Frank
500ac2b871
The "`--swap-space` is removed; use `--kv-offloading-size`" claim was carried by six pages, two of them with their own copy of the upstream source citation. It now lives only in [[RAM CPU Offloading in VLLM]], which carries the 2026-10-19 verification against `vllm/config/cache.py` (no `swap_space`; `kv_offloading_size` activates only with `kv_offloading_backend`): - `VLLM Overview` (two argument tables), `VLLM Index` (parameter table), `DFlash DSpark Speculative Decoding`, `Shared Memory Architecture Dankclaw`, `Hybrid CPU GPU Processing Dankserver` -> cite the owner. - `VLLM Index`'s example command used the dead flag; it now shows the live pair. - `dankserver-vram-growth`: banner disambiguates the 2026-08 `frank-zealot` (llama.cpp on the 3090 when that card was in Dankserver) from today's endpoint of the same name on Dankclaw, so a retired crash signature does not read as a live fault on a same-card-class service. Refs: vault de-dup campaign, clusters C2 and C6.
144 lines
6.6 KiB
Markdown
144 lines
6.6 KiB
Markdown
---
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type: reference
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title: Dankserver VRAM and RAM Growth Under Load
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description: Investigation of the recurring cuBLAS crash on frank-zealot. What grows, what does not, and what to do next.
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tags:
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- dankserver
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- llamacpp
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- vram
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- ram
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- ctx-checkpoints
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- crash
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timestamp: 2026-09-03
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---
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> **SUPERSEDED 2026-08-17.** The Frank redo retired this topology.
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> See [[frank-redo-2026-08-17]] and [[deployment]] for the active configuration.
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> The `frank-zealot` below is the 2026-08 service: llama.cpp on the RTX 3090
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> **while that card sat in Dankserver**. Today's [[frank-zealot]] is a different host
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> (Dankclaw), payload and runtime build, though the same card class - this crash
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> signature is not a live fault.
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# Dankserver VRAM and RAM Growth Under Load
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This page records the investigation of the recurring cuBLAS crash on
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`frank-zealot` (llama.cpp, RTX 3090 24 GiB). The service aborts
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with `CUDA error: an unsupported value or parameter was passed to the
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function` in `cublasSgemm_v2` at `ggml-cuda.cu:1541` during
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`update_slots` -> `decode` -> `process_ubatch`. It crashed on 2026-08-13
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at 19:45 and 19:55 and on 2026-08-14 at 12:00:43.
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## What Was Ruled Out
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### ctx-checkpoints do not grow VRAM
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`--ctx-checkpoints 4` stores context checkpoints in host RAM. The log
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records every checkpoint at exactly 62.813 MiB. The size never grows.
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The reasoning:
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- `common_prompt_checkpoint` (common/common.h) stores the serialized KV
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state in `std::vector<uint8_t>` fields. These live on the host heap.
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- `update_tgt()` and `update_dft()` call `llama_state_seq_get_data_ext`
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with `LLAMA_STATE_SEQ_FLAGS_PARTIAL_ONLY`. The serialized state moves
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from VRAM to RAM for the snapshot and back on restore.
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- With 4 slots and `--ctx-checkpoints 4`, the maximum checkpoint RAM is
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16 x 62.813 MiB, about 1.0 GiB. That is fixed and small.
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- `data_spec` (spec-decode state) is empty for ngram-mod. The ngram-mod
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implementation does not override `get_state()`.
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### ngram-mod does not grow VRAM
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ngram-mod allocates one fixed 64 MiB CPU hash table
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(`common_ngram_mod::entries`, 16M int32 entries). It never resizes. The
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matcher keeps about 12 bytes per sequence. Draft generation runs on the
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CPU. The speculative path allocates zero GPU memory.
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### The CUDA graph cache has eviction in this build
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`ggml_backend_cuda_context::cuda_graph()` sweeps every 5 seconds and
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evicts graphs unused for 10 seconds. Upstream issue #25082 describes an
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unbounded graph cache, but build b10108-13-g555881ebc includes the
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eviction sweep. This build does not exhibit that leak.
