Julian Bellavita

Computer Science PhD Student at Cornell

I am a Computer Science PhD student at Cornell advised by Dr. Giulia Guidi. I have a BA in CS from UC Berkeley, and I previously worked at Lawrence Berkeley National Laboratory.

I work on writing fast distributed sparse linear algebra kernels for heterogeneous HPC systems, parallel clustering using sparse linear algebra, and tensor decompositions.

I am supported by a Department of Energy Computational Science Graduate Fellowship.

You can email me at jbellavita@cs.cornell.edu

Bellavita_Julian_CSGF_[2024] (5) (1).JPG

Publications

Julian Bellavita, Thomas Pasquali, Laura Del Rio Martin, Flavio Vella, and Giulia Guidi. 2025. "Popcorn: Accelerating Kernel Kmeans on GPUs through Sparse Linear Algebra". In The 30th ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming (PPoPP 2025).

McFarland, Thomas, Julian Bellavita, and Giulia Guidi. "Parallel GPU-Enabled Algorithms for SpGEMM on Arbitrary Semirings with Hybrid Communication". In Proceedings of the 16th ACM/SPEC International Conference on Performance Engineering (ICPE 2025).

Julian Bellavita, Mathias Jacquelin, Esmond G. Ng., Dan Bonachea, Johnny Corbino, & Paul H. Hargrove. "symPACK: A GPU-Capable Fan-Out Sparse Cholesky Solver". In Proceedings of the SC'23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis (SC-W 2025).

Adrián Castelló, Julian Bellavita, Grace Dinh, Yuka Ikarashi, & Hector Martínez. (2023). Tackling the Matrix Multiplication Micro-kernel Generation with Exo. IEEE/ACM International Symposium on Code Generation and Optimization (CGO 2024).

Julian Bellavita, Caitlin Sim, Kesheng Wu, Alex Sim, Shinjae Yoo, Hiro Ito, Vincent Garonne, Eric Lancon, ”Understanding Data Access Patterns for dCache System". In 26th International Conference on Computing in High Energy & Nuclear Physics (CHEP 2023).

Julian Bellavita, Alex Sim, Kesheng Wu, Inder Monga, Chin Guok, Frank Würthwein, and Diego Davila. 2022. ”Studying Scientific Data Lifecy- cle in On-demand Distributed Storage Caches”. In Fifth International Workshop on Systems and Network Telemetry and Analytics (SNTA 2022).

Education

Cornell University

PhD, Computer Science

2023-Present

University of California, Berkeley

B.A. Computer Science

2019-2023