Accelerator programming using directives : 6th International Workshop, WACCPD 2019, Denver, CO, USA, November 18, 2019, Revised selected papers /: 6th International Workshop, WACCPD 2019, Denver, CO, USA, November 18, 2019, Revised selected papers. (2020)

• Record Type: Book
• Other Titles: WACCPD 2019
• Further Information: Note: Sandra Wienke, Sridutt Bhalachandra (eds.).
• Other Names: Wienke, Sandra; Bhalachandra, Sridutt; WACCPD (Workshop), 6th
• Contents: Intro -- Preface -- Organization -- Contents -- Porting Scientific Applications to Heterogeneous Architectures Using Directives -- GPU Implementation of a Sophisticated Implicit Low-Order Finite Element Solver with FP21-32-64 Computation Using OpenACC -- 1 Introduction -- 2 Baseline Solver on CPU-based Computers -- 2.1 The Target Problem -- 2.2 The Solver Algorithm -- 2.3 Implementation of Solver for CPU Systems -- 3 GPU Implementation Using OpenACC -- 3.1 Baseline Implementation -- 3.2 Introduction of Lower-Precision Data Types -- 3.3 Miscellaneous Optimizations in the Solver 4 Performance Measurement -- 4.1 Performance Evaluation of FP21 Computation -- 4.2 Performance Evaluation of the Entire Solver -- 5 Conclusions -- References -- Acceleration in Acoustic Wave Propagation Modelling Using OpenACC/OpenMP and Its Hybrid for the Global Monitoring System -- 1 Introduction -- 2 Computing Environment -- 3 3D-SSFPE -- 3.1 Overview -- 3.2 Implementation -- 3.3 Performance Evaluation and Conclusion -- 4 Global Acoustic Simulation with FDM -- 4.1 Overview -- 4.2 Formulation -- 4.3 Yin-Yang Grid -- 4.4 Computational Schemes -- 4.5 Performance Optimization 4.6 Software Evaluation -- 5 Conclusion -- References -- Accelerating the Performance of Modal Aerosol Module of E3SM Using OpenACC -- 1 Introduction -- 2 OpenACC Programming Model -- 2.1 Parallelizing Loops -- 2.2 Data Transfer -- 3 Experimental Platforms and Approach -- 4 MAM Algorithms and Kernels -- 5 Offloading Computations to GPUs -- 5.1 Kernel: subgrid_mean_updraft -- 5.2 Kernel: hetfrz_classnuc_cam_calc -- 5.3 Kernel: ccncalc -- 5.4 Kernel: nsubmix -- 6 MAM Kernel Performance Discussion -- 6.1 Multi-Process Service (MPS) -- 6.2 Scaling Results -- 7 Summary and Conclusion -- References Evaluation of Directive-Based GPU Programming Models on a Block Eigensolver with Consideration of Large Sparse Matrices -- 1 Introduction -- 2 Background and Related Work -- 3 Methodology -- 3.1 The LOBPCG Algorithm -- 3.2 Baseline CPU Implementation -- 3.3 A GPU Implementation of LOBPCG -- 3.4 Tiling LOBPCG Kernels to Fit in GPU Memory Capacity -- 3.5 Hardware and Software Environment -- 3.6 Experiments -- 4 Results -- 4.1 Performance of the LOBPCG Solver -- 4.2 Performance of XTY and SpMM Kernels for Large Matrices -- 4.3 Performance of Tiled and Unified Memory Versions of SpMM -- 5 Discussion 6 Conclusions -- References -- Directive-Based Programming for Math Libraries -- Performance of the RI-MP2 Fortran Kernel of GAMESS on GPUs via Directive-Based Offloading with Math Libraries -- 1 Introduction -- 2 RI-MP2 Kernel of GAMESS -- 2.1 RI-MP2 Kernel -- 2.2 Inputs for the RI-MP2 Kernel from GAMESS -- 3 Employed Systems -- 3.1 Summit System at Oak Ridge Leadership Computing Facility -- 3.2 JLSE System at Argonne Leadership Computing Facility -- 4 Programming Environments -- 4.1 Employed Compilers -- 4.2 Math Libraries -- 5 Offloading the RI-MP2 Kernel
• Publisher Details: Cham : Springer
• Publication Date: 2020
• Extent: 1 online resource
• Subjects: 005.13; Computer programming -- Congresses; High performance computing -- Congresses; Electronic books; Electronic books
• Languages: English
• ISBNs: 9783030499433
• Related ISBNs: 303049943X; 3030499421; 9783030499426
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