Eidola is a gem5 extension that emulates cycle-level peer-to-peer GPU writes via real-application timing profiles to simulate traffic and synchronization in multi-GPU AI systems.
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2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 2verdicts
UNVERDICTED 2representative citing papers
A scoping review of physics-informed machine learning for seismic wave propagation finds applications in forward and inverse problems with often comparable accuracy at lower cost, while identifying gaps in benchmarking, training cost, and 3D/experimental validation.
citing papers explorer
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Eidola: Modeling Multi-GPU Network Communication Traffic in Distributed AI Workloads
Eidola is a gem5 extension that emulates cycle-level peer-to-peer GPU writes via real-application timing profiles to simulate traffic and synchronization in multi-GPU AI systems.
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A Scoping Review of Physics Informed Machine Learning for Wave Propagation Modeling in Seismology
A scoping review of physics-informed machine learning for seismic wave propagation finds applications in forward and inverse problems with often comparable accuracy at lower cost, while identifying gaps in benchmarking, training cost, and 3D/experimental validation.