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home to HiPerGator, one of the most powerful high-performance computers at a US public university (https://www.rc.ufl.edu/about/hipergator/ ), and recently added the new AI NVIDIA GPU SuperPod (https
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following technology areas: hardware/software co-design, performance optimization with heterogeneous and alternative computing systems (CPU/GPU/NPU/etc.), FPGA design, high-performance computing (HPC
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University is home to Türkiye’s largest GPU cluster, providing advanced infrastructure for leading-edge AI research. The Department of Computer Science and Engineering at Koç University has world-renowned
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networking technologies such as InfiniBand. Working knowledge of GPU technologies like CUDA and OpenCL. Experience with distributed computing job schedulers (e.g., Slurm, PBS). Familiarity with
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IT4Innovations National Supercomputing Center, VSB - Technical University of Ostrava | Czech | 2 months ago
on highly scalable parallel applications with focus on: development and implementation of parallel aplications, GPU acceleration of applications, application optimization (improving scalability, vectorization
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SecureData4Health (SD4H) OpenStack cloud infrastructure. It currently includes 15,000 VCPU, 60 Petabyte of storage, 30 GPU and is growing as additional academic research projects join. The Software Infrastructure
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well as experience working with large biological datasets in scalable GPU-based computing environments. What we provide: A competitive compensation package, with comprehensive health and welfare benefits. A supportive
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and scalable model deployment. Skilled in working with medium-large scale multicore and heterogeneous (CPU + GPU) clusters. Excellent verbal and written communication skills. Preferred qualifications
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data analysis, simulation, and machine learning, integrating resources across multiple facilities. NERSC's next major supercomputer, Doudna, will combine next generation GPUs, networking and storage
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Windows and Linux virtual machines for research and instructional purposes, including the allocation and optimization of GPU resources. Develop and maintain scripts and simple web applications to support