File size: 4,333 Bytes
8efb28e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 | ### Server benchmark tools
Benchmark is using [k6](https://k6.io/).
##### Install k6 and sse extension
SSE is not supported by default in k6, you have to build k6 with the [xk6-sse](https://github.com/phymbert/xk6-sse) extension.
Example (assuming golang >= 1.21 is installed):
```shell
go install go.k6.io/xk6/cmd/xk6@latest
$GOPATH/bin/xk6 build master \
--with github.com/phymbert/xk6-sse
```
#### Download a dataset
This dataset was originally proposed in [vLLM benchmarks](https://github.com/vllm-project/vllm/blob/main/benchmarks/README.md).
```shell
wget https://huggingface.co/datasets/anon8231489123/ShareGPT_Vicuna_unfiltered/resolve/main/ShareGPT_V3_unfiltered_cleaned_split.json
```
#### Download a model
Example for PHI-2
```shell
../../../scripts/hf.sh --repo ggml-org/models --file phi-2/ggml-model-q4_0.gguf
```
#### Start the server
The server must answer OAI Chat completion requests on `http://localhost:8080/v1` or according to the environment variable `SERVER_BENCH_URL`.
Example:
```shell
llama-server --host localhost --port 8080 \
--model ggml-model-q4_0.gguf \
--cont-batching \
--metrics \
--parallel 8 \
--batch-size 512 \
--ctx-size 4096 \
-ngl 33
```
#### Run the benchmark
For 500 chat completions request with 8 concurrent users during maximum 10 minutes, run:
```shell
./k6 run script.js --duration 10m --iterations 500 --vus 8
```
The benchmark values can be overridden with:
- `SERVER_BENCH_URL` server url prefix for chat completions, default `http://localhost:8080/v1`
- `SERVER_BENCH_N_PROMPTS` total prompts to randomly select in the benchmark, default `480`
- `SERVER_BENCH_MODEL_ALIAS` model alias to pass in the completion request, default `my-model`
- `SERVER_BENCH_MAX_TOKENS` max tokens to predict, default: `512`
- `SERVER_BENCH_DATASET` path to the benchmark dataset file
- `SERVER_BENCH_MAX_PROMPT_TOKENS` maximum prompt tokens to filter out in the dataset: default `1024`
- `SERVER_BENCH_MAX_CONTEXT` maximum context size of the completions request to filter out in the dataset: prompt + predicted tokens, default `2048`
Note: the local tokenizer is just a string space split, real number of tokens will differ.
Or with [k6 options](https://k6.io/docs/using-k6/k6-options/reference/):
```shell
SERVER_BENCH_N_PROMPTS=500 k6 run script.js --duration 10m --iterations 500 --vus 8
```
To [debug http request](https://k6.io/docs/using-k6/http-debugging/) use `--http-debug="full"`.
#### Metrics
Following metrics are available computed from the OAI chat completions response `usage`:
- `llamacpp_tokens_second` Trend of `usage.total_tokens / request duration`
- `llamacpp_prompt_tokens` Trend of `usage.prompt_tokens`
- `llamacpp_prompt_tokens_total_counter` Counter of `usage.prompt_tokens`
- `llamacpp_completion_tokens` Trend of `usage.completion_tokens`
- `llamacpp_completion_tokens_total_counter` Counter of `usage.completion_tokens`
- `llamacpp_completions_truncated_rate` Rate of completions truncated, i.e. if `finish_reason === 'length'`
- `llamacpp_completions_stop_rate` Rate of completions stopped by the model, i.e. if `finish_reason === 'stop'`
The script will fail if too many completions are truncated, see `llamacpp_completions_truncated_rate`.
K6 metrics might be compared against [server metrics](../README.md), with:
```shell
curl http://localhost:8080/metrics
```
### Using the CI python script
The `bench.py` script does several steps:
- start the server
- define good variable for k6
- run k6 script
- extract metrics from prometheus
It aims to be used in the CI, but you can run it manually:
```shell
LLAMA_SERVER_BIN_PATH=../../../cmake-build-release/bin/llama-server python bench.py \
--runner-label local \
--name local \
--branch `git rev-parse --abbrev-ref HEAD` \
--commit `git rev-parse HEAD` \
--scenario script.js \
--duration 5m \
--hf-repo ggml-org/models \
--hf-file phi-2/ggml-model-q4_0.gguf \
--model-path-prefix models \
--parallel 4 \
-ngl 33 \
--batch-size 2048 \
--ubatch-size 256 \
--ctx-size 4096 \
--n-prompts 200 \
--max-prompt-tokens 256 \
--max-tokens 256
```
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