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build: rename main → llama-cli, server → llama-server, llava-cli → llama-llava-cli, etc... (#7809) 
* `main`/`server`: rename to `llama` / `llama-server` for consistency w/ homebrew

* server: update refs -> llama-server

gitignore llama-server

* server: simplify nix package

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fix examples/main ref

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* main: target name -> llama-cli

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* add/fix gbnf-validator subfolder to cmake

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This reverts commit e474ef1df4.

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---------

Co-authored-by: HanClinto <hanclinto@gmail.com>
2024-06-13 00:41:52 +01:00
..
batched-bench.cpp common : refactor cli arg parsing (#7675) 2024-06-04 21:23:39 +03:00
CMakeLists.txt build: rename main → llama-cli, server → llama-server, llava-cli → llama-llava-cli, etc... (#7809) 2024-06-13 00:41:52 +01:00
README.md build: rename main → llama-cli, server → llama-server, llava-cli → llama-llava-cli, etc... (#7809) 2024-06-13 00:41:52 +01:00

README.md

llama.cpp/example/batched-bench

Benchmark the batched decoding performance of llama.cpp

Usage

There are 2 modes of operation:

  • prompt not shared - each batch has a separate prompt of size PP (i.e. N_KV = B*(PP + TG))
  • prompt is shared - there is a common prompt of size PP used by all batches (i.e. N_KV = PP + B*TG)
./llama-batched-bench -m model.gguf -c 2048 -b 2048 -ub 512 -npp 128,256,512 -ntg 128,256 -npl 1,2,4,8,16,32 [-pps]

# LLaMA 7B, F16, N_KV_MAX = 16384 (8GB), prompt not shared
./llama-batched-bench -m ./models/llama-7b/ggml-model-f16.gguf -c 16384 -b 2048 -ub 512 -ngl 99

# LLaMA 7B, Q8_0, N_KV_MAX = 16384 (8GB), prompt is shared
./llama-batched-bench -m ./models/llama-7b/ggml-model-q8_0.gguf -c 16384 -b 2048 -ub 512 -ngl 99 -pps

# custom set of batches
./llama-batched-bench -m ./models/llama-7b/ggml-model-q8_0.gguf -c 2048 -b 512 -ub 512 -ngl 999 -npp 128,256,512 -ntg 128,256 -npl 1,2,4,8,16,32

Sample results

  • PP - prompt tokens per batch
  • TG - generated tokens per batch
  • B - number of batches
  • N_KV - required KV cache size
  • T_PP - prompt processing time (i.e. time to first token)
  • S_PP - prompt processing speed ((B*PP)/T_PP or PP/T_PP)
  • T_TG - time to generate all batches
  • S_TG - text generation speed ((B*TG)/T_TG)
  • T - total time
  • S - total speed (i.e. all tokens / total time)
PP TG B N_KV T_PP s S_PP t/s T_TG s S_TG t/s T s S t/s
128 128 1 256 0.108 1186.64 3.079 41.57 3.187 80.32
128 128 2 512 0.198 1295.19 5.029 50.90 5.227 97.95
128 128 4 1024 0.373 1373.96 6.878 74.44 7.251 141.23
128 128 8 2048 0.751 1363.27 7.344 139.43 8.095 252.99
128 128 16 4096 1.570 1304.68 8.455 242.23 10.024 408.60
128 128 32 8192 3.408 1201.73 8.801 465.40 12.209 670.96
128 256 1 384 0.107 1196.70 6.329 40.45 6.436 59.67
128 256 2 768 0.194 1317.45 10.239 50.00 10.433 73.61
128 256 4 1536 0.366 1399.03 13.960 73.35 14.326 107.22
128 256 8 3072 0.751 1363.92 15.110 135.54 15.861 193.69
128 256 16 6144 1.569 1304.93 18.073 226.64 19.642 312.80
128 256 32 12288 3.409 1201.35 19.223 426.15 22.633 542.93