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for process-local loose coupling in high-performance simulation codes. PDI supports the modularization of codes by inter-mediating data exchange between the main simulation code and independent modules (plugins
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degree in computer science and: You have a good knowledge of C++ You have skills in software engineering. You are familiar with common development environments and associated tools Knowledge of parallel
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good understanding of matrix algebra • Good understanding of RF power amplifier design (Class of operation, loadline theory, loadpull…) • Good understanding of semiconductor process such as CMOS, BiCMOS
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long repetitive and complex process. (2) Assess how LLM perform and can be complementary to traditional tools used for evaluation (formal methods, using Frama-C and Lazart). Internship tasks •Literature
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Learning systems: Attack Objectives Implement diffusion-based gradient inversion attacks inspired by GGDM [5], conditioning the diffusion process on client gradients or embeddings to reconstruct original
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range of computer vision tasks. Their strong representational capacity, however, comes at the price of significantly higher computational complexity and memory requirements. This poses a major challenge