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the transport of data on different spatial channels, whether modes or cores. In this context, multicore fibers have been widely studied and the final properties observed on data transport are largely governed by
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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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mathematics or equivalent competence. Your degree must be completed by the time of employment. Strong practical skills in C++ software development. Experience with parallel programming for multicore CPUs, GPUs
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are long vector/matrix multicore architectures. The goal of our team is to develop effective runtime and compiler support to program these architectures using the SYCL, OpenMP and OneDNN programming models
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Inria, the French national research institute for the digital sciences | Saint Martin, Midi Pyrenees | France | about 2 months ago
Leverage Multicore Parallelism to Achieve Scalable, Jitter-free I/O. Matthieu Dorier , Gabriel Antoniu , Franck Cappello, Marc Snir , Leigh Orf. IEEE Cluster 2012. https://inria.hal.science/hal-00715252
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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