Presentations

2009
2008
2007
2006

• SIAM Conference on Computational Science and Engineering, Miami, Florida, March 2009.
  • U. Catalyurek, C. Aykanat and B. Ucar, Partitioning Sparse Matrices
  • C. Chevalier and E. Boman, Parallel Sparse Matrix Ordering with Zoltan
  • M. Halappanavar, F. Dobrian and A. Pothen, A Parallel Half-Approximation Algorithm for the Weighted Matching Problem
  • A. Gebremedhin, A. Tarafdar, D. Nguyen and A. Pothen, ColPack: A Graph Coloring Package for Sparse Derivative Computation
  • J. Utke, Automatic Differentiation via Source Transformation


• Dagstuhl Seminar on CSC , Germany, Feb 2009.
  • B. Hendrickson, Combinatorial Scientific Computing: A View to the Future (Plenary talk)
  • A. Pothen, Matching in Scientific Computing (Plenary talk)
  • P. Hovland, Combinatorial Problems in Automatic Differentiation (Plenary talk)
  • E. Boman, Zoltan - A Parallel Toolkit for Partitioning, Ordering, and Coloring (Tutorial)
  • J. Utke, Automatic Differentiation with OpenAD and Combinatorial Problems (Tutorial)
  • A. Gebremedhin, The Enabling Power of Graph Coloring Algorithms in Automatic Differentiation (Contributed talk)
  • A. Lyons and I. Safro, Randomized Heuristics for Exploiting Jacobian Scarcity (Contributed talk)
  • D. Bozdag and U. Catalyurek, Parallel Short Sequence Mapping for High Throughput Genome Sequencing (Contributed talk)
  • C. Chevalier and I. Safro, Weighted Aggregation for Multilevel Graph Partitioning (Poster; Extended abstract)

• The 5th International Conference on Automatic Differentiation, Bonn, Germany, Aug 11-15 2008.
  
  • A. Pothen, Automatic Differentiation and Combinatorics: An Accidental Partnership? (invited talk)
    
  • A. Walther, A.H. Gebremedhin, A. Pothen, Exploiting Sparsity in Jacobian Computation via Coloring and Automatic Differentiation: A Case Study in a Simulated Moving Bed Process
    
  • Charpentier, J. Utke, Dal Cappello, Efficient Higher-Order Derivatives of the Hypergeometric Function
    
  • A. Lyons, J. Utke, On the Practical Exploitation of Scarsity
    
  • P. Hovland, Design and Implementation of a Context-Sensitive, Flow-Sensitive Activity Analysis Algorithm for Automatic Differentiation
    
  • P. Hovland, Abdel-Khalik, A. Lyons, Stover, J. Utke, A Low Rank Approach to Automatic Differentiation
    


• SciDAC 2008 Conference, Seattle, WA, July 2008.
  • CSCAPES Team, Combinatorial Scientifc Computing and Petascale Simulations Institute (CSCAPES): Recent Progress . (Poster)
    


• SIAM Conference on Discrete Mathematics, Minisymposium on CSC, Burlington, VT, June 2008.
  • A. Pothen, Approximation Algorithms for Vertex Weighted Matching
    
  • E. Boman, Graph and hypergraph models and algorithms for sparse matrix-vector multiplication
    


• CSCAPES Workshop 2008, Santa Fe, NM, Jun 10-13, 2008.
  • E. Boman, Load-balancing, Partitioning, Ordering
    
  • U. Catalyurek, Repartitioning and Matrix Partitioning
    
  • A. Gebremedhin, Graph Coloring in Parallel Processing and Scientific Computing
    
  • P. Hovland, Automatic Differentiation
    
  • K. Devine, Dynamic Load Balancing Needs of Parallel Adaptive Analysis
    
  • F. Dobrian, Parallel Approximate Matching
    
  • M. Wolf, Optimizing Parallel Sparse Matrix-Vector Multiplication by Partitioning
    
  • D. Bozdag, Parallel Distance-2 Coloring
    
  • K. Devine and C. Chevalier, Tutorial: The Zoltan Toolkit
  • P. Hovland, Tutorial: Automatic Differentiation


• SIAM Conference on Optimization, Minisymposium on Graph Coloring for Sparse Derivative Computation, Boston, MA, May 2008.
  • A. Gebremedhin, Novel Acyclic and Star Coloring Algorithms and Their Application to Effcient Sparse Hessian Computation via Automatic Differentiation


• SIAM Conference on Parallel Processing for Scientific Computing, Minisymposium on Parallel CSC, Atlanta, GA, March 2008.
  • A. Gebremedhin, A Scalable Algorithmic Framework for Parallel Graph Coloring on Distributed Memory Computers

• Invited talk, North Carolina State University, September 2007.
  • Paul Hovland, Automatic Differentiation: Tools & Applications


• CSC Minisymposium at the 6th International Congress on Industrial and Applied Mathematics (ICIAM?07), Zurich, Switzerland, July 2007.
  • F. Dobrian, Matching algorithms in scientific computing
    
  • P. Hovland, Hierarchical coloring
    
  • P. Hovland, The OpenAD project: ADIC 2.0 and OpenAD/F
    
  • A. Pothen, Computing Hessians without tears: automatic differentiation and graph coloring
    
  • E. Boman, Combinatorial models and algorithms for parallel sparse matrix distributions
    
  • U. V. Catalyurek, Hypergraph-based Dynamic Load Balancing for Adaptive Scientific Computations
    


• SciDAC 2007 Conference, Boston, MA, June 2007.
  • K. Devine, Partitioning and Dynamic Load Balancing for Petascale Applications
    
  • A. Pothen, Enabling Petascale Computational Science through Combinatorial Algorithms
    
  • E. Boman and K. Devine, Tutorial: Partitioning, Load Balancing and the Zoltan Toolkit
  • P. Hovland and A. Gebremedhin, Computing Jacobians and Hessians for Nonlinear PDEs (Poster)
    


• Third SIAM Workshop on Combinatorial Scientific Computing, Costa Mesa, CA, Feb 2007.
  • E. Boman and U. Catalyurek, Fine-grain parallel sparse matrix distribution
  • C. Chevalier and F. Pellegrini, The PT-Scotch project
  • M. Strout , Hypergraphs for run-time reordering
  • I. Karlin and J. Utke, Local Jacobian pre-accumulation
  • A.H. Gebremedhin, A. Pothen, A. Tarafdar, F. Manne and A. Walther, Sparse Hessian computation using Automatic Differentiation


• SIAM Conference on Computational Science and Engineering, Costa Mesa, CA, Feb 2007.
  • A. Pothen and A. Gebremedhin, Graph Coloring Problems for Computing Derivatives: Recent Developments and Future Plans
  • The CSCAPES team, Combinatorial Scientific Computing and Petascale Simulations: A SciDAC Applied Math Institute. (Poster)

• DOE PI Meeting, October 2006.
  • CSCAPES Presentation, Seven powerpoint slides prepared for DOE.


• SciDAC 2006 Conference, Denver, CO, June 2006.
  • Combinatorial Algorithms Enabling Computational Science: Tales from the Front. (Poster)