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Field
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Python, using GPUs), with the precise balance determined by the candidate’s background and interests. The mathematical tools involved will include matrix analysis, optimization, backward error analysis
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projects to the Tier 2 supercomputer Bede (32 IBM Power 9 dual-CPU nodes, each with 4 NVIDIA V100 GPUs and high performance interconnect). The is also well-provisioned with computational resources and you
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projects to the Tier 2 supercomputer Bede (32 IBM Power 9 dual-CPU nodes, each with 4 NVIDIA V100 GPUs and high performance interconnect). The is also well-provisioned with computational resources and you
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the Northern 8 cluster, members of Durham University can also submit projects to the Tier 2 supercomputer Bede (32 IBM Power 9 dual-CPU nodes, each with 4 NVIDIA V100 GPUs and high performance interconnect
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/GPUs. These devices provide massive spatial parallelism and are well-suited for dataflow programming paradigms. However, optimizing and porting code efficiently to these architectures remains a key
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person will focus on either using and/or developing Vlasiator. Prior knowledge in at least one of the following areas is required: GPU technologies, high-performance computing, parallelisation algorithms
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development skills Model deployment (e.g., ONNX, TensorRT) Edge computing or embedded vision systems (e.g., NVIDIA Jetson Nano) Real-time processing and GPU acceleration Experience working on industry R&D
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 29 days ago
. Opportunities may also exist to participate in planned field campaigns in Greenland. The postdoctoral scholar will be expected to improve on existing GPU-accelerated ocean models and develop laboratory
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-getalp.imag.fr/ ), which offers a dynamic, international, and stimulating environment to conduct high-level multidisciplinary research. The person will have access to large datasets, GPU servers, means
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with AI inside HPC applications is considered a plus. Experience with performance modeling (such as computer architecture simulation) for multiple types of computer hardware (e.g. CPU/GPU/NPU, or network