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Paul Richmond -Tutorial -Large Scale Agent Based Modelling w/ FLAME GPU 2
FloodPedestrian Model on FLAME-GPU
1 billion tokens a minute on one GPU: Modal's inference research, explained
llama cpp SYCL vs Vulkan on Intel Arc Pro B70 Qwen3 8 27B
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Last Updated: September 29, 2026
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Summary
In this video, Paul Richmond of the University of Sheffield, talks about agent-based 1000 x 1000 cells visualised as a collection of cubes as we don't yet have a dedicated discrete visualiser. This is a video of the Pedestrian Navigation example inside Tutorial - Large Scale Agent Based An interactive and active agent-based flood When an LLM writes one token for one user, an H100 uses about 0.3% of its compute. The rest waits on memory. Modal's blog ... Same Intel Arc Pro B70, same Qwen3.8 27B Q4_K_M, two llama.cpp backends. I ran SYCL and Vulkan side by side with a real ...