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Peter Gottschling
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2020 – today
- 2020
- [i2]E. Theodore L. Omtzigt, Peter Gottschling, Mark Seligman, William Zorn:
Universal Numbers Library: design and implementation of a high-performance reproducible number systems library. CoRR abs/2012.11011 (2020)
2010 – 2019
- 2013
- [j3]Denis Demidov
, Karsten Ahnert, Karl Rupp
Programming CUDA and OpenCL: A Case Study Using Modern C++ Libraries. SIAM J. Sci. Comput. 35(5) (2013) - 2012
- [c13]Peter Gottschling, Torsten Hoefler:
Productive Parallel Linear Algebra Programming with Unstructured Topology Adaption. CCGRID 2012: 9-16 - [i1]Denis Demidov, Karsten Ahnert, Karl Rupp, Peter Gottschling:
Programming CUDA and OpenCL: A Case Study Using Modern C++ Libraries. CoRR abs/1212.6326 (2012)
2000 – 2009
- 2009
- [j2]Peter Gottschling, David S. Wise, Adwait Joshi:
Generic support of algorithmic and structural recursion for scientific computing. Int. J. Parallel Emergent Distributed Syst. 24(6): 479-503 (2009) - 2008
- [c12]Peter Gottschling, Andrew Lumsdaine
Integrating semantics and compilation: using c++ concepts to develop robust and efficient reusable libraries. GPCE 2008: 67-76 - [c11]Torsten Hoefler, Peter Gottschling, Andrew Lumsdaine:
Leveraging non-blocking collective communication in high-performance applications. SPAA 2008: 113-115 - 2007
- [j1]Torsten Hoefler, Peter Gottschling, Andrew Lumsdaine
Optimizing a conjugate gradient solver with non-blocking collective operations. Parallel Comput. 33(9): 624-633 (2007) - [c10]Peter Gottschling, David S. Wise, Michael D. Adams:
Representation-transparent matrix algorithms with scalable performance. ICS 2007: 116-125 - 2006
- [c9]Alex Breuer, Peter Gottschling, Douglas P. Gregor, Andrew Lumsdaine
Effecting parallel graph eigensolvers through library composition. IPDPS 2006 - [c8]Torsten Hoefler, Peter Gottschling, Wolfgang Rehm, Andrew Lumsdaine
Optimizing a Conjugate Gradient Solver with Non-Blocking Collective Operations. PVM/MPI 2006: 374-382 - 2003
- [c7]Andreas Alexander Albrecht, Peter Gottschling, Uwe Naumann:
Markowitz-Type Heuristics for Computing Jacobian Matrices Efficiently. International Conference on Computational Science 2003: 575-584 - [c6]Uwe Naumann, Peter Gottschling:
Simulated Annealing for Optimal Pivot Selection in Jacobian Accumulation. SAGA 2003: 83-97 - 2001
- [c5]Jens Gerlach, Peter Gottschling, Uwe Der:
A Generic C++ Framework for Parallel Mesh-Based Scientific Applications. HIPS 2001: 45-54 - [c4]Jens Gerlach, Peter Gottschling:
A Generic C++ Framework for Parallel Mesh Based Scientific Applications. IPDPS 2001: 103 - [c3]Uwe Naumann, Peter Gottschling:
Prospects for Simulated Annealing Algorithms in Automatic Differentiation. SAGA 2001: 131-144 - 2000
- [c2]Peter Gottschling, Wolfgang E. Nagel:
An Efficient Parallel Linear Solver with a Cascadic Conjugate Gradient Method: Experience with Reality. Euro-Par 2000: 784-794
1990 – 1999
- 1999
- [c1]Rolf Rabenseifner, Peter Gottschling, Wolfgang E. Nagel, Stephan Seidl:
Effective performance problem detection of MPI programs on MPP systems: From the global view to the details. PARCO 1999: 647-655
Coauthor Index
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