Meet the SCC23 Team
Competition Team
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About |
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Khai Vu (Team Lead) |
Khai is the SCC23 team lead and was a SCC22 alternate. His expertise spans numerical methods and networking, with a focus on high-performance networking, system administration, containerization, and various low-level hardware interfaces and parallelization frameworks like IBverbs, SIMD intrinsics, MPI, and OpenMP. |
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Austin Garcia |
Austin is a master of low-level coding and data science. Austin has a penchant for delving into the lowest levels of abstraction, including assembly language. He is known for creatively repurposing Turing-complete environments, as exemplified by his project of building a 3D rendering engine into Desmos. His involvement in the Super Fast Storage project of the supercomputing club highlights his proficiency in storage systems and data science prowess. |
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Francisco Gutierrez |
Francisco has a taste for fine-tuning operating systems and their configurations, and is on a continual quest to understand the deepest layers of his computers. This hobby has prepared him well for SCC, where optimization is the name of the game. Francisco also leads the Supercomputing Club on campus. |
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Gloria Seo |
Gloria is a third-year Mathematics and Computer Science major at UC San Diego, with a solid understanding of both disciplines. Her interest lies in leveraging mathematical theory to solve complex computer science problems. She is also passionate about data science and machine learning, where her mathematical background allows her to excel in extracting insights from data and developing predictive models. |
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Kyle Smith |
Kyle offers a unique intersection of bioinformatics and computer architecture research experience. He specializes in high-performance software design and parallel computing for CPUs and GPUs. He is keen to explore how supercomputing can assist in solving complex computational problems within bioinformatics. |
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Zixian Wang |
Zixian excels in the field of computer vision and deep learning. He has experience training large datasets like BDD100K and SHIFT for object detection. Having participated in last year’s team training, he aspires to apply his HPC knowledge to train large models efficiently and effectively. |
Alternate Team
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STUDENT_NAME |
STUDENT_NAME description |
Home Team
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Danny Vo |
Danny is a first-year masters student in Computer Engineering at UC San Diego. He is interested in FPGA and VLSI design as well as GPU programming, though he is also versed in various other topics such as servers, networking and electronics prototyping. Danny mentors and leads in the measurement of power usage and Grafana visualization to monitor the cluster’s performanc |
Mentors
For questions and comments, please contact Mary Thomas: mpthomas at ucsd.edu