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Inria, the French national research institute for the digital sciences | Pau, Aquitaine | France | 4 days ago
deterministic inversion approaches. Low-order arithmetic offers promises of important cost-reduction via the use of GPUs, and is commonly used in learning approaches, it has therefore become a central block of an
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FPGAs, CGRAs, and many Machine Learning accelerators, offer significant opportunities for improving performance and energy efficiency compared to traditional CPUs/GPUs. Yet, porting and optimizing code
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physics, mathematics or any related field. What we offer State of the art on-site high performance/GPU compute facilities Competitive research in an inspiring, world-class environment A wide range of offers
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-design with accelerators (FPGAs, GPUs, near-memory systems) to achieve real-time, energy-efficient AI for high-tech industry applications. Work with leading companies like ASMPT and shape the future of AI
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the development of scalable software tools and pipelines, potentially leveraging GPU/FPGA accelerators. Our aim is to build next-generation molecular atlases for chronic diseases and to improve patient
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compressible gas dynamics, heat transfer, free-surface/melt behaviour, and mass transfer driven by phase change, within a GPU-accelerated solver to reduce simulation turnaround times. You will develop and
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compressible gas dynamics, heat transfer, free-surface/melt behaviour, and mass transfer driven by phase change, within a GPU-accelerated solver to reduce simulation turnaround times. You will develop and
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-following inverters. Implementing and optimizing scalable algorithms for transient and stability analyses on HPC architectures (CPU, GPU, hybrid). Enhancing the numerical robustness and efficiency of existing
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foundations. Candidates should possess an exceptional academic record and a strong mathematical background. Experience conducting large-scale computational experiments (e.g., multi-GPU systems) is advantageous
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and clinical MR systems fully dedicated to research, state-of-the-art local and scalable cloud-based compute infrastructure (CPU, GPU) and workshops for mechanical, electrical and electronic development