Pub Date : 2018-03-01DOI: 10.1109/PDP2018.2018.00096
Francesco Cauteruccio, Davide Consalvo, G. Terracina
In this paper, we propose a method for the computation of a novel distance metrics, called Multi-Parameterized Edit Distance (MPED) among strings defined over heterogeneous alphabets. We show that the computation of MPED is hard and that several interesting application contexts can benefit from its application. We then present a novel imple- mentation strategy based on an Evolutionary Heuristics, which we experimentally demonstrate to be efficient and effective for the problem at hand. Our approach paves indeed the way to the adoption of this new metric in all those contexts in which involved strings come from heterogeneous sources, each adopting its own alphabet.
{"title":"High Performance Computation for the Multi-Parameterized Edit Distance","authors":"Francesco Cauteruccio, Davide Consalvo, G. Terracina","doi":"10.1109/PDP2018.2018.00096","DOIUrl":"https://doi.org/10.1109/PDP2018.2018.00096","url":null,"abstract":"In this paper, we propose a method for the computation of a novel distance metrics, called Multi-Parameterized Edit Distance (MPED) among strings defined over heterogeneous alphabets. We show that the computation of MPED is hard and that several interesting application contexts can benefit from its application. We then present a novel imple- mentation strategy based on an Evolutionary Heuristics, which we experimentally demonstrate to be efficient and effective for the problem at hand. Our approach paves indeed the way to the adoption of this new metric in all those contexts in which involved strings come from heterogeneous sources, each adopting its own alphabet.","PeriodicalId":333367,"journal":{"name":"2018 26th Euromicro International Conference on Parallel, Distributed and Network-based Processing (PDP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129817200","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-03-01DOI: 10.1109/PDP2018.2018.00012
Felix MoBbauer, R. Kowalewski, Tobias Fuchs, K. Fürlinger
Fortran Coarrays are a well known data structure in High Performance Computing (HPC) applications. There have been various attempts to port the concept to other programming languages that have a wider user base outside of scientific computing. While a popular implementation of the partitioned global address space (PGAS) model is Unified Parallel C (UPC), there is currently no portable implementation of Coarrays for C++. In this paper a portable version is presented, which is closely based on the Coarray C++ implementation of the Cray Compiling Environment. In this work we focus on a common subset of all proposed features by Cray. Our implementation utilizes the distributed data structures provided by the DASH library, demonstrating their universal applicability. Finally, a performance evaluation shows that our proposed Coarray abstraction adds negligible overhead and even outperforms native Coarray Fortran.
{"title":"A Portable Multidimensional Coarray for C++","authors":"Felix MoBbauer, R. Kowalewski, Tobias Fuchs, K. Fürlinger","doi":"10.1109/PDP2018.2018.00012","DOIUrl":"https://doi.org/10.1109/PDP2018.2018.00012","url":null,"abstract":"Fortran Coarrays are a well known data structure in High Performance Computing (HPC) applications. There have been various attempts to port the concept to other programming languages that have a wider user base outside of scientific computing. While a popular implementation of the partitioned global address space (PGAS) model is Unified Parallel C (UPC), there is currently no portable implementation of Coarrays for C++. In this paper a portable version is presented, which is closely based on the Coarray C++ implementation of the Cray Compiling Environment. In this work we focus on a common subset of all proposed features by Cray. Our implementation utilizes the distributed data structures provided by the DASH library, demonstrating their universal applicability. Finally, a performance evaluation shows that our proposed Coarray abstraction adds negligible overhead and even outperforms native Coarray Fortran.","PeriodicalId":333367,"journal":{"name":"2018 26th Euromicro International Conference on Parallel, Distributed and Network-based Processing (PDP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126104448","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-03-01DOI: 10.1109/PDP2018.2018.00093
P. Kontou, I. Georgoudas, G. Trunfio, G. Sirakoulis
This study deals with the evacuation of areas that involve people with disabilities. A crowd evacuation model has been developed using the Cellular Automata (CA) parallel computing tool. This model is capable of simulating and evaluating human behavior and special features that exist when people with disabilities are included in the process of evacuation. During the experimental process, the model simulates the evacuation of a secondary school for disabled children in the prefecture of Xanthi. After attendance and observation of an earthquake safety exercise organized by this school, the total evacuation time is recorded. At the end of this study, the developed model is validated on the basis of actual data and useful conclusions are drawn for the specific application area. In addition, with the modification of the original data, the model is applicable to every building case.
