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Shrirang Abhyankar
Researcher at Argonne National Laboratory
Publications - 44
Citations - 3519
Shrirang Abhyankar is an academic researcher from Argonne National Laboratory. The author has contributed to research in topics: Electric power system & Computer science. The author has an hindex of 13, co-authored 36 publications receiving 3200 citations. Previous affiliations of Shrirang Abhyankar include Illinois Institute of Technology & Pacific Northwest National Laboratory.
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PETSc Users Manual
Satish Balay,Shrirang Abhyankar,Mark F. Adams,Jed Brown,Peter R. Brune,Kristopher R. Buschelman,Lisandro Dalcin,Alp Dener,Eijkhout,William Gropp,Dmitry Karpeyev,Dinesh K. Kaushik,Matthew G. Knepley,Dave A. May,L. Curfman McInnes,Richard T. Mills,Todd Munson,Karl Rupp,Patrick Sanan,Barry Smith,Stefano Zampini,Hong Zhang +21 more
TL;DR: The Portable, Extensible Toolkit for Scientific Computation (PETSc), is a suite of data structures and routines for the scalable (parallel) solution of scientific applications modeled by partial differential equations that supports MPI, and GPUs through CUDA or OpenCL, as well as hybrid MPI-GPU parallelism.
ReportDOI
PETSc Users Manual Revision 3.7
Satish Balay,Shrirang Abhyankar,Mark F. Adams,Peter R. Brune,Kristopher R. Buschelman,Lisandro Dalcin,W. Gropp,Barry Smith,Dmitry Karpeyev,Dinesh K. Kaushik,L. Curfman McInnes,Karl Rupp,Hong Zhang,Stefano Zampini +13 more
TL;DR: This manual describes the use of PETSc for the numerical solution of partial differential equations and related problems on high-performance computers.
Posted Content
PETSc/TS: A Modern Scalable ODE/DAE Solver Library
TL;DR: This work implemented a new general-purpose, extensive, extensible library for solving ODEs and differential algebraic equations (DAEs), which includes support for both forward and adjoint sensitivities.
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Solution techniques for transient stability-constrained optimal power flow – Part II
TL;DR: This study presents the TSC-OPF formulation and discusses various dynamic optimisation-based approaches and two optimisation techniques, full-space and reduced-space method, are presented for solving the resulting non-linear optimisation problem.
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Interfacing Issues in Multiagent Simulation for Smart Grid Applications
Xiaoyu Wang,Peng Zhang,Zhuo-di Wang,Venkata Dinavahi,Gary W. Chang,J. A. Martinez,Ali Davoudi,Ali Mehrizi-Sani,Shrirang Abhyankar +8 more
TL;DR: This paper discusses design and application of the multiagent simulation technology aiming to meet smart grid requirements and addresses the interface issues including synchronization and data distribution for multiagent co-simulation.