Summary of Research
My research focuses on developing novel high-performance computing and numerical linear algebra techniques that support scientific applications. I am currently focusing on the Random Phase Approximation (RPA) correlation energy, the gold standard for electronic structure calculations with chemical accuracy (1 kcal/mol). RPA's bottleneck is computing the trace of a function of a matrix. Current solvers scale poorly on distributed architectures for large chemical systems. My research addresses this by developing theory, algorithms, and software for the Simulation Package for Ab-initio Real-space Calculations (SPARC).
Publications
Abir Haque, Suzanne Shontz, Xuemin Tu. GPU-Accelerated, Mixed Precision GMRES(m) with Varied Restarts. IEEE High Performance Extreme Computing Conference (HPEC 2025), Sep 2025.
Abir Haque, Suzanne Shontz. Parallelization of the Finite Element-based Mesh Warping Algorithm Using Hybrid Parallel Programming. SIAM International Meshing Roundtable Workshop (SIAM IMR 25), Mar 2025.
Awards
National Science Foundation Graduate Research Fellowship Program (declined for DOE CSGF), 2026
Outstanding Student Paper Award, IEEE High Performance Extreme Computing Conference 2025 (HPEC 2025), 2025
Undergraduate Research Fellow, KU School of Engineering, 2023-2025
Honorable Mention for Computing Research Association Outstanding Undergraduate Researcher Award, 2024
3rd Place in ACM Undergraduate Student Research Competition at Supercomputing 2024 (SC24), 2024
1st Place in Undergraduate Poster Competition, KU Graduate Engineering Association Research Showcase, 2024
1st Place in Undergraduate Poster Competition, KU I2S Student Research Symposium, 2024