Anna Verner
About Anna Verner
Anna Verner is a Kernel Engineer and Member of Technical Staff at Cerebras Systems, where she has worked since 2022. She has extensive experience in software engineering, particularly in GPU architecture and performance optimization, with a strong background from her time at Intel Corporation and her academic achievements in Applied Mathematics and Computer Science.
Work at Cerebras Systems
Anna Verner has been employed at Cerebras Systems as a Kernel Engineer and Member of Technical Staff since 2022. In this role, she contributes to the development and optimization of kernel-level software, leveraging her expertise in performance tuning and parallel computing. Her work focuses on enhancing the efficiency of computing processes, which is essential for the high-performance computing solutions offered by Cerebras Systems.
Experience at Intel Corporation
Prior to her current position, Anna Verner worked at Intel Corporation in various capacities. She served as a Software Engineer from 2019 to 2020, where she gained valuable experience in software development. Additionally, she completed two summer internships at Intel, one in 2017 and another in 2018, each lasting seven months. These roles provided her with hands-on experience in software engineering and deepened her understanding of GPU architecture.
Education and Expertise
Anna Verner holds a Master's degree in Applied Mathematics and Computer Science from Northern (Arctic) Federal University, which she completed from 2016 to 2018. She also earned a Specialist's degree in the same field from the same institution, studying from 2010 to 2015. Her educational background has equipped her with a strong foundation in mathematical principles and computational techniques, which she applies in her professional work.
Technical Skills and Specializations
Anna possesses a deep understanding of GPU architecture, which is vital for General-Purpose computing on Graphics Processing Units (GPGPU) programming and performance optimization. She has demonstrated advanced skills in performance tuning by optimizing C++ and Fortran demos to exceed Intel Advisor's roofline benchmarks. Furthermore, she has implemented and optimized a third of C++ Standard Template Library (STL) algorithms on GPU using SYCL, showcasing her proficiency in parallel computing.
Proficiency in Modern C++
Anna Verner has a strong proficiency in C++14, particularly in template metaprogramming. This indicates her high level of expertise in modern C++ features, enabling her to write efficient and maintainable code. Her skills in C++ are critical for her work in kernel engineering and software optimization, allowing her to contribute effectively to complex projects.