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optimize large-scale distributed training frameworks (e.g., data parallelism, tensor parallelism, pipeline parallelism). Develop high-performance inference engines, improving latency, throughput, and memory
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architectures, distributed computing, high performance and parallel computing, ethical and sustainable computing, artificial intelligence. The journal will also explore opportunities in emerging and
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evaluation, or a strong willingness to gain hands-on experience. Eagerness to learn HPC concepts, including parallel computing, distributed systems, and optimization. Analytical skills, problem-solving
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subject matter expert at this level. Using deep expertise in high-performance computing (HPC) systems, including resource managers, schedulers, and parallel file systems (e.g., Lustre), the IT Security
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. Design, install, program, configure and maintain new or existing technology systems and services for a diverse customer base within the University community. Serves as a senior level technical support to
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assignments. Handle multiple and parallel projects and independently prioritize work assignments. Ability to obtain and retain Property Management Certifications. Preferred Knowledge, Skills, and Abilities
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exploring them. Basic data preprocessing, feature engineering, and model evaluation, or a strong willingness to gain hands-on experience. Eagerness to learn HPC concepts, including parallel computing
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to well-known open-source projects or a personal portfolio of impactful open-source research code. Experience with large-scale distributed training and high-performance computing (HPC) environments.
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hardware architectures (multicore, GPUs, FPGAs, and distributed machines). In order to have the best performance (fastest execution) for a given Tiramisu program, many code optimizations should be applied
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services, distributed web authentication, LDAP, computing account management, and other similar technologies, as well as auditing software, centralized antivirus management, intrusion detection systems