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precision algorithms for CPUs and GPUs. Performance engineering and analysis including application profiling, benchmarking to identify performance bottlenecks. Verification, and validation of the developed
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supporting new research and engineering using ORNL’s Frontier exascale supercomputer for its dense GPU-based HPC resources to train, deploy models and create large-scale production datasets for high-impact
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and collaborative team of computational scientists, software and AI engineers, and neuroscientists, you’ll have access to high-performance workstations, CPU/GPU clusters, and experimental systems
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infrastructures, improving system performance, scalability, and efficiency by optimizing resource usage (e.g., GPUs, CPUs, energy consumption). Researchers and students will explore innovative approaches to reduce
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models, LLMs and Transformer architectures Excellent programming skills in PyTorch/JAX and experience working with GPUs and high-performance clusters. Strong mathematical skills with excellent
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learning, multicore and GPU programming, and highly parallel systems. Good knowledge in one or more of the following programming languages/environments: C/C++, Python, PyTorch (or similar), and Cuda. Place
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in high-performance computing systems, storage and I/O. Extensive knowledge on parallel file systems, GPUs, and their trends. (more than 3 years of working with these systems) Experience with
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Inria, the French national research institute for the digital sciences | Pau, Aquitaine | France | 3 months ago
://ffaucher.gitlab.io/hawen-website/ ), by enriching its feature set and improving its parallel performance on graphical processing units (GPUs). The Hawen software simulates wave propagation in various media, including
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- and hardware-oriented, reliable programming of parallel systems ranging from embedded multi- and many-core processors to large-scale heterogeneous systems (CPUs, GPUs, Accelerators, etc.). The research
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spatial datasets efficiently. Research‑grade software engineering skills (version control, testing, reproducibility, documentation); open‑source contributions are meriting. Experience with GPU/high