Gahow Wang
ec73a95e05
Discrete-event simulator for evaluating KV cache-aware routing policies in prefill-disaggregated LLM serving clusters. Models a two-tier KV cache hierarchy (L0 GPU HBM + L1 CPU DRAM) with RDMA/PCIe link contention, architecture-derived roofline compute (MoE, MLA, DSA), and a cluster-wide meta-store for prefix-aware routing decisions. Includes 11 routing policies (random, round_robin, least_loaded, least_tokens, ttl_aware, precise, min_pd, cache_load, cache_score, estimated_ttft, prefix_affinity), HuggingFace config.json auto-parsing, built-in GPU hardware presets (H100/H800/H20/A100/B200), and ablation tooling for systematic policy comparison across real Alibaba serving traces. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
41 lines
1.3 KiB
YAML
41 lines
1.3 KiB
YAML
# GLM-5 using HuggingFace config.json + hardware preset.
|
|
#
|
|
# This config demonstrates the simplified format:
|
|
# model.config_json — loads architecture from HF config.json
|
|
# hardware.type — loads GPU specs from built-in preset
|
|
#
|
|
# Only deployment-specific fields need to be set explicitly.
|
|
# Any field from config_json or the preset can be overridden in YAML.
|
|
|
|
model:
|
|
# Auto-detect architecture: MoE, MLA, DSA, head dims, etc.
|
|
config_json: ../models/GLM-5/config.json
|
|
name: glm-5 # override HF model_type
|
|
dtype_bytes: 1 # BF16 (not in HF config.json)
|
|
block_size_tokens: 512 # matches bailian-traces blksz_512
|
|
|
|
hardware:
|
|
type: 8xb200 # 8 x B200 SXM (192GB each)
|
|
# Override preset values for this specific deployment:
|
|
hbm_bytes: 500.0e9 # KV budget after FP8 weights + activations
|
|
dram_bytes: 1.5e12 # ~1.5 TB usable CPU DRAM per node
|
|
max_batch_slots: 256
|
|
|
|
cluster:
|
|
num_instances: 32
|
|
meta_store:
|
|
ttl_seconds: 300.0
|
|
router:
|
|
mode: min_pd
|
|
precise_probe_latency_us: 50.0
|
|
precise_probe_topk: 4
|
|
load_alpha: 1.0
|
|
prefix_k: 8
|
|
|
|
sim:
|
|
trace_path: bailian-traces/glm_coder_blksz_512_040915-040917.jsonl
|
|
max_requests: null
|
|
output_dir: runs/glm5_8xb200_hf
|
|
sample_interval_s: 1.0
|
|
seed: 42
|