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## What Grows
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### RAM growth is suspected, not yet confirmed
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systemd reported MemoryPeak 46.9 GiB for the crashed process and 45.9
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GiB for the replacement. RSS is flat at 32.3 GiB, which matches the
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documented idle baseline of about 32 GiB. The difference is file-backed
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page cache from the `--no-mmap` model read; cgroup memory.current counts
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file pages attributed to the process. That gap is not proof of a leak by
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itself.
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The upstream pattern to watch is issue #26216: the prompt cache and
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checkpoint accumulation exceed the `--cache-ram` cap and do not plateau.
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The environment file does not set `--cache-ram`, so the llama.cpp
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default of 8192 MiB applies. The monitor logs RSS, which separates
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anonymous memory from file cache. If RSS climbs under load while VRAM is
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flat, the RAM-side accumulation is real.
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### VRAM suspects under load
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VRAM is flat at idle: 21,268 MiB across every monitor sample. The crash
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correlates with load density and slot context size (143K tokens on
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slot 2), not with wall-clock time. The two mechanisms worth testing:
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1. Flash-attention F16 K conversion workspace. The prefill kernel on
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Ampere is `MMA_F16`. It converts the quantized K cache (q8_0) to F16
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for the attention math. The workspace size scales with the attended
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context length (`ggml_nelements(K) x 2`). It is allocated into the
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graph buffer via `ggml_cuda_flash_attn_ext_get_alloc_size`.
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2. The CUDA VMM pool grows monotonically. `ggml_cuda_pool_vmm::alloc`
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only reserves more physical memory; `free` only releases the
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reservation slot. The pool never shrinks during the process
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lifetime. Any new peak allocation permanently expands VRAM usage.
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Both match the observed pattern: growth under prefill bursts at deep
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context, flat at idle, crash when a burst exceeds the ~2.8 GiB headroom.
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## Monitoring
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The monitor runs on Dankserver:
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```
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/home/dank/vram-monitor.sh
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/home/dank/vram-log.csv
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```
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It samples GPU VRAM and process RAM every 10 seconds and appends a CSV
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row. The columns are timestamp, uptime, GPU VRAM MiB, GPU utilization,
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process RSS, process VSZ, and systemd MemoryPeak.
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## Resolution: dual-f16 KV Cache (2026-08-14)
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The fix chose the first mechanism over the second. Both K and V moved to f16 on 2026-08-14. When K is already f16, the flash-attention MMA_F16 prefill kernel needs no F16 conversion copy, so the context-proportional workspace disappears. The pool becomes static: 20,480 bytes per cell (10 full-attention layers x 2 kv heads x 256 dims x 2 bytes for K plus 2 bytes for V).
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The pool at 800768 cells cost 15,640 MiB and did not fit. The load-time warmup graph (1472x1472 image) failed cudaMalloc by 248 MiB, and the service idled at 23,966 of 24,576 MiB. The context pool was refitted to 700416 cells (4 slots x 175104): KV pool 13,680 MiB, idle 22,110 MiB, about 2.0 GiB free after warmup. Parallel stays 4.
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Verified 2026-08-14 after deploy: flash attention enabled, warmup clean, decode about 42-44 t/s, cached prompt tokens working. The vram monitor log shows the restart arc (23,966 -> 5,210 during load -> 22,110 idle).
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## Mitigation Options
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The documentation for the benchmark ([[frank-zealot]])
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prescribes the first option for this crash class. None of these change
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the model.
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| Option | Effect | Cost |
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| ------ | ------ | ---- |
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| `GGML_CUDA_FORCE_MMQ=1` | Bypasses the cuBLAS path in the crashing function | Slight decode slowdown |
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| `--cache-ram 2048` | Bounds the confirmed RAM growth | Cache misses on prompt reuse |
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| `--ctx-checkpoints 2` | Cuts checkpoint RAM and save cost in half | More prefill work after eviction |
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| Apply PR #24649 | Clears slot checkpoints before the prompt-cache save | Needs a llama.cpp rebuild |
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Upstream references: issue #26216 (prompt cache growth), issue #25082
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(graph cache, not applicable to this build), issue #23635 (quantized KV
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with speculative decoding), PR #24649 (checkpoint-to-cache duplication),
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PR #25649 (slot checkpoints freed on prompt clear, merged), issue #26119
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(same cuBLAS signature, confirmed on V100 with speculative decoding).
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## See Also
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- [[frank-zealot]]
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- [[Dankserver System Specs]]
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- [[deployment]] |