Boro Sofranac
HPCLabs

My experiences include industry and research posts in the fields of High-Performance Computing, Mathematical Optimisation, Quantum Computing, as well as Scientific Simulations and Software Development. For a detailed list of my experiences, head over to my LinkedIn page.

I am a Founder at HPCLabs, a consultancy specialising in HIgh-Performance Computing. For more details on the types of services offered by HPCLabs, visit our website.

I hold a master's degree in Computational Science and Engineering from Technical University Munich and a bachelor's degree in Mechanical Engineering from the University of Montenegro. I am currently working towards a PhD in Computer Science at the Technical University Berlin, with a "Guest" position at the Zuse Institute Berlin.

Publications:

Preprints:

1. Chalkis, A., Kleinert, T., & Sofranac, B. (2023). QUBO Dual Bounds via SDP Plane Projection Method. [arXiv]

Refereed conference proceedings:
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1. Thuerck, D., Sofranac, B., Pfetsch, M. E., & Pokutta, S. (2023). Learning Cuts via Enumeration Oracles. NeurIPS 2023. [arXiv][Official page]
2. Sofranac, B., Gleixner, A., & Pokutta, S. (2021). An Algorithm-Independent Measure of Progress for Linear Constraint Propagation. In L. D. Michel (Red), 27th International Conference on Principles and Practice of Constraint Programming (CP 2021) (bll 52:1-52:17). doi:10.4230/LIPIcs.CP.2021.52. [arXiv][code][slides][video]
3. Sofranac, B., Gleixner, A., & Pokutta, S. (2020). Accelerating Domain Propagation: An Efficient GPU-Parallel Algorithm over Sparse Matrices. 2020 IEEE/ACM 10th Workshop on Irregular Applications: Architectures and Algorithms (IA3), 1–11. doi:10.1109/IA351965.2020.00007. [arXiv][code][summary][slides][video]

Refereed journals:
     

1. Bestuzheva et al. (2023). Enabling Research through the SCIP Optimization Suite 8.0. ACM Trans. Math. Softw. 49, 2, Article 22 (June 2023), 21 pages. doi:10.1145/3585516 [arXiv]
2. Sofranac, B., Gleixner, A., & Pokutta, S. (2022). An Algorithm-Independent Measure of Progress for Linear Constraint Propagation. Constraints (2022). doi:10.1007/s10601-022-09338-9 [arXiv][code][slides][video]
3. Sofranac, B., Gleixner, A., & Pokutta, S. (2022). Accelerating domain propagation: An efficient GPU-parallel algorithm over sparse matrices. Parallel Computing, 109, 102874.  doi:​10.1016/j.parco.2021.102874 [arXiv][code][summary][slides][video]