Publications

This page lists all publications in reverse chronological order, with the newest updates at the top. This list is also available as a BibTeX file and as a PDF, however, this web-page may contain more recent information. A subset of the list is also available on ArXiv and Google Scholar-- of the two, the former is (necessarily) incomplete whereas the latter does a pretty good job keeping up to date automatically.

Pre-prints

• Efficient handling of sparse vectors for parallel nonblocking execution in GraphBLAS

  by Aristeidis Mastoras and A. N. Yzelman; Euro-Par 2025: Parallel Processing Workshops; to appear (2025).
  
  [ Citation | Accepted version (terms of use) ]

• Faster Distributed Inference-Only Recommender Systems via Bounded Lag Synchronous Collectives

  by Kiril Dichev, F. Pawłowski, and A. N. Yzelman, arXiv: 2512.19342; pre-print (2025).
  
  [ Citation | 2025 pre-print (ArXiv, local mirror) ]

• HiCR, an Abstract Model for Distributed Heterogeneous Programming

  by Sergio Miguel Martin, Luca Terracciano, Kiril Dichev, Noah Baumann, Orestis Korakitis, Lin Jiashu, and A. N. Yzelman, arXiv: 2509.01425; extended pre-print (2025).
  
  [ Citation | 2025 extended pre-print (ArXiv, local mirror) ]

• Symmetry-breaking Symmetry in Directed Spectral Partitioning

  by Dimosthenis Pasadakis, Raphael S. Steiner, Pál András Papp, Toni Böhnlein, and A. N. Yzelman, arXiv: 2508.16173; pre-print (2025).
  
  [ Citation | 2025 pre-print (ArXiv, local mirror) ]

• Efficient Parallel Scheduling for Sparse Triangular Solvers

  by Toni Böhnlein, Pál András Papp, Raphael S. Steiner, Christos K. Matzoros, A. N. Yzelman, arXiv: 2503.05408; pre-print (2025).
  
  [ Citation | March 2025 pre-print (ArXiv, local mirror) | IPDPS '25 brief summary | June 2025 revision (ArXiv, local mirror) ]

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Publications in refereed journals

• Distributed and heterogeneous tensor-vector contraction algorithms for high performance computing

  by Pedro J. Martinez-Ferrer, A. N. Yzelman, and Vicenç Beltran in Future Generation Computer Systems, Vol. 166, ISSN 0167-739X, pp. 107698, Elsevier (2025).
  
  [ Citation | 2025 pre-print (ArXiv) | Published version (temporary free access PDF) ]

• Design and implementation for nonblocking execution in GraphBLAS: tradeoffs and performance

  by Aristeidis Mastoras, Sotiris Anagnostidis, and A. N. Yzelman, ACM Transactions on Architecture and Code Optimization (TACO) 20, 1, Article 6 (March 2023).
  
  [ Citation | First revision (author's version) | Published version ]

• A native tensor-vector multiplication algorithm for high performance computing

  by Pedro J. Martinez-Ferrer, A. N. Yzelman, and Vicenç Beltran in IEEE Transactions on Parallel and Distributed Systems, 33(12), pp. 3363-3374, IEEE (2022).
  
  [ Citation | Published version ]

• A multi-dimensional Morton-ordered block storage for mode-oblivious tensor computations

  by F. Pawłowski, B. Uçar, and A. N. Yzelman in Journal of Computational Science 33, pp. 34-44, Elsevier (2019).
  
  [ Citation | Pre-print | Published version ]

• MulticoreBSP for C: a high-performance library for shared-memory parallel programming

  by A. N. Yzelman, R. H. Bisseling, D. Roose, and K. Meerbergen in International Journal of Parallel Programming 42(4), pp. 619-642, Springer (2014).
  
  [ Citation | 2013 pre-print | First revision | Second revision | Published version ]

• High-Level Strategies for Parallel Shared-Memory Sparse Matrix–Vector Multiplication

  by A. N. Yzelman & D. Roose in IEEE Transactions on Parallel and Distributed Systems 25(1), pp. 116-125, IEEE (2014).
  
  [ Citation | 2012 pre-print | Published version ]

• An Object-Oriented Bulk Synchronous Parallel Library for Multicore Programming

  by A. N. Yzelman & Rob H. Bisseling in Concurrency and Computation: Practice and Experience 24(5), pp. 533-553, Wiley (2012).
  
