Diagnose the most expensive silent failure on a CoreWeave multi-node GPU job: GPUDirect RDMA falling back from InfiniBand to TCP. When NCCL drops from NET/IB to NET/Socket, collectives keep running with NO error but throughput collapses (commonly 5-20x slower) while every GPU still bills at full rate — 5x the GPU bill for the same work, invisibly. Paste an NCCLDEBUG=INFO log (and/or a pod-spec, ibstat, or allreduceperf output) and the bundled deterministic script verdicts whether RDMA is actually engaged, which of the three required conditions is missing, and the fix. Use when multi-node training is slow, when checking whether RDMA/InfiniBand is engaged, or when all-reduce bandwidth looks low. Trigger with "coreweave slow training", "is RDMA working", "NCCL fell back to TCP", "NET/Socket", "GPUDirect RDMA", "infiniband not used", "multi-node training slow".
Install with
Claude CodeCodexCursorGitHub CopilotGemini CLI
Supported by the Atlas install prompt. Skill-specific requirements vary.
Skill stats
Skills1CategoryGeneralStars0
About this skill
Diagnose the most expensive silent failure on a CoreWeave multi-node GPU job: GPUDirect RDMA falling back from InfiniBand to TCP. When NCCL drops from NET/IB to NET/Socket, collectives keep running with NO error but throughput collapses (commonly 5-20x slower) while every GPU still bills at full rate — 5x the GPU bill for the same work, invisibly. Paste an NCCLDEBUG=INFO log (and/or a pod-spec, ibstat, or allreduceperf output) and the bundled deterministic script verdicts whether RDMA is actually engaged, which of the three required conditions is missing, and the fix. Use when multi-node training is slow, when checking whether RDMA/InfiniBand is engaged, or when all-reduce bandwidth looks low. Trigger with "coreweave slow training", "is RDMA working", "NCCL fell back to TCP", "NET/Socket", "GPUDirect RDMA", "infiniband not used", "multi-node training slow".
Quick start
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Diagnose the most expensive silent failure on a CoreWeave multi-node GPU job: GPUDirect RDMA falling back from InfiniBand to TCP. When NCCL drops from NET/IB to NET/Socket, collectives keep running with NO error but throughput collapses (commonly 5-20x slower) while every GPU still bills at full rate — 5x the GPU bill for the same work, invisibly. Paste an NCCL_DEBUG=INFO log (and/or a pod-spec, ibstat, or all_reduce_perf output) and the bundled deterministic script verdicts whether RDMA is actually engaged, which of the three required conditions is missing, and the fix. Use when multi-node training is slow, when checking whether RDMA/InfiniBand is engaged, or when all-reduce bandwidth looks low. Trigger with "coreweave slow training", "is RDMA working", "NCCL fell back to TCP", "NET/Socket", "GPUDirect RDMA", "infiniband not used", "multi-node training slow".
About this listing
Category
General
Reported license
MIT
Listing language (estimated)
English
Review status
Not individually reviewed
Agent compatibility
Atlas installation supports Claude Code, Codex, and Cursor. Skill-specific dependencies and features are checked during setup.
Claude Code
Codex
Cursor
GitHub Copilot
Gemini CLI