Pdf High Performance Reverse Time Migration On Gpu

Reverse Time Migration Pdf Reflection Seismology Computing In this work we map a pde fd algorithm called reverse time migration to a gpu using cuda. this seismic imaging (geophysics) algorithm is widely used in the oil industry. gpus are natural. In this work we map a pde fd algorithm called reverse time migration to a gpu using cuda. this seismic imaging (geophysics) algorithm is widely used in the oil industry. gpus are natural contenders in the aftermath of the clock race, in particular for high performance computing (hpc).

Reverse Time Migration Pdf Reflection Physics Scattering In this work we map a pde fd algorithm called reverse time migration to a gpu using cuda. this seismic imaging (geophysics) algorithm is widely used in the oil industry. gpus are natural contenders in the aftermath of the clock race, in particular for high performance computing (hpc). In this work we map a pde fd algorithm called reverse time migration to a gpu using cuda. this seismic imaging (geophysics) algorithm is widely used in the oil industry. gpus are natural contenders in the aftermath of the clock race, in particular for high performance computing (hpc). In this report, i outline the implementation and preliminary benchmarking of a parallelized program to perform reverse time migration (rtm) seismic imag ing using the nvidia cuda platform for scientific computing, accelerated by a general purpose graphics processing unit (gpgpu). We test the rtm implementation on the 3 d hpc4e seismic test suite. the numerical experiments show that the openacc mpi 3 d rtm, which implements the wavefield reconstruction, presents the best execu tion times and hard disk demands.

Pdf High Performance Reverse Time Migration On Gpu In this report, i outline the implementation and preliminary benchmarking of a parallelized program to perform reverse time migration (rtm) seismic imag ing using the nvidia cuda platform for scientific computing, accelerated by a general purpose graphics processing unit (gpgpu). We test the rtm implementation on the 3 d hpc4e seismic test suite. the numerical experiments show that the openacc mpi 3 d rtm, which implements the wavefield reconstruction, presents the best execu tion times and hard disk demands. We present a computational strategy for reverse time migration (rtm) with accelerator aided clusters. a new imaging condition computed from the pressure and velocity elds is introduced. A gpu based tti reverse time migration program is written. the program uses gpu for compute intensive wavefield modeling while the cpu takes care of snapshot i o to and from disk and imaging. To our knowledge, this paper highlights for the first time the applicability of asynchronous executions with temporal blocking throughout the whole rtm on heterogeneous architectures. The execution time of the algorithm on one gpu is always faster compared to the execution time on one cpu core, even when the fields are transferred from and to the hard disk.

Figure 1 From High Performance Reverse Time Migration On Gpu Semantic We present a computational strategy for reverse time migration (rtm) with accelerator aided clusters. a new imaging condition computed from the pressure and velocity elds is introduced. A gpu based tti reverse time migration program is written. the program uses gpu for compute intensive wavefield modeling while the cpu takes care of snapshot i o to and from disk and imaging. To our knowledge, this paper highlights for the first time the applicability of asynchronous executions with temporal blocking throughout the whole rtm on heterogeneous architectures. The execution time of the algorithm on one gpu is always faster compared to the execution time on one cpu core, even when the fields are transferred from and to the hard disk.

Pdf Industrial Scale Reverse Time Migration On Gpu Hardware To our knowledge, this paper highlights for the first time the applicability of asynchronous executions with temporal blocking throughout the whole rtm on heterogeneous architectures. The execution time of the algorithm on one gpu is always faster compared to the execution time on one cpu core, even when the fields are transferred from and to the hard disk.