  [ Citation | 2011 pre-print | Published version ]

• Two-dimensional cache-oblivious sparse matrix-vector multiplication

  by A. N. Yzelman & Rob H. Bisseling in Parallel Computing 37(12), pp. 806-819, Elsevier (2011).
  
  [ Citation | 2010 pre-print | 2011 revision | Published version ]

• Cache-oblivious sparse matrix-vector multiplication by using sparse matrix partitioning methods

  by A. N. Yzelman & Rob H. Bisseling in SIAM Journal of Scientific Computation 31(4), pp. 3128-3154, SIAM (2009).
  
  [ Citation | 2008 pre-print | 2009 revision | Published version ]

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Publications in refereed proceedings

• Multiprocessor Scheduling with Memory Constraints: Fundamental Properties and Finding Optimal Solutions

  by Pál András Papp, Toni Böhnlein, and A. N. Yzelman, in Proceedings of the 54th International Conference on Parallel Processing (ICPP '25). pp. 238–247, ACM (2025).
  
  [ Citation | 2025 pre-print (ArXiv, local mirror) | Published version ]

• The Impact of Partial Computations on the Red-Blue Pebble Game

  by Pál András Papp, Aleksandros Sobczyk, A. N. Yzelman, in Proceedings of the 37th Symposium on Parallelism in Algorithms and Architectures (SPAA '25). pp. 328—338, ACM (2025).
  
  [ Citation | 2025 pre-print (ArXiv, local mirror) | Published version ]

• Red-Blue Pebbling with Multiple Processors: Time, Communication, and Memory Trade-offs

  by Toni Böhnlein, Pál András Papp, A. N. Yzelman in U. Schmid, R. Kuznets (editors), Structural Information and Communication Complexity (SIROCCO 2025), Lecture Notes in Computer Science 15671, pp. 109—125, Springer (2025).
  
  [ Citation | preceding SPAA '24 brief announcement | 2024 pre-print (ArXiv, local mirror) | Accepted version | Published version ]

• DAG Scheduling in the BSP Model

  by Pál András Papp, Georg Anegg, and A. N. Yzelman, in Královič, R., Kůrková, V. (editors), Theory and Practice of Computer Science (SOFSEM 2025), Lecture Notes in Computer Science 15539, pp. 238—253, Springer (2025). Best paper award.
  
  [ Citation | 2023 pre-print (ArXiv, local mirror) | 2024 revision (ArXiv, local mirror) | Accepted version | Published version ]

• Efficient Multi-Processor Scheduling in Increasingly Realistic Models

  by Pál András Papp, Georg Anegg, Aikaterini Karanasiou, and A. N. Yzelman in Proceedings of the 36th ACM Symposium on Parallelism in Algorithms and Architectures (SPAA '24). pp. 463–474, ACM (2024).
  
  [ Citation | 2024 pre-print (arXiv, local mirror) | preceding IPDPS '24 brief summary | IPDPS '24 poster | Published version ]

• Effective implementation of the High Performance Conjugate Gradient benchmark on GraphBLAS

  by Alberto Scolari and A. N. Yzelman, 2023 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), St. Petersburg, FL, USA, 2023, pp. 216-225, IEEE (2023).
  
  [ Citation | 2023 pre-print (local mirror) | Published version ]

• Partitioning Hypergraphs is Hard: Models, Inapproximability, and Applications

  by Pál András Papp, Georg Anegg, and A. N. Yzelman, proceedings of the 35th ACM Symposium on Parallelism in Algorithms and Architectures (SPAA '23), ACM (2023).
  
  [ Citation | 2022 pre-print (ArXiv, local mirror) | 2023 revision (author's version, local mirror) | Published version ]

• Towards Structured Algebraic Programming

  by Daniele G. Spampinato, Denis Jelovina, Jiawei Zhuang, and A. N. Yzelman, Proceedings of the 9th ACM SIGPLAN International Workshop on Libraries, Languages and Compilers for Array Programming (ARRAY 2023), ACM (2023).
  