{"title":"Cellular Automata Modelling of the Movement of People with Disabilities during Building Evacuation","authors":"P. Kontou, I. Georgoudas, G. Trunfio, G. Sirakoulis","doi":"10.1109/PDP2018.2018.00093","DOIUrl":"https://doi.org/10.1109/PDP2018.2018.00093","url":null,"abstract":"This study deals with the evacuation of areas that involve people with disabilities. A crowd evacuation model has been developed using the Cellular Automata (CA) parallel computing tool. This model is capable of simulating and evaluating human behavior and special features that exist when people with disabilities are included in the process of evacuation. During the experimental process, the model simulates the evacuation of a secondary school for disabled children in the prefecture of Xanthi. After attendance and observation of an earthquake safety exercise organized by this school, the total evacuation time is recorded. At the end of this study, the developed model is validated on the basis of actual data and useful conclusions are drawn for the specific application area. In addition, with the modification of the original data, the model is applicable to every building case.","PeriodicalId":333367,"journal":{"name":"2018 26th Euromicro International Conference on Parallel, Distributed and Network-based Processing (PDP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128466263","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-03-01DOI: 10.1109/PDP2018.2018.00100
Rodrigo Baya, C. Porrini, M. Pedemonte, P. Ezzatti
In the last decade the use of hybrid hardware (e.g., multicore processors + coprocessors) has been growing on the HPC field. However, this evolution in the HPC hardware has not been fully exploited by the WRF model since it shows limitations in the scalability when a large number of computing units are used. In a previous work, we proposed an asynchronous architecture for the WRF that overlaps the radiation computation with the execution of the rest of the model. In this work, we extend this idea with the aim of exploiting the computational power offered by hybrid hardware platforms. Specifically, we implement an OpenMP version of the asynchronous architecture and include the use of two types of coprocessors, a Xeon Phi and a GPU. The experimental evaluation performed shows that our proposal is able to adequately exploit these secondary computation devices, reaching interesting runtime reductions when solving tests cases from real scenarios.
{"title":"Task Parallelism in the WRF Model Through Computation Offloading to Many-Core Devices","authors":"Rodrigo Baya, C. Porrini, M. Pedemonte, P. Ezzatti","doi":"10.1109/PDP2018.2018.00100","DOIUrl":"https://doi.org/10.1109/PDP2018.2018.00100","url":null,"abstract":"In the last decade the use of hybrid hardware (e.g., multicore processors + coprocessors) has been growing on the HPC field. However, this evolution in the HPC hardware has not been fully exploited by the WRF model since it shows limitations in the scalability when a large number of computing units are used. In a previous work, we proposed an asynchronous architecture for the WRF that overlaps the radiation computation with the execution of the rest of the model. In this work, we extend this idea with the aim of exploiting the computational power offered by hybrid hardware platforms. Specifically, we implement an OpenMP version of the asynchronous architecture and include the use of two types of coprocessors, a Xeon Phi and a GPU. The experimental evaluation performed shows that our proposal is able to adequately exploit these secondary computation devices, reaching interesting runtime reductions when solving tests cases from real scenarios.","PeriodicalId":333367,"journal":{"name":"2018 26th Euromicro International Conference on Parallel, Distributed and Network-based Processing (PDP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130841685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-03-01DOI: 10.1109/PDP2018.2018.00112
M. Bugli
Current state-of-the-art simulations of accretion flows onto black holes require a significant level of numerical sophistication, in order to allow the three-dimensional modeling of relativistic magnetized plasma in a regime of strong gravity. We present here a new version of the GRMHD code ECHO developed in collaboration with the Max Planck Computing and Data Facility (MPCDF) and the Leibniz Rechenzentrum (LRZ), which employs a hybrid multidimensional MPI-OpenMP coupled with the production of MPI-HDF5 output files. The code's high degree of parallelization has been crucial for the study of some fundamental properties of thick accretion disks around black holes, in particular the excitation of non-axisymmetric modes in presence of both hydrodynamic and magnetohydrodynamic instabilities.
