[V1] TPU Prototype

[robertgshaw2-neuralmagic]

SUMMARY:

• prototyping TPU on vLLM V1
• correctness pytest -s tests/entrypoints/openai/test_accuracy.py::test_lm_eval_accuracy_v1_engine
• nice speedups for cpu intensive workload vs V0 (33% on Qwen-1.5B on tpuv5e for sharegpt)

TODOS:

• refactor to share abstractions with GPU
• support sampling
• support prefix caching
• support naive chunked prefill
• harden testing
• tp > 1 (wait for tyler's PR first)

LONG TERM TODO:

• get a true variable length append kernel to enable chunked prefill

BENCHMARKS:

export MODEL=Qwen/Qwen2.5-1.5B-Instruct

• VLLM_USE_V1=1 , VLLM_ENABLE_V1_MULTIPROCESSING=1

VLLM_ENABLE_V1_MULTIPROCESSING=1 VLLM_USE_V1=1 python3 benchmarks/benchmark_throughput.py --model $MODEL --dataset benchmarks/ShareGPT_V3_unfiltered_cleaned_split.json --max-model-len 2048

# Throughput: 27.81 requests/s

• VLLM_USE_V1=1, VLLM_ENABLE_V1_MULTIPROCESSING=0

VLLM_ENABLE_V1_MULTIPROCESSING=0 VLLM_USE_V1=1 python3 benchmarks/benchmark_throughput.py --model $MODEL --dataset benchmarks/ShareGPT_V3_unfiltered_cleaned_split.json --max-model-len 2048

# Throughput: 25.98 requests/s

• VLLM_USE_V1=0

VLLM_USE_V1=0 python3 benchmarks/benchmark_throughput.py --model $MODEL --dataset benchmarks/ShareGPT_V3_unfiltered_cleaned_split.json --max-model-len 2048

# Throughput: 20.87 requests/s

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