Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review
High-performance computing on GPUs for resistivity logging of oil and gas wells. / Glinskikh, V.; Dudaev, A.; Nechaev, O. et al.
Application of Mathematics in Technical and Natural Sciences: 9th International Conference for Promoting the Application of Mathematics in Technical and Natural Sciences, AMiTaNS 2017. ed. / MD Todorov. Vol. 1895 American Institute of Physics Inc., 2017. 120005 (AIP Conference Proceedings; Vol. 1895).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review
}
TY - GEN
T1 - High-performance computing on GPUs for resistivity logging of oil and gas wells
AU - Glinskikh, V.
AU - Dudaev, A.
AU - Nechaev, O.
AU - Surodina, I.
PY - 2017/10/12
Y1 - 2017/10/12
N2 - We developed and implemented into software an algorithm for high-performance simulation of electrical logs from oil and gas wells using high-performance heterogeneous computing. The numerical solution of the 2D forward problem is based on the finite-element method and the Cholesky decomposition for solving a system of linear algebraic equations (SLAE). Software implementations of the algorithm used the NVIDIA CUDA technology and computing libraries are made, allowing us to perform decomposition of SLAE and find its solution on central processor unit (CPU) and graphics processor unit (GPU). The calculation time is analyzed depending on the matrix size and number of its non-zero elements. We estimated the computing speed on CPU and GPU, including high-performance heterogeneous CPU-GPU computing. Using the developed algorithm, we simulated resistivity data in realistic models.
AB - We developed and implemented into software an algorithm for high-performance simulation of electrical logs from oil and gas wells using high-performance heterogeneous computing. The numerical solution of the 2D forward problem is based on the finite-element method and the Cholesky decomposition for solving a system of linear algebraic equations (SLAE). Software implementations of the algorithm used the NVIDIA CUDA technology and computing libraries are made, allowing us to perform decomposition of SLAE and find its solution on central processor unit (CPU) and graphics processor unit (GPU). The calculation time is analyzed depending on the matrix size and number of its non-zero elements. We estimated the computing speed on CPU and GPU, including high-performance heterogeneous CPU-GPU computing. Using the developed algorithm, we simulated resistivity data in realistic models.
UR - http://www.scopus.com/inward/record.url?scp=85031703158&partnerID=8YFLogxK
U2 - 10.1063/1.5007422
DO - 10.1063/1.5007422
M3 - Conference contribution
AN - SCOPUS:85031703158
VL - 1895
T3 - AIP Conference Proceedings
BT - Application of Mathematics in Technical and Natural Sciences
A2 - Todorov, MD
PB - American Institute of Physics Inc.
T2 - 9th International Conference for Promoting the Application of Mathematics in Technical and Natural Sciences, AMiTaNS 2017
Y2 - 21 June 2017 through 26 June 2017
ER -
ID: 9891338