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for reproducible, efficient and scalable training and inference on parallel, distributed and GPU-accelerated computing systems Benchmark the developed approaches against established methods, assessing
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leading the design and deployment of HPC or large-scale distributed computing systems. Expertise with batch schedulers (SLURM, PBS, LSF) and parallel file systems (Lustre, GPFS/Spectrum Scale). Proven
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compiler optimization techniques. Experience with distributed and parallel computing technologies such as MPI and OpenMP. Experience with large-scale neural network architectures for processing
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. About us The Department of Computer Science and Engineering , a joint department of Chalmers and the University of Gothenburg, spans the breadth of computing disciplines. Our internationally