Careers | Phone Book | A - Z Index

Oguz Selvitopi

Oguz Selvitopi
Research Scientist
Computer Science
Lawrence Berkeley National Laboratory
1 Cyclotron Road
059-4024B, MS 59R4104
Berkeley, CA 94720

Oguz Selvitopi is Research Scientist in the Performance and Algorithms group of Computer Science Department at Lawrence Berkeley National Laboratory. His research interests are high performance computing, parallel sparse matrix computations, combinatorial scientific computing, and bioinformatics. Oguz received his Ph.D. in computer engineering from Bilkent University, Turkey in 2016.

Journal Articles

Katherine Yelick, Aydın Buluç, Muaaz Awan, Ariful Azad, Benjamin Brock, Rob Egan, Saliya Ekanayake, Marquita Ellis, Evangelos Georganas, Giulia Guidi, Steven Hofmeyr, Oguz Selvitopi, Cristina Teodoropol, Leonid Oliker, "The parallelism motifs of genomic data analysis", Philosophical Transactions of The Royal Society A: Mathematical, Physical and Engineering Sciences, 2020,

R. Oguz Selvitopi, Gunduz Vehbi Demirci, Ata Turk, Cevdet Aykanat, "Locality-aware and load-balanced static task scheduling for MapReduce", Future Generation Computer Systems (FGCS), January 2019, 90:49-61, doi:

Seher Acer, R. Oguz Selvitopi, Cevdet Aykanat, "Optimizing nonzero-based sparse matrix partitioning models via reducing latency", Journal of Parallel and Distributed Computing (JPDC), December 2018, 122:145-158, doi:

Kadir Akbudak, R. Oguz Selvitopi, Cevdet Aykanat, "Partitioning Models for Scaling Parallel Sparse Matrix-Matrix Multiplication", ACM Transactions on Parallel Computing (TOPC), April 2018, 4, 3, doi: 10.1145/3155292

R. Oguz Selvitopi, Seher Acer, Cevdet Aykanat, "A Recursive Hypergraph Bipartitioning Framework for Reducing Bandwidth and Latency Costs Simultaneously", IEEE Transactions on Parallel and Distributed Systems (TPDS), February 2017, 28, 2:345-358, doi: 10.1109/TPDS.2016.2577024

Seher Acer, R. Oguz Selvitopi, Cevdet Aykanat, "Improving performance of sparse matrix dense matrix multiplication on large-scale parallel systems", Journal of Parallel Computing (PARCO), November 2016, 59:71-96, doi: 10.1016/j.parco.2016.10.001

R. Oguz Selvitopi, Cevdet Aykanat, "Reducing latency cost in 2D sparse matrix partitioning models", Journal of Parallel Computing (PARCO), September 2016, 57:1-24, doi: 10.1016/j.parco.2016.04.004

R. Oguz Selvitopi, Muhammet Mustafa Ozdal, Cevdet Aykanat, "A Novel Method for Scaling Iterative Solvers: Avoiding Latency Overhead of Parallel Sparse-Matrix Vector Multiplies", IEEE Transactions on Parallel and Distributed Systems (TPDS), March 2015, 26, 3:632-645, doi: 10.1109/TPDS.2014.2311804

Ata Turk, R. Oguz Selvitopi, Hakan Ferhatosmanoglu, Cevdet Aykanat, "Temporal Workload-Aware Replicated Partitioning for Social Networks", IEEE Transactions on Knowledge and Data Engineering (TKDE), November 2014, 26, 11:2832-2845, doi: 10.1109/TKDE.2014.2302291

R. Oguz Selvitopi, Ata Turk, Cevdet Aykanat, "Replicated partitioning for undirected hypergraphs", Journal of Parallel and Distributed Computing (JPDC), April 2012, 72:547-563, doi: 10.1016/j.jpdc.2012.01.004

Conference Papers

Giulia Guidi, Oguz Selvitopi, Marquita Ellis, Leonid Oliker, Katherine Yelick, Aydin Buluc, "Parallel String Graph Construction and Transitive Reduction for De Novo Genome Assembly", Proceedings of the IPDPS, 2021., October 20, 2020,

Oguz Selvitopi*, Saliya Ekanayake*, Giulia Guidi, Georgios Pavlopoulos, Ariful Azad, Aydın Buluç, "Distributed Many-to-Many Protein Sequence Alignment Using Sparse Matrices", Proceedings of the International Conference for High Performance Computing, Networking, Storage, and Analysis (SC’20)., 2020,

(*:joint first authors)

Seher Acer, R. Oguz Selvitopi, Cevdet Aykanat, "Addressing Volume and Latency Overheads in 1D-parallel Sparse Matrix-Vector Multiplication", European Conference on Parallel Processing (Euro-Par), Springer, August 2017, 625-637, doi: 10.1007/978-3-319-64203-1_45

Book Chapters

R. Oguz Selvitopi, Kadir Akbudak, Cevdet Aykanat, "Parallelization of Sparse Matrix Kernels for Big Data Applications", Resource Management for Big Data Platforms, edited by Pop F., Kołodziej J., Di Martino B. , (Springer: October 2016) Pages: 367-382 doi: 10.1007/978-3-319-44881-7_17