reasoning: raise num_cpu_blocks 32->256 for real DRAM KV offload capacity

32 blocks was a ~1GB safety-valve leftover from the num_cpu_blocks=2000
hang incident, not meaningful offload capacity. This model's KV cache is
~32MB/128-token block (64 layers, 8 KV heads x 128 head_dim, fp16) --
256 blocks gives ~8GB of real DRAM offload (32,768 tokens), comfortably
under the pod's 36Gi limit alongside the ~20GB bnb-4bit weights.
This commit is contained in:
Story Crater Bot
2026-08-19 18:42:37 -07:00
parent ea0c00f76e
commit 052f235d7b
+12 -10
View File
@@ -45,21 +45,23 @@ spec:
# to CPU DRAM instead of discarding them on preemption (max-num-seqs=4
# + max-model-len=16384 means concurrent long sequences compete for
# the same GPU KV space). No extra dependency, built into vLLM core.
# num_cpu_blocks=2000 hung the pod at startup ("Allocating 64 CPU
# tensors..." then nothing -- 64 is this model's layer count, one
# pinned host tensor per layer, each sized for every CPU block; 2000
# was oversized enough to stall pinning that much host memory, likely
# blowing well past the pod's memory limit). Dropped to a small,
# known-safe starting point -- confirm it actually comes up healthy,
# then watch real host memory usage and raise it deliberately rather
# than guessing a round number again. block_size=128 tokens matches
# vLLM's own example.
# num_cpu_blocks=2000 hung the pod at startup on the old model (2000 x
# ~32MB/block blew well past the pod's memory limit). num_cpu_blocks=32
# was the safe-recovery value after that -- only ~1GB of real DRAM
# (32 blocks x 128 tokens x 256KB/token-across-all-64-layers, fp16),
# basically a token-count safety valve, not real offload capacity.
# This model: 64 layers, 8 KV heads x 128 head_dim, fp16 -> ~256KB of
# KV per token across all layers -> ~32MB per 128-token block.
# num_cpu_blocks=256 -> ~8GB of actual DRAM offload (32,768 tokens),
# comfortably under the pod's 36Gi limit alongside the ~20GB bnb-4bit
# weights. Watch real host memory on boot before raising further --
# block_size=128 tokens matches vLLM's own example.
# Note: 0.11.0 ships the original (fragmented, small-transfer-block)
# version of this connector -- 0.12.0 consolidates KV data into one
# contiguous block per request and is reported an order of magnitude
# faster for this specific feature, so this is a real but not yet
# optimal implementation until the image gets bumped.
- --kv-transfer-config={"kv_connector":"OffloadingConnector","kv_role":"kv_both","kv_connector_extra_config":{"num_cpu_blocks":32,"block_size":128}}
- --kv-transfer-config={"kv_connector":"OffloadingConnector","kv_role":"kv_both","kv_connector_extra_config":{"num_cpu_blocks":256,"block_size":128}}
- --host=0.0.0.0
- --port=8080
env: