Performance portability study for massively parallel computational fluid dynamics application on scalable heterogeneous architectures
Patient-specific hemodynamic simulations have the potential to greatly improve both the diagnosis and treatment of a variety of vascular diseases. Portability will enable wider adoption of computational fluid dynamics (CFD) applications in the biomedical research community and targeting to platforms...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Lee, Seyong [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2019transfer abstract |
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| Schlagwörter: |
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| Umfang: |
13 |
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| Übergeordnetes Werk: |
Enthalten in: 25. Functional Outcomes Following Orbital Preservation in Patients with Surgical management of Sinonasal Tumours - Al Asaadi, Zahra ELSEVIER, 2022, Amsterdam [u.a.] |
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| Übergeordnetes Werk: |
volume:129 ; year:2019 ; pages:1-13 ; extent:13 |
| Links: |
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| DOI / URN: |
10.1016/j.jpdc.2019.02.005 |
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| 520 | |a Patient-specific hemodynamic simulations have the potential to greatly improve both the diagnosis and treatment of a variety of vascular diseases. Portability will enable wider adoption of computational fluid dynamics (CFD) applications in the biomedical research community and targeting to platforms ideally suited to different vascular regions. In this work, we present a case study in performance portability that assesses (1) the ease of porting an MPI application optimized for one specific architecture to new platforms using variants of hybrid MPI＋X programming models; (2) performance portability seen when simulating blood flow in three different vascular regions on diverse heterogeneous architectures; (3) model-based performance prediction for future architectures; and (4) performance scaling of the hybrid MPI＋X programming on parallel heterogeneous systems. We discuss the lessons learned in porting HARVEY, a massively parallel CFD application, from traditional multicore CPUs to diverse heterogeneous architectures ranging from NVIDIA/AMD GPUs to Intel MICs and Altera FPGAs. | ||
| 520 | |a Patient-specific hemodynamic simulations have the potential to greatly improve both the diagnosis and treatment of a variety of vascular diseases. Portability will enable wider adoption of computational fluid dynamics (CFD) applications in the biomedical research community and targeting to platforms ideally suited to different vascular regions. In this work, we present a case study in performance portability that assesses (1) the ease of porting an MPI application optimized for one specific architecture to new platforms using variants of hybrid MPI＋X programming models; (2) performance portability seen when simulating blood flow in three different vascular regions on diverse heterogeneous architectures; (3) model-based performance prediction for future architectures; and (4) performance scaling of the hybrid MPI＋X programming on parallel heterogeneous systems. We discuss the lessons learned in porting HARVEY, a massively parallel CFD application, from traditional multicore CPUs to diverse heterogeneous architectures ranging from NVIDIA/AMD GPUs to Intel MICs and Altera FPGAs. | ||
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10.1016/j.jpdc.2019.02.005 doi GBV00000000000598.pica (DE-627)ELV046543007 (ELSEVIER)S0743-7315(19)30157-1 DE-627 ger DE-627 rakwb eng 610 VZ 44.96 bkl Lee, Seyong verfasserin aut Performance portability study for massively parallel computational fluid dynamics application on scalable heterogeneous architectures 2019transfer abstract 13 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Patient-specific hemodynamic simulations have the potential to greatly improve both the diagnosis and treatment of a variety of vascular diseases. Portability will enable wider adoption of computational fluid dynamics (CFD) applications in the biomedical research community and targeting to platforms ideally suited to different vascular regions. In this work, we present a case study in performance portability that assesses (1) the ease of porting an MPI application optimized for one specific architecture to new platforms using variants of hybrid MPI＋X programming models; (2) performance portability seen when simulating blood flow in three different vascular regions on diverse heterogeneous architectures; (3) model-based performance prediction for future architectures; and (4) performance scaling of the hybrid MPI＋X programming on parallel heterogeneous systems. We discuss the lessons learned in porting HARVEY, a massively parallel CFD application, from traditional multicore CPUs to diverse heterogeneous architectures ranging from NVIDIA/AMD GPUs to Intel MICs and Altera FPGAs. Patient-specific hemodynamic simulations have the potential to greatly improve both the diagnosis and treatment of a variety of vascular diseases. Portability will enable wider adoption of computational fluid dynamics (CFD) applications in the biomedical research community and targeting to platforms ideally suited to different vascular regions. In this work, we present a case study in performance portability that assesses (1) the ease of porting an MPI application optimized for one specific architecture to new platforms using variants of hybrid MPI＋X programming models; (2) performance portability seen when simulating blood flow in three different vascular regions on diverse heterogeneous architectures; (3) model-based performance prediction for future architectures; and (4) performance scaling of the hybrid MPI＋X programming on parallel heterogeneous systems. We discuss the lessons learned in porting HARVEY, a massively parallel CFD application, from traditional multicore CPUs to diverse heterogeneous architectures ranging from NVIDIA/AMD GPUs to Intel MICs and Altera FPGAs. Computational fluid dynamics Elsevier Performance prediction Elsevier OpenACC Elsevier Lattice Boltzmann method Elsevier Patient-specific hemodynamics Elsevier Heterogeneous architectures Elsevier Performance portability Elsevier Gounley, John oth Randles, Amanda oth Vetter, Jeffrey S. oth Enthalten in Elsevier Al Asaadi, Zahra ELSEVIER 25. Functional Outcomes Following Orbital Preservation in Patients with Surgical management of Sinonasal Tumours 2022 Amsterdam [u.a.] (DE-627)ELV008974187 volume:129 year:2019 pages:1-13 extent:13 https://doi.org/10.1016/j.jpdc.2019.02.005 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.96 Zahnmedizin VZ AR 129 2019 1-13 13 |
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10.1016/j.jpdc.2019.02.005 doi GBV00000000000598.pica (DE-627)ELV046543007 (ELSEVIER)S0743-7315(19)30157-1 DE-627 ger DE-627 rakwb eng 610 VZ 44.96 bkl Lee, Seyong verfasserin aut Performance portability study for massively parallel computational fluid dynamics application on scalable heterogeneous architectures 2019transfer abstract 13 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Patient-specific hemodynamic simulations have the potential to greatly improve both the diagnosis and treatment of a variety of vascular diseases. Portability will enable wider adoption of computational fluid dynamics (CFD) applications in the biomedical research community and targeting to platforms ideally suited to different vascular regions. In this work, we present a case study in performance portability that assesses (1) the ease of porting an MPI application optimized for one specific architecture to new platforms using variants of hybrid MPI＋X programming models; (2) performance portability seen when simulating blood flow in three different vascular regions on diverse heterogeneous architectures; (3) model-based performance prediction for future architectures; and (4) performance scaling of the hybrid MPI＋X programming on parallel heterogeneous systems. We discuss the lessons learned in porting HARVEY, a massively parallel CFD application, from traditional multicore CPUs to diverse heterogeneous architectures ranging from NVIDIA/AMD GPUs to Intel MICs and Altera FPGAs. Patient-specific hemodynamic simulations have the potential to greatly improve both the diagnosis and treatment of a variety of vascular diseases. Portability will enable wider adoption of computational fluid dynamics (CFD) applications in the biomedical research community and targeting to platforms ideally suited to different vascular regions. In this work, we present a case study in performance portability that assesses (1) the ease of porting an MPI application optimized for one specific architecture to new platforms using variants of hybrid MPI＋X programming models; (2) performance portability seen when simulating blood flow in three different vascular regions on diverse heterogeneous architectures; (3) model-based performance prediction for future architectures; and (4) performance scaling of the hybrid MPI＋X programming on parallel heterogeneous systems. We discuss the lessons learned in porting HARVEY, a massively parallel CFD application, from traditional multicore CPUs to diverse heterogeneous architectures ranging from NVIDIA/AMD GPUs to Intel MICs and Altera FPGAs. Computational fluid dynamics Elsevier Performance prediction Elsevier OpenACC Elsevier Lattice Boltzmann method Elsevier Patient-specific hemodynamics Elsevier Heterogeneous architectures Elsevier Performance portability Elsevier Gounley, John oth Randles, Amanda oth Vetter, Jeffrey S. oth Enthalten in Elsevier Al Asaadi, Zahra ELSEVIER 25. Functional Outcomes Following Orbital Preservation in Patients with Surgical management of Sinonasal Tumours 2022 Amsterdam [u.a.] (DE-627)ELV008974187 volume:129 year:2019 pages:1-13 extent:13 https://doi.org/10.1016/j.jpdc.2019.02.005 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.96 Zahnmedizin VZ AR 129 2019 1-13 13 |
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10.1016/j.jpdc.2019.02.005 doi GBV00000000000598.pica (DE-627)ELV046543007 (ELSEVIER)S0743-7315(19)30157-1 DE-627 ger DE-627 rakwb eng 610 VZ 44.96 bkl Lee, Seyong verfasserin aut Performance portability study for massively parallel computational fluid dynamics application on scalable heterogeneous architectures 2019transfer abstract 13 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Patient-specific hemodynamic simulations have the potential to greatly improve both the diagnosis and treatment of a variety of vascular diseases. Portability will enable wider adoption of computational fluid dynamics (CFD) applications in the biomedical research community and targeting to platforms ideally suited to different vascular regions. In this work, we present a case study in performance portability that assesses (1) the ease of porting an MPI application optimized for one specific architecture to new platforms using variants of hybrid MPI＋X programming models; (2) performance portability seen when simulating blood flow in three different vascular regions on diverse heterogeneous architectures; (3) model-based performance prediction for future architectures; and (4) performance scaling of the hybrid MPI＋X programming on parallel heterogeneous systems. We discuss the lessons learned in porting HARVEY, a massively parallel CFD application, from traditional multicore CPUs to diverse heterogeneous architectures ranging from NVIDIA/AMD GPUs to Intel MICs and Altera FPGAs. Patient-specific hemodynamic simulations have the potential to greatly improve both the diagnosis and treatment of a variety of vascular diseases. Portability will enable wider adoption of computational fluid dynamics (CFD) applications in the biomedical research community and targeting to platforms ideally suited to different vascular regions. In this work, we present a case study in performance portability that assesses (1) the ease of porting an MPI application optimized for one specific architecture to new platforms using variants of hybrid MPI＋X programming models; (2) performance portability seen when simulating blood flow in three different vascular regions on diverse heterogeneous architectures; (3) model-based performance prediction for future architectures; and (4) performance scaling of the hybrid MPI＋X programming on parallel heterogeneous systems. We discuss the lessons learned in porting HARVEY, a massively parallel CFD application, from traditional multicore CPUs to diverse heterogeneous architectures ranging from NVIDIA/AMD GPUs to Intel MICs and Altera FPGAs. Computational fluid dynamics Elsevier Performance prediction Elsevier OpenACC Elsevier Lattice Boltzmann method Elsevier Patient-specific hemodynamics Elsevier Heterogeneous architectures Elsevier Performance portability Elsevier Gounley, John oth Randles, Amanda oth Vetter, Jeffrey S. oth Enthalten in Elsevier Al Asaadi, Zahra ELSEVIER 25. Functional Outcomes Following Orbital Preservation in Patients with Surgical management of Sinonasal Tumours 2022 Amsterdam [u.a.] (DE-627)ELV008974187 volume:129 year:2019 pages:1-13 extent:13 https://doi.org/10.1016/j.jpdc.2019.02.005 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.96 Zahnmedizin VZ AR 129 2019 1-13 13 |
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performance portability study for massively parallel computational fluid dynamics application on scalable heterogeneous architectures |
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Performance portability study for massively parallel computational fluid dynamics application on scalable heterogeneous architectures |
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Patient-specific hemodynamic simulations have the potential to greatly improve both the diagnosis and treatment of a variety of vascular diseases. Portability will enable wider adoption of computational fluid dynamics (CFD) applications in the biomedical research community and targeting to platforms ideally suited to different vascular regions. In this work, we present a case study in performance portability that assesses (1) the ease of porting an MPI application optimized for one specific architecture to new platforms using variants of hybrid MPI＋X programming models; (2) performance portability seen when simulating blood flow in three different vascular regions on diverse heterogeneous architectures; (3) model-based performance prediction for future architectures; and (4) performance scaling of the hybrid MPI＋X programming on parallel heterogeneous systems. We discuss the lessons learned in porting HARVEY, a massively parallel CFD application, from traditional multicore CPUs to diverse heterogeneous architectures ranging from NVIDIA/AMD GPUs to Intel MICs and Altera FPGAs. |
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Patient-specific hemodynamic simulations have the potential to greatly improve both the diagnosis and treatment of a variety of vascular diseases. Portability will enable wider adoption of computational fluid dynamics (CFD) applications in the biomedical research community and targeting to platforms ideally suited to different vascular regions. In this work, we present a case study in performance portability that assesses (1) the ease of porting an MPI application optimized for one specific architecture to new platforms using variants of hybrid MPI＋X programming models; (2) performance portability seen when simulating blood flow in three different vascular regions on diverse heterogeneous architectures; (3) model-based performance prediction for future architectures; and (4) performance scaling of the hybrid MPI＋X programming on parallel heterogeneous systems. We discuss the lessons learned in porting HARVEY, a massively parallel CFD application, from traditional multicore CPUs to diverse heterogeneous architectures ranging from NVIDIA/AMD GPUs to Intel MICs and Altera FPGAs. |
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Patient-specific hemodynamic simulations have the potential to greatly improve both the diagnosis and treatment of a variety of vascular diseases. Portability will enable wider adoption of computational fluid dynamics (CFD) applications in the biomedical research community and targeting to platforms ideally suited to different vascular regions. In this work, we present a case study in performance portability that assesses (1) the ease of porting an MPI application optimized for one specific architecture to new platforms using variants of hybrid MPI＋X programming models; (2) performance portability seen when simulating blood flow in three different vascular regions on diverse heterogeneous architectures; (3) model-based performance prediction for future architectures; and (4) performance scaling of the hybrid MPI＋X programming on parallel heterogeneous systems. We discuss the lessons learned in porting HARVEY, a massively parallel CFD application, from traditional multicore CPUs to diverse heterogeneous architectures ranging from NVIDIA/AMD GPUs to Intel MICs and Altera FPGAs. |
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