{"title":"ECHO-3DHPC: Relativistic Accretion Disks onto Black Holes","authors":"M. Bugli","doi":"10.1109/PDP2018.2018.00112","DOIUrl":"https://doi.org/10.1109/PDP2018.2018.00112","url":null,"abstract":"Current state-of-the-art simulations of accretion flows onto black holes require a significant level of numerical sophistication, in order to allow the three-dimensional modeling of relativistic magnetized plasma in a regime of strong gravity. We present here a new version of the GRMHD code ECHO developed in collaboration with the Max Planck Computing and Data Facility (MPCDF) and the Leibniz Rechenzentrum (LRZ), which employs a hybrid multidimensional MPI-OpenMP coupled with the production of MPI-HDF5 output files. The code's high degree of parallelization has been crucial for the study of some fundamental properties of thick accretion disks around black holes, in particular the excitation of non-axisymmetric modes in presence of both hydrodynamic and magnetohydrodynamic instabilities.","PeriodicalId":333367,"journal":{"name":"2018 26th Euromicro International Conference on Parallel, Distributed and Network-based Processing (PDP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131157079","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-03-01DOI: 10.1109/PDP2018.2018.00031
Ferrol Aderholdt, Manjunath Gorentla Venkata, Zachary W. Parchman
Extreme-scale applications (i.e., Big-Compute) are becoming increasingly data-intensive, i.e., producing and consuming increasingly large amounts of data. The HPC systems traditionally used for these applications are now used for Big-Data applications such as data analytics, social network analysis, machine learning, and genomics. As a consequence of these trends, the system architecture should be flexible and data-centric. This can already be witnessed in the pre-exascale systems with TBs of on-node hierarchical and heterogeneous memories, PBs of system memory, low-latency, high-throughput networks, and many threaded cores. As such, the pre-exascale systems suit the needs of both Big-Compute and Big-Data applications. Though the system architecture is flexible enough to support both Big-Compute and Big-Data, we argue there is a software gap. Particularly, we need data-centric abstractions to leverage the full potential of the system, i.e., there is a need for native support for data resilience, the ability to express data locality and affinity, mechanisms to reduce data movement, the ability to share data, and abstractions to express User's data usage and data access patterns. In this paper, we (i) show the need for taking a holistic approach towards data-centric abstractions, (ii) show how these approaches were realized in the SHARed data-structure centric Programming abstraction (SharP) library, a data-structure centric programming abstraction, and (iii) apply these approaches to a variety of applications that demonstrate its usefulness. Particularly, we apply these approaches to QMCPack and the Graph500 benchmark and demonstrate the advantages of this approach on extreme-scale systems.
{"title":"SharP Data Constructs: Data Constructs to Enable Data-Centric Computing","authors":"Ferrol Aderholdt, Manjunath Gorentla Venkata, Zachary W. Parchman","doi":"10.1109/PDP2018.2018.00031","DOIUrl":"https://doi.org/10.1109/PDP2018.2018.00031","url":null,"abstract":"Extreme-scale applications (i.e., Big-Compute) are becoming increasingly data-intensive, i.e., producing and consuming increasingly large amounts of data. The HPC systems traditionally used for these applications are now used for Big-Data applications such as data analytics, social network analysis, machine learning, and genomics. As a consequence of these trends, the system architecture should be flexible and data-centric. This can already be witnessed in the pre-exascale systems with TBs of on-node hierarchical and heterogeneous memories, PBs of system memory, low-latency, high-throughput networks, and many threaded cores. As such, the pre-exascale systems suit the needs of both Big-Compute and Big-Data applications. Though the system architecture is flexible enough to support both Big-Compute and Big-Data, we argue there is a software gap. Particularly, we need data-centric abstractions to leverage the full potential of the system, i.e., there is a need for native support for data resilience, the ability to express data locality and affinity, mechanisms to reduce data movement, the ability to share data, and abstractions to express User's data usage and data access patterns. In this paper, we (i) show the need for taking a holistic approach towards data-centric abstractions, (ii) show how these approaches were realized in the SHARed data-structure centric Programming abstraction (SharP) library, a data-structure centric programming abstraction, and (iii) apply these approaches to a variety of applications that demonstrate its usefulness. Particularly, we apply these approaches to QMCPack and the Graph500 benchmark and demonstrate the advantages of this approach on extreme-scale systems.","PeriodicalId":333367,"journal":{"name":"2018 26th Euromicro International Conference on Parallel, Distributed and Network-based Processing (PDP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132247232","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-03-01DOI: 10.1109/PDP2018.2018.00057
Luis Veas-Castillo, Gabriel Ovando-Leon, V. Gil-Costa, Mauricio Marín
We studied routing protocols for Delay Tolerant Networks devised to improve the message delivery performance in natural disaster scenarios. In this paper we propose the MinVisited protocol which during the transitive path to the message destination, selects the next node based on two features: (1) the most distant neighbor, and (2) the largest number of encounters with the destination node of the message. We compare our protocol with well-known protocols of the technical literature. The results show that the proposed protocol presents a low workload overhead with a number of hops lower than 2, and in average 95% of the messages are successfully delivered.
