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- Ümit V. Çatalyürek, Cevdet Aykanat
- IEEE Trans. Parallel Distrib. Syst.
- 1999

ÐIn this work, we show that the standard graph-partitioning-based decomposition of sparse matrices does not reflect the actual communication volume requirement for parallel matrix-vector multiplication. We propose two computational hypergraph models which avoid this crucial deficiency of the graph model. The proposed models reduce the decomposition problem… (More)

- Doruk Bozdag, Ümit V. Çatalyürek, Füsun Özgüner
- Proceedings 20th IEEE International Parallel…
- 2006

We propose a new duplication-based DAG scheduling algorithm for heterogeneous computing environments. Contrary to the traditional approaches, proposed algorithm traverses the DAG in a bottom-up fashion while taking advantage of task duplication and task insertion. Experimental results on random DAGs and three different application DAGs show that the… (More)

Many emerging large-scale data science applications require searching large graphs distributed across multiple memories and processors. This paper presents a distributed breadth-first search (BFS) scheme that scales for random graphs with up to three billion vertices and 30 billion edges. Scalability was tested on IBM BlueGene/L with 32,768 nodes at the… (More)

- Karen D. Devine, Erik G. Boman, Robert T. Heaphy, Rob H. Bisseling, Ümit V. Çatalyürek
- Proceedings 20th IEEE International Parallel…
- 2006

Graph partitioning is often used for load balancing in parallel computing, but it is known that hypergraph partitioning has several advantages. First, hypergraphs more accurately model communication volume, and second, they are more expressive and can better represent nonsymmetric problems. Hypergraph partitioning is particularly suited to parallel sparse… (More)

- Ümit V. Çatalyürek, Erik G. Boman, Karen D. Devine, Doruk Bozdag, Robert T. Heaphy, Lee Ann Riesen
- J. Parallel Distrib. Comput.
- 2009

In parallel adaptive applications, the computational structure of the applications changes over time, leading to load imbalances even though the initial load distributions were balanced. To restore balance and to keep communication volume low in further iterations of the applications, dynamic load balancing (repartitioning) of the changed computational… (More)

A k-core of a graph is a maximal connected subgraph in which every vertex is connected to at least k vertices in the subgraph. k-core decomposition is often used in large-scale network analysis, such as community detection, protein function prediction, visualization, and solving NP-Hard problems on real networks efficiently, like maximal clique finding. In… (More)

- Olcay Sertel, Jun Kong, Gerard Lozanski, Arwa Shanaah, Ümit V. Çatalyürek, Joel H. Saltz +1 other
- 2008 IEEE International Conference on Acoustics…
- 2008

In this paper, a novel color texture classification approach is introduced and applied to computer-assisted grading of follicular lymphoma from whole-slide tissue samples. The digitized tissue samples of follicular lymphoma were classified into histological grades under a statistical framework. The proposed method classifies the image either into low or… (More)

- Cevdet Aykanat, Ali Pinar, Ümit V. Çatalyürek
- SIAM J. Scientific Computing
- 2004

We investigate the problem of permuting a sparse rectangular matrix into block-diagonal form. Block-diagonal form of a matrix grants an inherent parallelism for solving the deriving problem, as recently investigated in the context of mathematical programming, LU factorization, and QR factorization. To represent the nonzero structure of a matrix, we propose… (More)

- Olcay Sertel, Jun Kong, Ümit V. Çatalyürek, Gerard Lozanski, Joel H. Saltz, Metin Nafi Gürcan
- Signal Processing Systems
- 2009

- Olcay Sertel, Jun Kong, Hiroyuki Shimada, Ümit V. Çatalyürek, Joel H. Saltz, Metin Nafi Gürcan
- Pattern Recognition
- 2009

We are developing a computer-aided prognosis system for neuroblastoma (NB), a cancer of the nervous system and one of the most malignant tumors affecting children. Histopathological examination is an important stage for further treatment planning in routine clinical diagnosis of NB. According to the International Neuroblastoma Pathology Classification (the… (More)