Problemsby IbisNVIDIA error messages are cryptic
Dev tooling2 posts from 2 people2d active+00 posts in the last 7 days, 1 the 7 days before (fading)Unverified
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The posts behind it
2, newest first[distributed] MemTracker memory accounting is CUDA-only: non-CUDA accelerators (NPU/XPU/MTIA) skip the 512-byte allocation rounding### 🐛 Describe the bug `_WeakRefInfo._calculate_mem_consumed` in `torch/distributed/_tools/mem_tracker.py` hardcodes the device check: `_PYTORCH_MIN_ALLOCATE` (512 bytes) is the minimum allocation granularity of the **caching allocator** - which is not CUDA-specific. All...pytorch/pytorch · wangdefeng1Open ↗"Waiting for resources" taking forever...nothing... is this normal? I tried changing from us-west to us-east, but not much luck. Any suggestions? Thanks!.r/googlecloud · u/InTakeJuanitoOpen ↗
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About this problem
Evidence
2 posts from 2 people in 2 places, about 2 a week over 6 days. Mostly on r/googlecloud, pytorch/pytorch. Tools named alongside: Google Cloud, PyTorch.
Frustration Frustration 0 of 3· Seen on Reddit, GitHub issues
How it was grouped
Posts that state a pain and match the "errors-unclear" rule about NVIDIA. First post Oct 7, 2026, latest Oct 12, 2026. Unverified: fewer than 3 posts, or one person or place only. Method
The same problem elsewhere
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Other NVIDIA problems
NVIDIA GPU access and drivers are painfulNVIDIA runs out of memoryNVIDIA users keep filing bugsNVIDIA vulnerabilities are hard to triage and patchRunning NVIDIA locally hits memory and speed limitsNVIDIA upgrades break working setupsTrouble with NVIDIA accountNVIDIA lock-in makes switching costlyTrouble with NVIDIA inductorTrouble with NVIDIA phoneFine-tuning NVIDIA is costly and unpredictableTrouble with NVIDIA careers
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NVIDIA error messages are cryptic (2 posts)