【昇腾】单张96G Atlas 300I Duo推理卡MindIE+WebUI方式跑32B大语言模型_20250818

【昇腾】单张96G Atlas 300I Duo推理卡MindIE+WebUI方式跑32B大语言模型_20250818

一、Atlas 300I Duo推理卡相关安装步骤

由于显存的瓶颈,48G的Atlas 300I Duo推理卡是没办法跑得起来DeepSeek-R1-Distill-Qwen-32B大语言模型的,这里换了一张96G版本的Atlas 300I Duo推理卡来跑,32B大语言模组除了对显存有要求,对服务器本身的内存条也有要求,在加载的过程中需要较大的内存,这里服务器的内存条内存为128GB

duo卡图.jpg

1.1 服务器系统与内核说明

服务器系统版本内核版本内存条内存
S5000CKylin V104.19.90-89.11.v2401.ky10.aarch64128GB

P.S.服务器安装好系统后先不要执行yum update -y更新,否则内核版本会从4.19.90-89.11升级到4.19.90-89.21,Atlas 300I Duo推理卡的driver包会安装失败

1.2 系统环境说明

本服务器IP地址:192.168.2.71
登录用户:root

新开一个 terminal ,执行以下命令确认是否有探到Atlas 300I Duo推理卡:

lspci |grep Huawei 

如有卡,回显信息是:
0000:01:00.0 Processing accelerators: Huawei Technologies Co., Ltd. Device d500 (rev 23)

uname-a

回显信息是:
Linux localhost.localdomain 4.19.90-89.11.v2401.ky10.aarch64 #1 SMP Thu Apr 25 18:20:10 CST 2024 aarch64 aarch64 aarch64 GNU/Linux

cat /etc/*release 

回显信息是:
Kylin Linux Advanced Server release V10 (Halberd)
DISTRIB_ID=Kylin
DISTRIB_RELEASE=V10
DISTRIB_CODENAME=Halberd
DISTRIB_DESCRIPTION=“Kylin V10”
DISTRIB_KYLIN_RELEASE=V10
DISTRIB_VERSION_TYPE=enterprise
DISTRIB_VERSION_MODE=normal
NAME=“Kylin Linux Advanced Server”
VERSION=“V10 (Halberd)”
ID=“kylin”
VERSION_ID=“V10”
PRETTY_NAME=“Kylin Linux Advanced Server V10 (Halberd)”
ANSI_COLOR=“0;31”

Kylin Linux Advanced Server release V10 (Halberd)

############################################################################################

1.3 准备安装驱动固件

1.3.1 新增HwHiAiUser用户
groupadd HwHiAiUser useradd-g HwHiAiUser -d /home/HwHiAiUser -m HwHiAiUser -s /bin/bash 
1.3.2 准备驱动与固件文件并安装

到网站 https://www.hiascend.com/hardware/firmware-drivers/community?product=2&model=17&cann=8.0.0.beta1&driver=Ascend+HDK+24.1.0 去下载

Ascend-hdk-310p-npu-driver_24.1.0.1_linux-aarch64.run
Ascend-hdk-310p-npu-firmware_7.5.0.5.220.run

将下载好安装文件,放到/root/work目录下:

cd /root/work chmod +x * 

参考《Atlas 中心推理卡 24.1.0 NPU驱动和固件安装指南 02.pdf》文档“2 物理机安装与卸载”章节中介绍的方法安装驱动与固件
因为Atlas 300I Duo推理卡是新采购回来的卡,本次安装为首次安装场景,需先安装驱动再安装固件
安装driver:

./Ascend-hdk-310p-npu-driver_24.1.0.1_linux-aarch64.run --check ./Ascend-hdk-310p-npu-driver_24.1.0.1_linux-aarch64.run --full

安装成功回显信息是:
Driver package installed successfully! The new version takes effect immediately.

安装firmware:

./Ascend-hdk-310p-npu-firmware_7.5.0.5.220.run --check ./Ascend-hdk-310p-npu-firmware_7.5.0.5.220.run --full

安装成功回显信息是:
Firmware package installed successfully! Reboot now or after driver installation for the installation/upgrade to take effect.

执行reboot命令重启
如果驱动固件安装正确,执行 npu-smi info命令探到信息如下:

1.npu-smi.png

以上驱动固件安装完毕
############################################################################################

二、安装docker

Kylin V10并没有自带docker命令,需自行安装,请参考:https://blog.ZEEKLOG.net/weixin_43273656/article/details/145469516

2.1 查看内核版本

uname -a 

回显信息是:
Linux localhost.localdomain 4.19.90-89.11.v2401.ky10.aarch64 #1 SMP Thu Apr 25 18:20:10 CST 2024 aarch64 aarch64 aarch64 GNU/Linux

2.2 查看内核参数

cat /proc/version 

回显信息是:
Linux version 4.19.90-89.11.v2401.ky10.aarch64 ([email protected]) (gcc version 7.3.0 (GCC)) #1 SMP Thu Apr 25 18:20:10 CST 2024

