tzhouamandClaude Opus 5
3834de3105
Renamed from vllm-embedding: nothing here is about embeddings, and the name had come from the parent working directory. edge-infer says what it does. The GitHub repository is renamed to match; nothing had been pushed yet. The audit found the packaging was incomplete in two ways. Scripts: 56 of them produced results that are published in this repo but were not included, so the numbers could be read and not checked. Added under benchmarks/edge_harness/experiments/ (one-off drivers: the AI Hub on-device runs, the 4-bit GEMM microbenchmark, fidelity and parity checks, checkpoint build and round-trip, activation capture, and the load generator used to prove the contention guard actually refuses) and benchmarks/edge_harness/runs/ (the 24 shell drivers behind published grids). Both directories carry a README saying plainly that they are a record of what was run rather than a supported interface -- most hardcode absolute paths from the machine they ran on. The supported entry points remain the tools one level up. One broken relative link fixed (comparison.md is under docs/engines/, not docs/analysis/). All other links and every script reference in the docs now resolve inside the repo. Secret scan: the token in ~/.qai_hub/client.ini is absent from the worktree and from all 61 commits. Worth noting that an earlier version of my own check reported a false positive, because `grep -rl ... | head` takes its exit status from head, which always succeeds -- the same class of mistake as the measurement errors this project keeps recording. The AI Hub scripts authenticate by reading that file at runtime and contain no credential. README reframed for the new name and the wider scope: the repository is the engine changes, the harness, the raw results, the baselines and the analyses, not just a patch set. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01L1ax5wYLA6XbqEL1i8L9gZ
39 lines
1.7 KiB
Bash
Executable File
39 lines
1.7 KiB
Bash
Executable File
#!/bin/bash
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# Init time and memory, the two things that decide whether this can be served
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# from an edge box. Sequential; each row changes exactly one thing.
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set -u
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HERE=/data/zhoutaichang/embedding_infer/analysis/experiments/spark_edge
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V=/data/zhoutaichang/embedding_infer/.venvs/omni-cpu
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M=/data/zhoutaichang/embedding_infer/models/spark2_5-gptq-g128
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SCRATCH=/tmp/claude-2005/-data-zhoutaichang-embedding-infer/e695f57b-0163-4287-b1be-1d0ec9330768/scratchpad
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OUT=$HERE/init_memory.jsonl
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CORES=32-55; T=24
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cd $HERE
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run () { # tag cache_root shim kv_gib max_len
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VLLM_CACHE_ROOT=$2 VLLM_OMNI_AOT_CACHE_SHIM=$3 VLLM_CPU_KVCACHE_SPACE=$4 \
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VLLM_OMNI_SPARK_GATE_REDUCTION=1 VLLM_OMNI_CPU_FUSED_NORMS=0 \
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KMP_BLOCKTIME=infinite OMP_WAIT_POLICY=active \
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LD_PRELOAD="$V/lib/python3.12/site-packages/vllm/libs/libtcmalloc_minimal.so.4:$V/lib/libiomp5.so" \
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CUDA_VISIBLE_DEVICES= VLLM_TARGET_DEVICE=cpu VLLM_ENABLE_V1_MULTIPROCESSING=0 \
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OMP_NUM_THREADS=$T VLLM_CPU_OMP_THREADS_BIND=$CORES \
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taskset -c $CORES timeout 1800 $V/bin/python bench_init_memory.py --model $M \
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--tag "$1" --max-model-len $5 --out $OUT 2>&1 \
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| grep -E '"(tag|init_s|rss_mb|rss_peak_mb|tokens_generated|kvcache|aot_shim)"'
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}
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FRESH=$SCRATCH/vllm_cache_fresh_$$
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rm -rf $FRESH
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echo "#### 1. cold cache, shim on"
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run "cold-shim-on" $FRESH 1 4 2048
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echo "#### 2. warm cache, shim on (the point of the shim)"
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run "warm-shim-on" $FRESH 1 4 2048
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echo "#### 3. warm cache, shim OFF (vLLM recompiles: the bug)"
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run "warm-shim-off" $FRESH 0 4 2048
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echo "#### 4. warm, shim on, KV sized to the context instead of 4 GiB"
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run "warm-kv-0.25" $FRESH 1 0.25 2048
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echo "#### 5. warm, shim on, KV 0.25 GiB and 1k context"
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run "warm-kv-0.25-1k" $FRESH 1 0.25 1024
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rm -rf $FRESH
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echo "#### INIT MEMORY DONE"
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