{"title":"MinVisited: A Message Routing Protocol for Delay Tolerant Network","authors":"Luis Veas-Castillo, Gabriel Ovando-Leon, V. Gil-Costa, Mauricio Marín","doi":"10.1109/PDP2018.2018.00057","DOIUrl":"https://doi.org/10.1109/PDP2018.2018.00057","url":null,"abstract":"We studied routing protocols for Delay Tolerant Networks devised to improve the message delivery performance in natural disaster scenarios. In this paper we propose the MinVisited protocol which during the transitive path to the message destination, selects the next node based on two features: (1) the most distant neighbor, and (2) the largest number of encounters with the destination node of the message. We compare our protocol with well-known protocols of the technical literature. The results show that the proposed protocol presents a low workload overhead with a number of hops lower than 2, and in average 95% of the messages are successfully delivered.","PeriodicalId":333367,"journal":{"name":"2018 26th Euromicro International Conference on Parallel, Distributed and Network-based Processing (PDP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133231982","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-03-01DOI: 10.1109/PDP2018.2018.00083
Hergys Rexha, S. Lafond, K. Desnos
Heterogeneous systems promise to improve performance and endurance of power constrained systems, by utilizing computing elements of different power and performance characteristics. Such systems provide the possibility to trade number and types of core with Dynamic Voltage and Frequency Scaling (DVFS) levels and core utilization rate to achieve optimal energy efficiency. Therefore by making smart decisions on application scheduling and mapping we can exploit and maximize the benefits of using heterogeneous processors. At the same time, the application level of parallelism can conveniently be exposed by dataflow Models of Computation (MoCs). In this paper we show an energy efficient execution approach for heterogeneous architecture. We demonstrate the approach on a real-life streaming application modelled with Parameterized and Interfaced Synchronous Dataflow (PiSDF). The presented solution shows how to integrate our approach in the workflow of a dataflow application prototyping tool. The obtained results demonstrate that, by using an optimal scheduling and mapping, more than 30% of energy reduction can be achieved on a single actor level.
{"title":"Energy-Efficient Actor Execution for SDF Application on Heterogeneous Architectures","authors":"Hergys Rexha, S. Lafond, K. Desnos","doi":"10.1109/PDP2018.2018.00083","DOIUrl":"https://doi.org/10.1109/PDP2018.2018.00083","url":null,"abstract":"Heterogeneous systems promise to improve performance and endurance of power constrained systems, by utilizing computing elements of different power and performance characteristics. Such systems provide the possibility to trade number and types of core with Dynamic Voltage and Frequency Scaling (DVFS) levels and core utilization rate to achieve optimal energy efficiency. Therefore by making smart decisions on application scheduling and mapping we can exploit and maximize the benefits of using heterogeneous processors. At the same time, the application level of parallelism can conveniently be exposed by dataflow Models of Computation (MoCs). In this paper we show an energy efficient execution approach for heterogeneous architecture. We demonstrate the approach on a real-life streaming application modelled with Parameterized and Interfaced Synchronous Dataflow (PiSDF). The presented solution shows how to integrate our approach in the workflow of a dataflow application prototyping tool. The obtained results demonstrate that, by using an optimal scheduling and mapping, more than 30% of energy reduction can be achieved on a single actor level.","PeriodicalId":333367,"journal":{"name":"2018 26th Euromicro International Conference on Parallel, Distributed and Network-based Processing (PDP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116170642","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-03-01DOI: 10.1109/PDP2018.2018.00121
P. Fernández, David del Rio Astorga, M. F. Dolz, Javier Fernández, O. Awile, José Daniel García Sánchez
Real time data processing is an important component of particle physics experiments with large computing resource requirements. As the Large Hadron Collider (LHC) at CERN is preparing for its next upgrade the LHCb experiment is upgrading its detector for a 30x increase in data throughput. In preparation for this upgrade the experiment is considering a number of architectural improvements encompassing both its software and hardware infrastructure. One of the hardware platforms under consideration is the Intel Xeon-Phi Knights Landing processor. Thanks to its on-package high-bandwidth memory and many-core architecture it offers an interesting alternative to more traditional server systems. We present a scalable, multi-threaded and NUMA-aware Kalman filter proto-application for particle track fitting expressed in terms of generic parallel patterns using the GrPPI interface. We show how code maintainability and readability improves, while maintaining comparable levels of performance to the baseline implementation. This is achieved by keeping the parallel algorithms in the underlying framework generic, but topology aware through the use of the Portable Hardware Locality (hwloc) library, which allows us to target different architectures with the same program. We measure the performance of our topology-aware GrPPI Kalman filter implementation on the Intel Xeon-Phi Knights Landing platform and conclude on the feasibility of integrating such high-level parallelization libraries in complex software frameworks such as LHCb's Gaudi framework.