  [ Citation | First revision (author's version) | published version ]

• Studying the expressiveness and performance of parallelization abstractions for linear pipelines

  by Aristeidis Mastoras and A. N. Yzelman, 14th International Workshop on Programming Models and Applications for Multicores and Manycores (PMAM '23), February 25–March 1 2023, Montreal, QC, Canada, ACM (2023).
  
  [ Citation | First revision (author's version) | Published version ]

• Nonblocking execution in GraphBLAS

  by Aristeidis Mastoras, Sotiris Anagnostidis, and A. N. Yzelman in 2022 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), pp. 230-233, IEEE (2022).
  
  [ Citation | Accepted version | Published version ]

• Combinatorial Tiling for Sparse Neural Networks

  by F. Pawłowski, R. H. Bisseling, B. Uçar, A. N. Yzelman, 2020 IEEE High Performance Extreme Computing Conference (HPEC), Waltham, MA, United States (2020).
  
  [ Citation | 2020 pre-print | First revision | Second revision | Published version ]

• High Performance Tensor–Vector Multiplication on Shared-Memory Systems

  by F. Pawłowski, B. Uçar, A. N. Yzelman in Wyrzykowski R., Deelman E., Dongarra J., Karczewski K. (editors), Parallel Processing and Applied Mathematics, PPAM 2019, Lecture Notes in Computer Science, vol 12043, Springer (2020).
  
  [ Citation | 2019 pre-print | First revision | Published version ]

• Generalised vectorisation for sparse matrix–vector multiplication

  by A. N. Yzelman in Proceedings of the 5th Workshop on Irregular Applications: Architectures and Algorithms (IA3), article 6, pp. 1-8, ACM (2015).
  
  [ Citation | 2015 pre-print, errata | Published version ]

• A cache-oblivious sparse matrix-vector multiplication scheme based on the Hilbert curve

  by A. N. Yzelman & Rob H. Bisseling
  in M. Günther, A. Bartel, M. Brunk, S. Schöps, and M. Striebel (eds.), Progress in Industrial Mathematics at ECMI 2010, pp. 627-634, Springer (2012).
  
  [ Citation | 2010 pre-print | Published version ]

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Others

• Incremental Sparse Tensor Format for Maximizing Efficiency in Tensor-Vector Multiplications

  by Xiaohe Niu, Georg Meyer, Dimosthenis Pasadakis, A. N. Yzelman, and Olaf Schenk, in 2025 IEEE International Conference on Cluster Computing Workshops (CLUSTER). Best poster award.
  
  [ Citation | Extended abstract (accepted version) | Code (GitHub) | Poster (local mirror) ]

• Efficient Parallel Scheduling for Sparse Triangular Solvers (Brief Summary)

  by Toni Böhnlein, Pál András Papp, Raphael S. Steiner, and A. N. Yzelman in Proceedings of the 2025 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), pp. 1263-1265, IEEE (2025).
  
  [ Citation | Published version ]

• Humble Heroes

  by A. N. Yzelman in Communications of Huawei Research, Issue 6, pp. 146–170, Huawei (2024)
  
  [ Citation | 2022 pre-print | Published version (local mirror) | Code repository (Apache 2.0 License) ]

• Brief Announcement: Red-Blue Pebbling with Multiple Processors: Time, Communication and Memory Trade-offs

  by Toni Böhnlein, Pál András Papp, and A. N. Yzelman in Proceedings of the 36th ACM Symposium on Parallelism in Algorithms and Architectures (SPAA '24), pp. 285-287, ACM (2024).
  
  [ Citation | Published version ]

• Efficient Multi-Processor Scheduling in Increasingly Realistic Models (Brief Summary)

  by Pál András Papp, Georg Anegg, Aikaterini Karanasiou, and A. N. Yzelman in Proceedings of the 2024 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), pp. 1169-1171, IEEE (2024).
  
  [ Citation | Published version ]

• Recent Trends in Graph Decomposition

  by G. Karypis, C. Schulz, D. Strash, D. Ajwani, R. H. Bisseling, K. Casel, Ü. V. Çatalyürek, C. Chevalier, F. Chudigiewitsch, M. F. Faraj, M. Fellows, L. Gottesbüren, T. Heuer, K. Kaya, J. Lacki, J. Langguth, X. S. Li, R. Mayer, J. Meintrup, Y. Mizutani, F. Pellegrini, F. Petrini, F. Rosamond, I. Safro, S. Schlag, R. Sharma, B. D. Sullivan, B. Uçar, A. N. Yzelman in G. Karypis, C. Schulz, D. Strash (eds.), Dagstuhl Reports, Vol. 13, Issue 8, pp. 1–45 (2024).
  