2.3 查看系统和内核的详细信息

hostnamectl 

回显信息是:
Static hostname: localhost.localdomain
Icon name: computer-server
Chassis: server
Machine ID: 889689ba3a9f48c4985c1519c2d8f553
Boot ID: 24cf07b36d6d4db69befaca323c4be93
Operating System: Kylin Linux Advanced Server V10 (Halberd)
Kernel: Linux 4.19.90-89.11.v2401.ky10.aarch64
Architecture: arm64

总结:需要下载aarch64的官方下载docker离线安装包,这里下载docker-27.2.0.tgz

2.4 将下载好安装文件,放到/root/work目录下,解压安装包

cd /root/work tar-zxvf docker-27.2.0.tgz 

2.5 移动 Docker 文件

mv /root/work/docker/* /usr/bin/ 

2.6 修改docker.service

vim /usr/lib/systemd/system/docker.service 

新增以下内容:
[Unit]
Description=Docker Application Container Engine
Documentation=https://docs.docker.com
After=network-online.target firewalld.service
Wants=network-online.target
[Service]
Type=notify
ExecStart=/usr/bin/dockerd
ExecReload=/bin/kill -s HUP $MAINPID
LimitNOFILE=infinity
LimitNPROC=infinity
TimeoutStartSec=0
Delegate=yes
KillMode=process
Restart=on-failure
StartLimitBurst=3
StartLimitInterval=60s
[Install]
WantedBy=multi-user.target

2.7 修改daemon.json文件

mkdir-p /etc/docker vim /etc/docker/daemon.json 

新增以下内容
{
“exec-opts”: [“native.cgroupdriver=systemd”],
“insecure-registries”: [
“http://172.31.192.88:81”,“http://111.51.123.456:2222”
]
}

2.8 运行守护进程,启动 Docker

dockerd 

2.9 docker 其他命令介绍

  • 启动
systemctl start docker 
  • 查看状态
systemctl status docker 
  • 设置开机自启动
systemctl enable docker 

reboot重启设备,并完成以下操作

三、安装与部署

3.1 拉取镜像

https://www.hiascend.com/developer/ascendhub/detail/af85b724a7e5469ebd7ea13c3439d48f
切到镜像版本页面,找到1.0.0-300I-Duo-py311-openeuler24.03-lts镜像点击下载,按指引将镜像拉取到服务器
3.1.1.docker login -u cn-south-1@HST3UBLG0X38GM0FMAGK swr.cn-south-1.myhuaweicloud.com
3.1.2.密码[d153e20f53b515e9f388f5bedf341c09b22b573e143c0cf33e1dd1f834535862]
3.1.3.docker pull swr.cn-south-1.myhuaweicloud.com/ascendhub/mindie:1.0.0-300I-Duo-py311-openeuler24.03-lts

拉取镜像完毕以后:
执行docker images
回显信息是:

2.png

3.2 新建容器

docker run -it -d --net=host --shm-size=1g
–privileged
–name sakway
-v /usr/local/Ascend/driver:/usr/local/Ascend/driver:ro
-v /usr/local/sbin:/usr/local/sbin:ro
-v /root/work:/root/work:rw
-v /path-to-weights:/path-to-weights:ro
swr.cn-south-1.myhuaweicloud.com/ascendhub/mindie:1.0.0-300I-Duo-py311-openeuler24.03-lts bash

3.3 查询正在运行的docker

[root@localhost work]# docker ps -a

3.png

3.4 进容器:

docker exec -it sakway bash

3.5 下载权重模型:

3.5.1 确保进docker以后:
cd /root/work/ 
3.5.2 安装modelscope命令:
pip install modelscope --index-url https://mirrors.huaweicloud.com/repository/pypi/simple/ 
3.5.3 下载权重:
modelscope download --model deepseek-ai/DeepSeek-R1-Distill-Qwen-32B 

将权重移动到/root/work/目录

mv /root/.cache/modelscope/hub/models/deepseek-ai/DeepSeek-R1-Distill-Qwen-32B /root/work/ 

将权重文件放在/root/work/目录以后,把x权限去掉,给添加config.json文件赋750权限

cd /root/work/ chmod750 /root/work/DeepSeek-R1-Distill-Qwen-32B/config.json 
vim /root/work/DeepSeek-R1-Distill-Qwen-32B/config.json 

将"torch_dtype": “bfloat16”,修改为"torch_dtype": “float16”,

vim /usr/local/Ascend/mindie/latest/mindie-service/conf/config.json 

有九处要修改,在/usr/local/Ascend/mindie/latest/mindie-service/conf/目录下有修改以后的config.json与原始的config.json_org,具体修改项可对比

