its efficient processin
UnivIS-Import:2015-04-16:Pub.2014.tech.IMMD.IMMD3.onthew
Keywords: compression; industrial computed tomography; nondestructive testing; sensor data; streaming

OpenCL 2.0 for FPGAs using OCLAcc - Richter, Franz; Ditter, Alexander; Fey, Dietmar (Proceedings of the Second International Workshop on FPGAs for Software Programmers (FSP 2015), 2015)
UnivIS-Import:2015-10-26:Pub.2015.tech.IMMD.IMMD3.opencl

Programming Reconfigurable Heterogeneous Computing Clusters Using MPI with Transpilation - Ringlein, Burkhard; Abel, Francois; Ditter, Alexander; Weiss, Beat; Hagleitner, Christoph; Fey, Dietmar (Proceedings of H2RC 2020: 6th International Workshop on Heterogeneous High-Performance Reconfigurable Computing, Held in conjunction with SC 2020: The International Conference for High Performance Computing, Networking, Storage and Analysis, 2020)
With the slowdown of Moore's law and the stop of Dennard scaling, energy efficiency of compute hardware translates to compute power. Therefore, High-Performance Computing (HPC) systems tend to rely more and more on accelerators such as Field-Programmable Gate Arrays (FPGAs) to fuel high demanding workloads, like Big Data applications or Deep Neuronal Networks. These FPGAs are reconfigurable and sometimes no longer bus-attached to a CPU but directly connected to the data center network fabric as standalone nodes. This mix of CPUs and FPGAs leads to the creation of Reconfigurable Heterogeneous HPC (ReH2PC) clusters for which no established programming model exists, despite many proposals in the past. In contrast to this, the Message Passing Interface (MPI) has evolved as the de-facto standard to program classical HPC clusters, due to its high-re-usability and fast development of applications. This paper revisits the programming model of ReH2PC clusters and argues that MPI is suitable for program-ming heterogeneous clusters of FPGAs and CPUs. Our experiments with 31 FPGAs show an average speedup of 4 and a 90% reduction of power consumption compared to a cluster of CPUs. We demonstrate a one-click solution for compiling and deploying a standard MPI application on ReH2PC clusters. Our framework implements a High-Level Synthesis (HLS) library, a specific run-time environment for FPGAs and CPUs, and a transpiler that closes the semantic gap between the MPI API and FPGA designs. Our experiments with 31 FPGAs show an average speedup of 4 and a 90% reduction of power consumption compared to a cluster of CPUs
CRIS-Team Scopus Importer:2021-04-19
Keywords: data centers; heterogeneous clusters; heterogeneous programming model; MPI; network-attached FPGA; partial reconfiguration; stand-alone FPGA; transpilation

Reproducibility report: Team SegFAUlt @ SCC 2016 - Ditter, Alexander; Laukemann, Jan; Oehlrich, Benedikt (Parallel Computing, 2017)
UnivIS-Import:2019-08-15:Pub.2017.tech.IMMD.IMMD3.reprod
Keywords: De Bruijn Graphs; High performance computing; ParConnect; Reproducibility; Student cluster compeition

Security Aspects of Cloud Computing - Trusted Cloud in Cloud4E - Ditter, Alexander; Fey, Dietmar (Conference Proceedings of the 17th ITI Symposium, 2014)
UnivIS-Import:2015-10-26:Pub.2014.tech.IMMD.IMMD3.securi

SmartEco: An Integrated Solution from Load Balancing between the Grid and Consumers to Local Energy Efficiency - Bürner, Johannes; Ditter, Alexander; Fey, Dietmar; Franke, Jörg (IEEE/ACM 8th International Conference on Utility and Cloud Computing (UCC), 2015)

System architecture for network-attached FPGAs in the cloud using partial reconfiguration - Ringlein, Burkhard; Abel, Francois; Ditter, Alexander; Weiss, Beat; Hagleitner, Christoph; Fey, Dietmar (Proceedings - 29th International Conference on Field-Programmable Logic and Applications, FPL 2019, 2019)
Emerging applications such as deep neural networks, bioinformatics or video encoding impose a high computing pressure on the Cloud. Reconfigurable technologies like Field-Programmable Gate Arrays (FPGAs) can handle such compute-intensive workloads in an efficient and performant way. To seamlessly incorporate FPGAs into existing Cloud environments and leverage their full power efficiency, FPGAs should be directly attached to the data center network and operate independent of power-hungry CPUs. This raises new questions about resource management, application deployment and network integrity. We present a system architecture for managing a large number of network-attached FPGAs in an efficient, flexible and scalable way. To ensure the integrity of the infrastructure, we use partial reconfiguration to separate the non-privileged user logic from the privileged system logic. To create a really scalable and agile cloud service, the management of all resources builds on the Representational State Transfer (REST) concept.
CRIS-Team Scopus Importer:2019-12-10
Keywords: Cloud computing; Data centers; Network-attached FPGA; Partial reconfiguration; Stand-alone FPGA

Test@Cloud - A Platform for Test Execution in the Cloud - Limmer, Steffen; Ditter, Alexander; Fey, Dietmar; Pruksch, Matthias; Braun, Christopher; Drescher, Florian; Beißer-Dresel, Martin (Parallel-Algorithmen und Rechnerstrukturen, 2015)
UnivIS-Import:2015-10-26:Pub.2015.tech.IMMD.IMMD3.testcl

Testen in der Cloud - Automatisiertes Testen in virtualisierten Umgebungen - Ditter, Alexander; Pruksch, Matthias; Limmer, Steffen; Fey, Dietmar (Elektrotechnik, 2013)
UnivIS-Import:2015-03-09:Pub.2013.tech.IMMD.IMMD3.testen

