2008 |
12 | EE | Peter Gottschling,
Andrew Lumsdaine:
Integrating semantics and compilation: using c++ concepts to develop robust and efficient reusable libraries.
GPCE 2008: 67-76 |
11 | EE | Torsten Hoefler,
Peter Gottschling,
Andrew Lumsdaine:
Leveraging non-blocking collective communication in high-performance applications.
SPAA 2008: 113-115 |
2007 |
10 | EE | Peter Gottschling,
David S. Wise,
Michael D. Adams:
Representation-transparent matrix algorithms with scalable performance.
ICS 2007: 116-125 |
9 | EE | Torsten Hoefler,
Peter Gottschling,
Andrew Lumsdaine,
Wolfgang Rehm:
Optimizing a conjugate gradient solver with non-blocking collective operations.
Parallel Computing 33(9): 624-633 (2007) |
2006 |
8 | EE | A. Breuer,
Peter Gottschling,
Douglas Gregor,
Andrew Lumsdaine:
Effecting parallel graph eigensolvers through library composition.
IPDPS 2006 |
7 | EE | Torsten Hoefler,
Peter Gottschling,
Wolfgang Rehm,
Andrew Lumsdaine:
Optimizing a Conjugate Gradient Solver with Non-Blocking Collective Operations.
PVM/MPI 2006: 374-382 |
2003 |
6 | EE | Andreas Alexander Albrecht,
Peter Gottschling,
Uwe Naumann:
Markowitz-Type Heuristics for Computing Jacobian Matrices Efficiently.
International Conference on Computational Science 2003: 575-584 |
5 | EE | Uwe Naumann,
Peter Gottschling:
Simulated Annealing for Optimal Pivot Selection in Jacobian Accumulation.
SAGA 2003: 83-97 |
2001 |
4 | EE | Jens Gerlach,
Peter Gottschling,
Uwe Der:
A Generic C++ Framework for Parallel Mesh-Based Scientific Applications.
HIPS 2001: 45-54 |
3 | | Jens Gerlach,
Peter Gottschling:
A Generic C++ Framework for Parallel Mesh Based Scientific Applications.
IPDPS 2001: 103 |
2 | EE | Uwe Naumann,
Peter Gottschling:
Prospects for Simulated Annealing Algorithms in Automatic Differentiation.
SAGA 2001: 131-144 |
2000 |
1 | EE | Peter Gottschling,
Wolfgang E. Nagel:
An Efficient Parallel Linear Solver with a Cascadic Conjugate Gradient Method: Experience with Reality.
Euro-Par 2000: 784-794 |