  [ Citation | Published version (local mirror) ]

• Nonlinear spectral clustering with C++ GraphBLAS

  by Dimosthenis Pasadakis, Olaf Schenk, Verner Vlačić, and A. N. Yzelman in IEEE HPEC '23 (virtual conference). Outstanding short paper award (2023).
  
  [ Citation | Final version ]

• A C++ GraphBLAS: specification, implementation, parallelisation, and evaluation

  by A. N. Yzelman, D. Di Nardo, J. M. Nash, and W. J. Suijlen, arXiv:1906.03196 (2020).
  
  [ Citation | 2020 pre-print | 2020 poster | Code repository (Apache 2.0 License) ]

• Lightweight Parallel Foundations: a model-compliant communication layer

  by W. J. Suijlen and A. N. Yzelman (2019).
  
  [ Citation | arXiv ]

• High performance sparse computations applied to a parallel conjugate gradient solver

  by A. N. Yzelman, pre-print (2015). In part succeeded by the paper ``A C++ GraphBLAS''.
  
  [ Citation | 2015 pre-print ]

• Sparse matrix-vector multiplication: parallelization and vectorization

  by A. N. Yzelman, D. Roose, & K. Meerbergen
  in J. Reinders and J. Jeffers (eds.), High Performance Parallelism Pearls: Multicore and Many-core Programming Approaches, Chapter 27, ISBN 978-01-280-2118-7, Elsevier (2014).
  [ Citation | Elsevier store | Amazon store ]

• Sparse matrix computations on multi-core systems

  A. N. Yzelman & D. Roose, Intel European Exascale Labs report 2013, pp. 24-29, Intel (2014).
  
  [ Citation | Published version ]

• Two-dimensional approaches to sparse matrix partitioning

  by R. H. Bisseling, B. O. Fagginger Auer, A. N. Yzelman, T. van Leeuwen & Ü. V. Çatalyürek in Uwe Naumann & Olaf Schenk (eds.), Combinatorial Scientific Computing, pp. 321--349, Chapman & Hall / CRC Press (2012).
  
  [ Citation | Published version ]

• Node counting in wireless ad-hoc networks

  Joep Evers, Demeter Kiss, Wojtek Kowalczyk, Tejaswi Navilarekallu, Michiel Renger, Lorenzo Sella, Vincent Timperio, Adrian Viorel, Sandra van Wijk, Albert-Jan Yzelman in B. Planqué, S. Bhualai, J. Hulshof, W. Kager, T. Rot (eds.), Proceedings of the 79th European Study Group with Industry, pp. 49-73, VU University Amsterdam (2012).
  
  [ Citation | Published version ]

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Theses

• Fast sparse matrix-vector multiplication by partitioning and reordering

  A. N. Yzelman, Ph.D. Dissertation, Utrecht University, ISBN 978-90-393-5590-9 (2011).
  
  [ Citation | Utrecht University archive | Local mirror ]

• R-Trees: an efficient structure for spatial data management

  A. N. Yzelman, Master's thesis, Utrecht University, August 2007.
  
  [ Citation | PDF ]

• Parallel Radiosity

  A. N. Yzelman, Bachelor's thesis, Utrecht University, February 2007.
  
  [ Citation | PDF ]

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Terms of use

Published articles and articles to appear are copyrighted by their respective publishers. Other articles copyrighted by their authors and/or employers, which may transfer to future publishers. Non-final forms of published articles may have terms of use that are stipulated within the PDF and/or in the below, if and as required by the publisher.

• Efficient handling of sparse vectors for parallel nonblocking execution in GraphBLAS (2025): This version of the contribution has been accepted for publication, after peer review (when applicable) but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available at a location that will be shared here once it appears. Use of this Accepted Version is subject to the publisher’s Accepted Manuscript terms of use https://www.springernature.com/gp/open-research/policies/accepted-manuscript-terms