{"title":"Parallelizing and Optimizing LHCb-Kalman for Intel Xeon Phi KNL Processors","authors":"P. Fernández, David del Rio Astorga, M. F. Dolz, Javier Fernández, O. Awile, José Daniel García Sánchez","doi":"10.1109/PDP2018.2018.00121","DOIUrl":"https://doi.org/10.1109/PDP2018.2018.00121","url":null,"abstract":"Real time data processing is an important component of particle physics experiments with large computing resource requirements. As the Large Hadron Collider (LHC) at CERN is preparing for its next upgrade the LHCb experiment is upgrading its detector for a 30x increase in data throughput. In preparation for this upgrade the experiment is considering a number of architectural improvements encompassing both its software and hardware infrastructure. One of the hardware platforms under consideration is the Intel Xeon-Phi Knights Landing processor. Thanks to its on-package high-bandwidth memory and many-core architecture it offers an interesting alternative to more traditional server systems. We present a scalable, multi-threaded and NUMA-aware Kalman filter proto-application for particle track fitting expressed in terms of generic parallel patterns using the GrPPI interface. We show how code maintainability and readability improves, while maintaining comparable levels of performance to the baseline implementation. This is achieved by keeping the parallel algorithms in the underlying framework generic, but topology aware through the use of the Portable Hardware Locality (hwloc) library, which allows us to target different architectures with the same program. We measure the performance of our topology-aware GrPPI Kalman filter implementation on the Intel Xeon-Phi Knights Landing platform and conclude on the feasibility of integrating such high-level parallelization libraries in complex software frameworks such as LHCb's Gaudi framework.","PeriodicalId":333367,"journal":{"name":"2018 26th Euromicro International Conference on Parallel, Distributed and Network-based Processing (PDP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114830968","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-03-01DOI: 10.1109/PDP2018.2018.00113
T. Dietrich, S. Bernuzzi, B. Brügmann, W. Tichy
The recent detection of gravitational waves and electromagnetic counterparts emitted during and after the collision of two neutron stars marks a breakthrough in the field of multi-messenger astronomy. Numerical relativity simulations are the only tool to describe the binary's merger dynamics in the regime when speeds are largest and gravity is strongest. In this work we report state-of-the-art binary neutron star simulations for irrotational (non-spinning) and spinning configurations. The main use of these simulations is to model the gravitational-wave signal. Key numerical requirements are the understanding of the convergence properties of the numerical data and a detailed error budget. The simulations have been performed on different HPC clusters, they use multiple grid resolutions, and are based on eccentricity reduced quasi-circular initial data. We obtain convergent waveforms with phase errors of 0.5-1.5rad accumulated over ~12 orbits to merger. The waveforms have been used for the construction of a phenomenological waveform model which has been applied for the analysis of the recent binary neutron star detection. Additionally, we show that the data can also be used to test other state-of-the-art semi-analytical waveform models.
{"title":"High-Resolution Numerical Relativity Simulations of Spinning Binary Neutron Star Mergers","authors":"T. Dietrich, S. Bernuzzi, B. Brügmann, W. Tichy","doi":"10.1109/PDP2018.2018.00113","DOIUrl":"https://doi.org/10.1109/PDP2018.2018.00113","url":null,"abstract":"The recent detection of gravitational waves and electromagnetic counterparts emitted during and after the collision of two neutron stars marks a breakthrough in the field of multi-messenger astronomy. Numerical relativity simulations are the only tool to describe the binary's merger dynamics in the regime when speeds are largest and gravity is strongest. In this work we report state-of-the-art binary neutron star simulations for irrotational (non-spinning) and spinning configurations. The main use of these simulations is to model the gravitational-wave signal. Key numerical requirements are the understanding of the convergence properties of the numerical data and a detailed error budget. The simulations have been performed on different HPC clusters, they use multiple grid resolutions, and are based on eccentricity reduced quasi-circular initial data. We obtain convergent waveforms with phase errors of 0.5-1.5rad accumulated over ~12 orbits to merger. The waveforms have been used for the construction of a phenomenological waveform model which has been applied for the analysis of the recent binary neutron star detection. Additionally, we show that the data can also be used to test other state-of-the-art semi-analytical waveform models.","PeriodicalId":333367,"journal":{"name":"2018 26th Euromicro International Conference on Parallel, Distributed and Network-based Processing (PDP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127904667","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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