Investigating Low-Parallelism Inference Performance in vLLM
Analysis
Key Takeaways
- •vLLM's performance is significantly lower than llama.cpp in low-parallelism requests.
- •PyTorch Profiler was used to identify performance bottlenecks in vLLM.
- •The investigation focuses on optimizing vLLM for resource-constrained environments.
“前回の記事ではAMD Ryzen AI Max+ 395でgpt-oss-20bをllama.cppとvLLMで推論させたときの性能と精度を評価した。”