Publications

Project results have been disseminated through high-impact publications in order to validate the project’s concept, findings and advantages and promote ideas gathering and knowledge exchange with relevant communities.

1. Ricardo Nobre, Aleksandar Ilic, Sergio Santander-Jiménez, and Leonel Sousa (2021). Fourth-Order Exhaustive Epistasis Detection for the xPU Era. 50th International Conference on Parallel Processing. Association for Computing Machinery, New York, NY, USA, Article 27, 1–10.
DOI: 10.1145/3472456.3472509.

2. Sunidhi Dhandhania, Akshay Deodhar, Konstantin Pogorelov, Swarnendu Biswas and Johannes Langguth (2021). Explaining the Performance of Supervised and Semi-Supervised Methods for Automated Sparse Matrix Format Selection, 50th International Conference on Parallel Processing Workshop, pp. 1-10.
DOI: 10.1145/3458744.3474049.

3. Diogo Marques, Aleksandar Ilic, and Leonel Sousa (2021). Mansard Roofline Model: Reinforcing the Accuracy of the Roofs. ACM Trans. Model. Perform. Eval. Comput. Syst. 6, 2, Article 7.
DOI: 10.1145/3475866.

4. Luk Burchard, Johannes Moe, Daniel Thilo Schroeder, Konstantin Pogorelov, and Johannes Langguth (2021). iPUG: Accelerating Breadth-First Graph Traversals Using Manycore Graphcore IPUs. High Performance Computing. ISC High Performance 2021. Lecture Notes in Computer Science, vol 12728. Springer, Cham.
DOI: 10.1007/978-3-030-78713-4_16.

5. Amro Alabsi Aljundi, Taha Atahan Akyildiz, and Kamer Kaya (2021). Boosting Graph Embedding on a Single GPU. IEEE Transactions on Parallel and Distributed Systems, vol. 33, no. 11, pp. 3092-3105.
DOI: 10.1109/TPDS.2021.3129617.

6. Luk Burchard, Xing Cai, and Johannes Langguth (2021). iPUG for Multiple Graphcore IPUs: Optimizing Performance and Scalability of Parallel Breadth-First Search. IEEE 28th International Conference on High Performance Computing, Data, and Analytics (HiPC), pp. 162-171.
DOI: 10.1109/HiPC53243.2021.00030.

7. Diogo Marques, Rafael Campos, Sergio Santander-Jiménez, Zakhar Matveev, Leonel Sousa, and Aleksandar Ilic (2022). Unlocking Personalized Healthcare on Modern CPUs/GPUs: Three-way Gene Interaction Study. 2022 IEEE International Parallel and Distributed Processing Symposium (IPDPS), pp. 146-156.
DOI: 10.1109/IPDPS53621.2022.00023.

8. Diogo Pinheiro, Sergio Santander-Jimenéz, and Aleksandar Ilic (2022). PhyloMissForest: a random forest framework to construct phylogenetic trees with missing data. BMC Genomics 23, 377.
DOI: 10.1186/s12864-022-08540-6

9. Amro Alabsi Aljundi, Taha Atahan Akyıldız, and Kamer Kaya (2022). Degree-Aware Kernels for Computing Jaccard Weights on GPUs. 2022 IEEE International Parallel and Distributed Processing Symposium (IPDPS), pp. 897-907.
DOI: 10.1109/IPDPS53621.2022.00092.

10. Gökhan Göktürk and Kamer Kaya (2022). Fast and High-Quality Influence Maximization on Multiple GPUs. 2022 IEEE International Parallel and Distributed Processing Symposium (IPDPS), pp. 897-907.
DOI: 10.1109/IPDPS53621.2022.00093.

11. Ricardo Nobre, Aleksandar Ilic, Sergio Santander-Jiménez, and Leonel Sousa (2022). Tensor-Accelerated Fourth-Order Epistasis Detection on GPUs. 51st International Conference on Parallel Processing (ICPP ’22), August 29-September 1, 2022, Bordeaux, France. ACM, New York, NY, USA, 11 pages.
DOI: 10.1145/3545008.3545066.

