mirror of
https://github.com/hpcaitech/ColossalAI.git
synced 2025-09-28 21:17:08 +00:00
86b63f720c
* adapted to the triton attn kernels * fix pad input * adapted to copy_kv_to_blocked_cache * fix ci test * update kv memcpy * remove print
34 lines
1.1 KiB
Bash
Executable File
34 lines
1.1 KiB
Bash
Executable File
ROOT=$(realpath $(dirname $0))
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PY_SCRIPT=${ROOT}/benchmark_llama.py
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GPU=$(nvidia-smi -L | head -1 | cut -d' ' -f4 | cut -d'-' -f1)
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mode=$1
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mkdir -p logs
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CUDA_VISIBLE_DEVICES_set_n_least_memory_usage() {
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local n=${1:-"9999"}
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echo "GPU Memory Usage:"
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local FIRST_N_GPU_IDS=$(nvidia-smi --query-gpu=memory.used --format=csv \
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| tail -n +2 \
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| nl -v 0 \
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| tee /dev/tty \
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| sort -g -k 2 \
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| awk '{print $1}' \
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| head -n $n)
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export CUDA_VISIBLE_DEVICES=$(echo $FIRST_N_GPU_IDS | sed 's/ /,/g')
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echo "Now CUDA_VISIBLE_DEVICES is set to:"
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echo "CUDA_VISIBLE_DEVICES=$CUDA_VISIBLE_DEVICES"
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}
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CUDA_VISIBLE_DEVICES_set_n_least_memory_usage 1
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# benchmark llama2-7b one single GPU
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for bsz in 16 32 64; do
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python3 ${PY_SCRIPT} -m llama2-7b --tp_size 1 --pp_size 1 -b $bsz -s 256 --output_len 128 --mode ${mode} | tee logs/${mode}_${GPU}_${bsz}_256.txt
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done
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for bsz in 16 32 64; do
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python3 ${PY_SCRIPT} -m llama2-7b --tp_size 1 --pp_size 1 -b $bsz -s 1024 --output_len 128 --mode ${mode} | tee logs/${mode}_${GPU}_${bsz}_1024.txt
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done
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