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. Computational Optimization: Resolving hardware-specific performance and numerical precision challenges across diverse GPU environments. Architecture Design: Leading the design of new loss functions, model
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Posting Number R260058 Posting Link https://www.ubjobs.buffalo.edu/postings/61964 Employer Research Foundation Position Type RF Professional Job Type Full-Time Appointment Term Salary Grade E.89 Posting
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of three active research communities: operating systems memory management (NUMA policy, page migration, swap behaviour), high-performance and GPU computing (memory coalescing, unified memory, PCIe transfer
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well as large-scale GPU computing facilities for deep learning. We are looking for a Research Engineer to manage the EEE GPU Cluster. The role will focus on enhancing the EEE GPU Cluster team’s ability in terms
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orchestration in Kubernetes (e.g., NVIDIA device plugin, GPU scheduling, MIG, node affinity). Experience optimizing GPU utilization, memory management, and cost efficiency for compute-intensive workloads
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, MIG, node affinity). Experience optimizing GPU utilization, memory management, and cost efficiency for compute-intensive workloads. Preferred Competencies Ability to collaborate and interact effectively
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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | 20 days ago
Internal Number: 25597 INFORMATION SECURITY MANAGER, The Massachusetts Green High Performance Computing Center (MGHPCC ), to serve as the primary security leader across MGHPCC and the AI Computing Resource
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compensation package with comprehensive health and welfare benefits. A supportive team environment that promotes collaboration and knowledge sharing. Access to world-class computational infrastructure, GPU-based
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studies. These pipelines must be capable of efficiently exploiting different types of parallelism, both at the level of a computing node (CPU and GPU) and at the level of a cluster of PCs. This environment
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supportive team environment that promotes collaboration and knowledge sharing. Access to world-class computational infrastructure, GPU-based computing environments, and unique high-quality cryoET datasets