diff --git a/README.md b/README.md
index 8d2ebc601e..f11d12c525 100644
--- a/README.md
+++ b/README.md
@@ -359,6 +359,10 @@ python -m sglang.launch_server --model-path meta-llama/Llama-2-7b-chat-hf --port
 ```
 python -m sglang.launch_server --model-path meta-llama/Llama-2-7b-chat-hf --port 30000 --tp 2
 ```
+- Add `--dp 2` to enable data parallelism. It can also be used together with tp. Data parallelism is better for throughput if there is enough memory.
+```
+python -m sglang.launch_server --model-path meta-llama/Llama-2-7b-chat-hf --port 30000 --dp 2 --tp 2
+```
 - If you see out-of-memory errors during serving, please try to reduce the memory usage of the KV cache pool by setting a smaller value of `--mem-fraction-static`. The default value is `0.9`
 ```
 python -m sglang.launch_server --model-path meta-llama/Llama-2-7b-chat-hf --port 30000 --mem-fraction-static 0.7
diff --git a/docs/hyperparameter_tuning.md b/docs/hyperparameter_tuning.md
new file mode 100644
index 0000000000..8246374305
--- /dev/null
+++ b/docs/hyperparameter_tuning.md
@@ -0,0 +1,30 @@
+# 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:
+```[gpu_id=0] #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 `100 - 3000`.
+
+### 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 0.5.
+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.
+
+### Tune `--dp-size` and `--tp-size`
+Data parallelism is better for throughput. When there is enough GPU memory, always favor data parallelism for throughput.
+
+### (Minor) Tune `--schedule-heuristic`
+If you have many shared prefixes, use the default `--schedule-heuristic lpm`. `lpm` stands for longest prefix match.
+When you have no shared prefixes at all, you can try `--schedule-heuristic fcfs`. `fcfs` stands for first come first serve.
+
+### (Minor) Tune `--max-prefill-tokens`, `--mem-fraction-static`, `--max-running-requests`.
+If you see out of memory errors, you can decrease them. Otherwise, the default value should work well.
\ No newline at end of file