# Guide on Hyperparameter Tuning ## Achieving Peak Throughput Achieving a large batch size is the most important thing for attaining high throughput. When the server is running at full load, look for the following in the log: ```Decode batch. #running-req: 233, #token: 370959, token usage: 0.82, gen throughput (token/s): 4594.01, #queue-req: 417``` ### Tune Your Request Submission Speed `#queue-req` indicates the number of requests in the queue. If you frequently see `#queue-req == 0`, it suggests you are bottlenecked by the request submission speed. A healthy range for `#queue-req` is `50 - 1000`. On the other hand, do not make `#queue-req` too large because it will also increase the scheduling overhead on the server. ### Tune `--schedule-conservativeness` `token usage` indicates the KV cache memory utilization of the server. `token usage > 0.9` means good utilization. If you frequently see `token usage < 0.9` and `#queue-req > 0`, it means the server is too conservative about taking in new requests. You can decrease `--schedule-conservativeness` to a value like 0.3. The case of serving being too conservative can happen when users send many requests with a large `max_new_tokens` but the requests stop very early due to EOS or stop strings. On the other hand, if you see `token usage` very high and you frequently see warnings like `decode out of memory happened, #retracted_reqs: 1, #new_token_ratio: 0.9998 -> 1.0000`, you can increase `--schedule-conservativeness` to a value like 1.3. If you see `decode out of memory happened` occasionally but not frequently, it is okay. ### Tune `--dp-size` and `--tp-size` Data parallelism is better for throughput. When there is enough GPU memory, always favor data parallelism for throughput. ### Avoid out-of-memory by tuning `--chunked-prefill-size`, `--mem-fraction-static`, `--max-running-requests` If you see out of memory (OOM) errors, you can decrease these parameters. If OOM happens during prefill, try to decrease `--chunked-prefill-size` to `4096` or `2048`. If OOM happens during decoding, try to decrease `--max-running-requests`. You can also try to decrease `--mem-fraction-static`, which reduces the memory usage of the KV cache memory pool and helps both prefill and decoding. ### (Minor) Tune `--schedule-policy` If you have many shared prefixes, use the default `--schedule-policy lpm`. `lpm` stands for longest prefix match. When you have no shared prefixes at all or you always send the requests with the shared prefixes together, you can try `--schedule-policy fcfs`. `fcfs` stands for first come first serve.