Babak Poursartip is a computational scientist and software engineer with 15+ years solving PDEs and nine years of professional software experience, now building high-performance numerical libraries and ML infrastructure at AMD. He combines deep domain expertise in finite element/finite volume methods, seismic and acoustic wave simulation, and inverse problems with hands-on HPC skills in C++, CUDA/HIP, PETSc, MPI and OpenMP. His work spans research-grade modeling—mesh generation, PMLs, fluid-structure interaction—and production performance engineering, contributing to prominent ROCm projects like rocBLAS and Tensile to optimize high-precision GEMM kernels. Academically grounded with a PhD in Computational Mechanics and teaching experience at UT Austin, he translates theory into scalable parallel codes and large-scale visualization pipelines using VTK/HDF5. Notably, he has a track record of end-to-end implementations from 5k-line finite-element solvers to GPU backend optimizations, reflecting both deep numerical insight and practical performance tuning. Based in Austin, he maintains an open-source portfolio that surfaces his blend of research rigor and production-oriented engineering.
9 years of coding experience
11 years of employment as a software developer
Doctor of Philosophy - PhD, Computational Mechanics, 4.00 GPA, Doctor of Philosophy - PhD, Computational Mechanics, 4.00 GPA at The University of Texas at Austin
Amirkabir University of Technology
Bachelor of Science, ENGINEERING, Bachelor of Science, ENGINEERING at Shahid Chamran University
Dimlopa, Math. and Physics, Dimlopa, Math. and Physics at National Organization for Development of Exceptional Talents
Contributions:14 reviews, 29 commits, 19 PRs in 1 year 1 month
Contributions summary:Babak's contributions primarily focused on optimizing and enhancing the rocBLAS library, specifically concerning High Precision Accumulate (HPA) GEMM kernels. They modified the code to normalize naming conventions for HPA kernels and implemented memory allocation strategies for GSU (Generalized Solution Update) operations. Furthermore, the user added test cases for updated HPA functionality and updated the documentation, indicating a focus on performance improvements and code maintainability. The commits also include updates to code object versions and library logic, indicating work to keep the library current.
Contributions:151 reviews, 16 commits, 122 PRs in 11 months
Contributions summary:Babak contributed to the `rocm/tensile` repository by addressing a bug related to High-precision fp16 (HBH) in the kernel assembly and modifying compute data types. They also normalized naming conventions for various HPA types and updated the GSU (Global Split U) functionality, including adding a SingleBuffer algorithm for HSS/BSS gemm functions. Additionally, the user enhanced the efficiency script by including all gemm data types and added zero to valid values for StaggerUStride. Finally, the user updated the library version.
amdpythontensorhipauto-tuning
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