12. Erhan Tezcan, Tugba Torun, Fahrican Koşar, Kamer Kaya, and Didem Unat (2022). Mixed and Multi-Precision SpMV for GPUs with Row-wise Precision Selection. 2022 IEEE 34th International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD), Bordeaux, France, 2022, pp. 31-40.
DOI: 10.1109/SBAC-PAD55451.2022.00014.

13. Andreas Thune, Sven-Arne Reinemo, Tor Skeie and Xing Cai (2023). Detailed Modeling of Heterogeneous and Contention-Constrained Point-to-Point MPI Communication. IEEE Transactions on Parallel and Distributed Systems.
DOI: 10.1109/TPDS.2023.3253881.

14. Luk Burchard, Kristian Gregorius Hustad, Johannes Langguth and Xing Cai (2023). Enabling Unstructured-Mesh Computation on Massively Tiled AI-Processors: An Example of Accelerating In-Silico Cardiac Simulation. Front. Phys. Sec. Statistical and Computational Physics.
DOI: 10.3389/fphy.2023.979699.

15. Muhammad Aditya Sasongko, Milind Chabbi, Paul H. J. Kelly and Didem Unat (2023). Precise event sampling-based data locality tools for AMD multicore architectures. Concurrency Computat Pract Exper., BASARIM 2022. WSCAD 2021.
DOI: 10.1002/cpe.7707.

16. Sergej Breiter, Josef Weidendorfer, Minh Thanh Chung and Karl Fürlinger (2023). A Profiling-Based Approach to Cache Partitioning of Program Data. Parallel and Distributed Computing, Applications and Technologies. PDCAT 2022. Lecture Notes in Computer Science, vol 13798. Springer, Cham.
DOI: 10.1007/978-3-031-29927-8_35.

17. Miguel Graça, Diogo Marques, Sergio Santander-Jiménez, Leonel Sousa, and Aleksandar Ilic (2023). Interpreting High Order Epistasis Using Sparse Transformers. In 2023 IEEE/ACM Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE), pp. 114-125.
DOI: 10.1145/3580252.3586982.

18. James D. Trotter, Johannes Langguth and Xing Cai (2023). Targeting performance and user-friendliness: GPU-accelerated finite element computation with automated code generation in FEniCS. Parallel Computing, vol. 118.
DOI: 10.1016/j.parco.2023.103051.

19. James D. Trotter, Sinan Ekmekçibaşı, Johannes Langguth, Tugba Torun, Emre Düzakın, Aleksandar Ilic, and Didem Unat (2023). Bringing Order to Sparsity: A Sparse Matrix Reordering Study on Multicore CPUs. In Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC ’23). Association for Computing Machinery, New York, NY, USA, Article 31, 1–13.
DOI: 10.1145/3581784.3607046.

20. Alexandre Rodrigues, Leonel Sousa and Alexandar Ilic (2023). Performance Modelling-driven Optimization of RISC-V Hardware for Efficient SpMV. Proceedings of the International workshop on RISC-V for HPC. High Performance Computing. ISC High Performance 2023. Lecture Notes in Computer Science, vol 13999. 
DOI: 10.1007/978-3-031-40843-4_36.

21. Afonso Coutinho, Diogo Marques, Leonel Sousa and Aleksandar Ilic (2023). Sparse-aware CARM: Rooflining locality of sparse computations. In the 1st International Workshop on Tools for Data Locality, Power and Performance (TDLPP/EuroPar) (to be published).

22. Sergej Breiter, James D. Trotter, and Karl Fürlinger (2023). Modelling Data Locality of Sparse Matrix-Vector Multiplication on the A64FX. In Proceedings of the SC ’23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis (SC-W ’23). Association for Computing Machinery, 1334–1342.
DOI: 10.1145/3624062.3624198.