The Impact of H.264/AVC on Compression and Non-Destructive Evaluation of Piston Data in Industrial Computed Tomography - Ditter, Alexander; Fey, Dietmar; Schön, Tobias; Luxa, Maik; Gruber, Roland (IST 2013 Proceedings, 2013)
The application of video encoding for the compression of Computed Tomography (CT) based projection images is very promising with respect to a more efficient transmission and storage of this particular type of data. Especially the use of 'off-the-shelf' technologies, such as the H.264/AVC codec, ensures long term support due to its widespread use in the media industry. We present an approach for the application of this standard 8-bit video codec even for 16-bit projection data sets. Based on a benchmark set of 200 pistons, we evaluate its performance in terms of the compression rate relative to the original input data. Furthermore, we compare the detection rate of manufacturing defects in the reconstructed volumes to the state-of-the-art technique without video encoding. For this purpose our benchmark does not only contain the projections of the 200 pistons, but additionally the exact information about location and size of the manufacturing defects of the respective piston. We show that the detection rate based on the video encoded projection data is, up to a certain threshold, as good as without compression. © 2013 IEEE.
UnivIS-Import:2015-04-16:Pub.2013.tech.IMMD.IMMD3.theimp
Keywords: Compression; industrial computed tomography; non-destructice testing; video encoding

The NAS Benchmark Kernels for Single and Multi-Tenant Cloud Instances with LXC/KVM - Maliszewski, Anderson Mattheus; Griebler, Dalvan; Schepke, Claudio; Ditter, Alexander; Fey, Dietmar; Fernandes, Luiz Gustavo (2018 International Conference on High Performance Computing Simulation (HPCS), 2018)
Private IaaS clouds are an attractive environment for scientific workloads and applications. It provides advantages such as almost instantaneous availability of high-performance computing in a single node as well as compute clusters, easy access for researchers, and users that do not have access to conventional supercomputers. Furthermore, a cloud infrastructure provides elasticity and scalability to ensure and manage any software dependency on the system with no third-party dependency for researchers. However, one of the biggest challenges is to avoid significant performance degradation when migrating these applications from physical nodes to a cloud environment. Also, we lack more research investigations for multi-Tenant cloud instances. In this paper, our goal is to perform a comparative performance evaluation of scientific applications with single and multi-Tenancy cloud instances using KVM and LXC virtualization technologies under private cloud conditions. All analyses and evaluations were carried out based on NAS Benchmark kernels to simulate different types of workloads. We applied statistic significance tests to highlight the differences. The results have shown that applications running on LXC-based cloud instances outperform KVM-based cloud instances in 93.75% of the experiments w.r.t single tenant. Regarding multi-Tenant, LXC instances outperform KVM instances in 45% of the results, where the performance differences were not as significant as expected.
UnivIS-Import:2019-08-15:Pub.2018.tech.IMMD.IMMD3.thenas
Keywords: cloud computing; parallel processing; virtual machines; virtualisation; multitenant cloud instances; private IaaS clouds; high-performance computing; single node; compute clusters; cloud infrastructure; cloud environment; comparative performance evaluation; scientific applications; multitenancy cloud instances; private cloud conditions; LXC-based cloud instances; KVM-based cloud instances; LXC instances; KVM instances; LXC virtualization technologies; KVM virtualization technologies; LXC-KVM; single tenant cloud instances; performance degradation; NAS benchmark kernels; Cloud computing; Virtualization; Benchmark testing; Containers; Hardware; Kernel; Linux

Tsunami and Storm Surge Simulation Using Low Power Architectures - Concept and Evaluation - Schönwetter, Dominik; Ditter, Alexander; Kleinert, Bruno; Hendricks, Arne; Aizinger, Vadym; Köstler, Harald; Fey, Dietmar (Proceedings of the 5th International Conference on Simulation and Modeling Methodologies, Technologies and Applications, 2015)
UnivIS-Import:2018-09-06:Pub.2015.tech.IMMD.IMMD3.tsunam
Keywords: Crisis modeling and simulation; Environmental modeling; Multiscale simulation

Virtualization Guided Tsunami and Storm Surge Simulations for Low Power Architectures - Schönwetter, Dominik; Ditter, Alexander; Kleinert, Bruno; Hendricks, Arne; Aizinger, Vadym; Fey, Dietmar (Springer Verlag, 2016)
UnivIS-Import:2018-09-05:Pub.2016.tech.IMMD.IMMD3.virtua
Keywords: Multiscale simulation; Environmental modeling; Crisis modeling and simulation

ZRLMPI: A Unified Programming Model for Reconfigurable Heterogeneous Computing Clusters - Ringlein, Burkhard; Abel, Francois; Ditter, Alexander; Weiss, Beat; Hagleitner, Christoph; Fey, Dietmar (Proceedings - 28th IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2020, 2020)
Over the past two decades, the Message Passing Interface (MPI) has evolved as the de-facto standard for programming High-Performance Computing (HPC) clusters. Its widespread utilization led to the rapid development of applications and high reusability. Meanwhile, energy- and compute-efficient devices such as Field-Programmable Gate Arrays (FPGAs) are stepping into modern data centers and HPC clusters to address the nearing end of technology scaling. This combination of traditional CPU servers and FPGA nodes leads to Reconfigurable Heterogeneous HPC (ReH 2 PC) systems that are particularly cumbersome to program because of the absence of a standard programming model. This work advocates the use of MPI to program such ReH 2 PC clusters and presents a proof of concept based on a cross-compiler, a High-Level Synthesis library, C++ library, an FPGA- and a CPU-runtime environment. The result is a one-click solution, which compiles a standard MPI application for a ReH 2 PC cluster.
CRIS-Team Scopus Importer:2020-07-10