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heterogeneous architectures, including CPUs, GPUs, and other accelerators, the project seeks to achieve unprecedented efficiency and resolution in plasma simulations. This advancement will enable high-fidelity
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provide a performance or efficiency advantage, and determine scenarios where conventional AI accelerators (such as embedded GPUs or FPGA-based accelerators) remain more appropriate due to data
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
workloads with dedicated GPU and large-memory partitions. The Research Triangle area is a dynamic collaborative environment with UNC-Chapel Hill, Duke University, and North Carolina State University all
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
, including the 17,000-core Longleaf cluster optimized for I/O intensive workloads with dedicated GPU and large-memory partitions. The Research Triangle area is a dynamic collaborative environment with UNC
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 4 days ago
, including the 17,000-core Longleaf cluster optimized for I/O intensive workloads with dedicated GPU and large-memory partitions. The Research Triangle area is a dynamic collaborative environment with UNC
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 4 days ago
workloads with dedicated GPU and large-memory partitions. The Research Triangle area is a dynamic collaborative environment with UNC-Chapel Hill, Duke University, and North Carolina State University all
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, Matlab Preferred Qualifications: Experience in thermos-fluids in porous media. Experience in High-Performance Computing (HPC) on CPU or GPU platforms. Experience in mentoring of graduate and undergraduate
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, with PyTorch and/or other GPU programming tools is also necessary. You should have completed all requirements for your PhD by the time you are hired. How to Apply: Candidates who have most, but not all
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FWO-UGent funded bioinformatics postdocs: Unveiling the significance of gene loss in plant evolution
environment Access to state-of-the-art tools and computational infrastructure, including CPU/GPU clusters Opportunity to contribute to cutting-edge research in plant evolution and genomics Support
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on the platform CUDA for parallelization of the computation over several GPUs’ cores, and has interfaces with Matlab and Python for ease of use. However, powerful as it is, MagTense is at present limited in its