23. Asep Maulana and Johannes Langguth (2023). Using GNNs for Misinformation Spreader Detection via Assortativity-Aware Node Label Classification in Twitter Networks. In 2023 Tenth International Conference on Social Networks Analysis, Management and Security (SNAMS), Abu Dhabi, United Arab Emirates, 2023, pp. 1-8. doi: 10.1109/SNAMS60348.2023.10375407.

24. Mustafa Orkun Acar, Fatma Güney, and Didem Unat (2023). Optimizing GNN-based Multiple Object Tracking on a Graphcore IPU. In The HPC on Heterogeneous Hardware (H3) Workshop 2023 (to be published).

25.Konstantin Pogorelov, James Trotter, Johannes Langguth and Tumanis (2023). Performance Prediction for Sparse Matrix Vector Multiplication using Structure-dependent Features. Proceedings of the TDLPP 2023 Workshop on Tools for Data Locality, Power and Performance (to be published).

26. Gökhan Göktürk, and Kamer Kaya (2024). Fast and error-adaptive influence maximization based on Count-Distinct sketches. Information Sciences, Volume 655, 119875. DOI: https://doi.org/10.1016/j.ins.2023.119875.

27. Ricardo Nobre, Aleksandar Ilic, Sergio Santander-Jiménez, and Leonel Sousa (2024).  IPU-EpiDet: Identifying Gene Interactions on Massively Parallel Graph-Based AI Accelerators. In the 38th IEEE International Parallel and Distributed Processing Symposium (IPDPS 2024), San Francisco, California USA, 2024 (to be published).

Theses

SparCity results were also disseminated through students’ theses.

Koç University

2022
Erhan Tezcan, M.Sc Thesis
Title: Exploring Mixed and Multi-Precision SpMV for GPUs

2024
Mandana Bagherimarzijarani, M.Sc Thesis
Tile: An Automated Framework for Concurrent Graph Processing Kernel Fusion on GPU

Mustafa Orkun Acar, M.Sc.
Title: Optimizing Multiple Object Tracking with Graph Neural Networks on a Graphcore IPU

INESC-ID

2022
Afonso Silva Mendes Coutinho, M.Sc Thesis
Title: CARM-based approach for sparse computation characterisation

Miguel Ângelo da Silva Graça, M.Sc Thesis
Title: Sparse Transformers for High Order Epistasis Detection

2023
Alexandre Daniel dos Santos Rodrigues, M.Sc Thesis
Title: Performance Modelling-based Methodology for RISC-V Architecture Design

Filipe dos Santos Borralho, M.Sc Thesis
Title: Exploring the Limits of Cross-Platform Sparse Tensor Processing

José Carlos Oliveira Brito, M.Sc Thesis
Title: The New Age of Genomic Analysis: Harnessing ReRAM Technology for Epistasis Detection

LMU

2022
Sergej Breiter, M.Sc Thesis
Title: Evaluating Sector Caches in High-Performance Computing

2023
Felix Rocke, Bachelor Thesis
Thesis: Evaluation of C++ SIMD Libraries

2024
Stefan Schnellberger, Bachelor Thesis (Ongoing)
Title: Requirements associated with a command line interface for a dynamic hardware topology information system

Simula

2021
Aigars Tumanis, M.Sc Thesis
Title: Graph Clustering for Long Term Twitter Observations Community Detection in Incremental Graphs

Johannes Moe, M.Sc Thesis
Title: Accelerator Performance Analysis on Spatio-Temporal Graph Convolutional Networks.

Simen Håpnes, M.Sc Thesis
Title: Solving Partial Differential Equations by the Finite Difference Method on a Specialized Processor.

2023
Rohullah Akbari, M.Sc Thesis
Title: NLP-Based Automated Conspiracy Detection for Massive Twitter Datasets.

Luk Burchard, PhD Thesis
Tile: Repurposing Domain-specific Hardware Accelerators for Sparse and Irregular High-Performance General-Purpose Computation.

Sabanci

2023
Fatih Taşyaran, M.Sc Thesis
Title: SuperTwin: Digital Twins for High-Performance Computing Clusters