Zobrazeno 1 - 10
of 11
pro vyhledávání: '"Suha N. Kayum"'
Autor:
Ghada Sindi, V. Etienne, Hussain Salim, Suha N. Kayum, Thierry Tonellot, Ali Momin, Maxim Dmitriev
Publikováno v:
First Break. 38:97-100
GeoDRIVE, a high performance computing (HPC) software framework tailored to massive seismic applications and super-computers is presented. The paper discusses the flexibility and modularity of the application along with optimized HPC features. GeoDRI
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e8659600a3c056a780745dfcee6dbf44
https://doi.org/10.3997/1365-2397.fb2020015
https://doi.org/10.3997/1365-2397.fb2020015
Publikováno v:
HPEC
An increase in the acquisition of seismic data volumes has resulted in applications processing seismic data running for weeks or months on large supercomputers. A fault occurring during processing would jeopardize the fidelity and quality of the resu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::69662aa3d85df7867f86c3bee67806ab
https://doi.org/10.1109/hpec43674.2020.9286143
https://doi.org/10.1109/hpec43674.2020.9286143
Autor:
Marcin Rogowski, Suha N. Kayum
Publikováno v:
EAGE 2020 Annual Conference & Exhibition Online.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c848af8d446dc4d94136afb1e9a4331a
https://doi.org/10.3997/2214-4609.202011938
https://doi.org/10.3997/2214-4609.202011938
Autor:
Suha N. Kayum, Marcin Rogowski
Publikováno v:
EAGE 2020 Annual Conference & Exhibition Online.
Summary Load balancing poses a challenge to massively parallel reservoir simulation. Inefficient work distribution impedes scalability and leads to inefficient use of computing resources. Rather than addressing the more popular - and admittedly more
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4bd872955dfe2e85c116cdb9788fc4bc
https://doi.org/10.3997/2214-4609.202011935
https://doi.org/10.3997/2214-4609.202011935
Autor:
Suha N. Kayum, Marcin Rogowski
Publikováno v:
Day 2 Tue, November 12, 2019.
Reservoir simulation models that represent large-sized reservoirs require significant use of High-Performance Computing resources. Several solutions aim to reduce the load of an individual simulation such as upscaling to consequently reduce the numbe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::aed510aaa7897c988e9eda5641ca49f3
https://doi.org/10.2118/197972-ms
https://doi.org/10.2118/197972-ms
Autor:
Suha N. Kayum, Marcin Rogowski
Publikováno v:
HPEC
Over the past few decades, the oil and gas (O&G) industry has become heavily dependent on parallel scientific computing. The turnaround time of such applications depends heavily on the amount of resources dedicated to the task. Increasing the number
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::31d9c91005153ea83da2a0c7860b2bc7
https://doi.org/10.1109/hpec.2019.8916420
https://doi.org/10.1109/hpec.2019.8916420
Autor:
Suha N. Kayum, Marcin Rogowski
Publikováno v:
HPEC
Load balancing is a crucial factor affecting the performance of parallel applications. Improper work distribution leads to underutilization of computing resources and an unnecessary increase in runtime. This paper identifies the imbalance sources in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e295559d8397af41bdc02338f41eef73
https://doi.org/10.1109/hpec.2019.8916495
https://doi.org/10.1109/hpec.2019.8916495
Publikováno v:
HPEC
In parallel reservoir simulation, massively sized files are written recurrently throughout a simulation run. A method is developed to compress the distributed data to be written during the simulation run and to output it to a single compressed file.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3d1f03f6b52023702d73409ff2d4d8cb
https://doi.org/10.1109/hpec.2019.8916298
https://doi.org/10.1109/hpec.2019.8916298
Publikováno v:
Day 4 Thu, June 06, 2019.
Algebraic Multigrid (AMG) methods have proven to be efficient when numerically solving elliptic Partial Differential Equations (PDE). In reservoir simulation, AMG is used together with the Constrained Pressure Residual (CPR) method to solve a partial
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3bd96f16e4733c6be4fddcf9133b869e
https://doi.org/10.2118/195472-ms
https://doi.org/10.2118/195472-ms
Publikováno v:
Fourth EAGE Workshop on High Performance Computing for Upstream 2019.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::447f7e1464de719dccabe0f0bb9017e0
https://doi.org/10.3997/2214-4609.201903293
https://doi.org/10.3997/2214-4609.201903293