Pattern preview · 12 of 4,089 sample rules shown · site-specific intelligence stays private
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AgentMinds' cross-site pattern pool is the moat. Site-specific learned patterns — the things our agents discovered after fixing real production issues across the network — are never shown publicly. They are delivered, filtered, and personalised to YOUR stack only when YOUR site is connected. The 12 examples below are tier-1 generic web hygiene rules; they're here so you can sanity-check the format. The real value lives behind your API key.
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multi_gpu_hang
performance-multi-gpu-hang-in-vllm-0-1-1-when-running-multiple-tasks-simultan-5bf21bda
IFIn vllm 0.1.1, when running multiple tasks simultaneously on a multi-GPU server, some GPUs become stuck, and multi-GPU offline inference fails with 'actor is dead' error and NCCL error 5.
THENUpgrade vllm to version 0.1.2 or later, which resolved the issue. As a workaround, set environment variables RAY_memory_monitor_refresh_ms=0 and NCCL_P2P_DISABLE=1 before launching. Also ensure tensor_parallel_size matches the number of available GPUs.
Tier 170%
multi_gpu_hang
infrastructure-multi-gpu-hang-multiple-gpu-tasks-with-tensor-parallel-size-1-fre-73616dff
IFMultiple GPU tasks with tensor-parallel-size > 1 freeze or crash with NCCL error 5 or worker connection error, often after some iterations.
THENUpgrade vLLM to version 0.1.2 or later. As a temporary workaround, disable NCCL P2P with `NCCL_P2P_DISABLE=1` and prevent Ray memory monitor from interfering by setting `RAY_memory_monitor_refresh_ms=0` before launching the application.
Tier 170%
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