{"Version":"1.1.0","LogConfig":{"logLevel":"Info","logFileSize":20,"logFileNum":20,"logPath":"logs/mindservice.log"},"ServerConfig":{"ipAddress":"192.168.2.71","managementIpAddress":"127.0.0.2","port":1040,"managementPort":1041,"metricsPort":1042,"allowAllZeroIpListening":false,"maxLinkNum":1000,"httpsEnabled":false,"fullTextEnabled":false,"tlsCaPath":"security/ca/","tlsCaFile":["ca.pem"],"tlsCert":"security/certs/server.pem","tlsPk":"security/keys/server.key.pem","tlsPkPwd":"security/pass/key_pwd.txt","tlsCrlPath":"security/certs/","tlsCrlFiles":["server_crl.pem"],"managementTlsCaFile":["management_ca.pem"],"managementTlsCert":"security/certs/management/server.pem","managementTlsPk":"security/keys/management/server.key.pem","managementTlsPkPwd":"security/pass/management/key_pwd.txt","managementTlsCrlPath":"security/management/certs/","managementTlsCrlFiles":["server_crl.pem"],"kmcKsfMaster":"tools/pmt/master/ksfa","kmcKsfStandby":"tools/pmt/standby/ksfb","inferMode":"standard","interCommTLSEnabled":true,"interCommPort":1121,"interCommTlsCaPath":"security/grpc/ca/","interCommTlsCaFiles":["ca.pem"],"interCommTlsCert":"security/grpc/certs/server.pem","interCommPk":"security/grpc/keys/server.key.pem","interCommPkPwd":"security/grpc/pass/key_pwd.txt","interCommTlsCrlPath":"security/grpc/certs/","interCommTlsCrlFiles":["server_crl.pem"],"openAiSupport":"vllm"},"BackendConfig":{"backendName":"mindieservice_llm_engine","modelInstanceNumber":1,"npuDeviceIds":[[0,1]],"tokenizerProcessNumber":8,"multiNodesInferEnabled":false,"multiNodesInferPort":1120,"interNodeTLSEnabled":true,"interNodeTlsCaPath":"security/grpc/ca/","interNodeTlsCaFiles":["ca.pem"],"interNodeTlsCert":"security/grpc/certs/server.pem","interNodeTlsPk":"security/grpc/keys/server.key.pem","interNodeTlsPkPwd":"security/grpc/pass/mindie_server_key_pwd.txt","interNodeTlsCrlPath":"security/grpc/certs/","interNodeTlsCrlFiles":["server_crl.pem"],"interNodeKmcKsfMaster":"tools/pmt/master/ksfa","interNodeKmcKsfStandby":"tools/pmt/standby/ksfb","ModelDeployConfig":{"maxSeqLen":2560,"maxInputTokenLen":2048,"truncation":false,"ModelConfig":[{"modelInstanceType":"Standard","modelName":"DeepSeek-R1-Distill-Qwen-32B","modelWeightPath":"/root/work/DeepSeek-R1-Distill-Qwen-32B","worldSize":2,"cpuMemSize":5,"npuMemSize":-1,"backendType":"atb","trustRemoteCode":false}]},"ScheduleConfig":{"templateType":"Standard","templateName":"Standard_LLM","cacheBlockSize":128,"maxPrefillBatchSize":50,"maxPrefillTokens":8192,"prefillTimeMsPerReq":150,"prefillPolicyType":0,"decodeTimeMsPerReq":50,"decodePolicyType":0,"maxBatchSize":200,"maxIterTimes":512,"maxPreemptCount":0,"supportSelectBatch":false,"maxQueueDelayMicroseconds":5000}}}

四、跑服务化(有个加载模型的过程需要点时间)

cd /usr/local/Ascend/mindie/latest/mindie-service/bin&&./mindieservice_daemon
成功标志:
Daemon start success!

4.1 命令行推理方式

新开一个terminal(问问题,可以不进docker)

curl 192.168.2.71:1040/generate -d ‘{
“prompt”: “请输出100个生僻字?”,
“max_tokens”: 32,
“stream”: false,
“do_sample”:true,
“repetition_penalty”: 1.00,
“temperature”: 0.01,
“top_p”: 0.001,
“top_k”: 1,
“model”: “qwen”
}’
大概3秒回答问题

五、MindIE+webUI方式

关闭防火墙(在docker外执行):
systemctl stop firewalld

安装webUI:
新开一个terminal,进docker:
docker exec -it sakway bash

cd /root/work/
pip install open-webui --index-url https://mirrors.huaweicloud.com/repository/pypi/simple/
这里open-webui的安装,大概需要十来分钟

安装成功后,到跑服务化的界面按Ctrl+C停止服务化进程(mindieservice_daemon):
vim /usr/local/Ascend/mindie/latest/mindie-service/conf/config.json
将"ipAddress" : “127.0.0.1”,修改为实际IP地址"ipAddress" : “192.168.2.71”,
如果已经是"ipAddress" : "192.168.2.71"则不需要再修改

启动Open-WebUI服务:
open-webui serve
成功标志:
有一个大的OPEN WEBUI的LOGO

新开一个terminal,进docker:
docker exec -it sakway bash
跑服务化(有个加载模型的过程需要点时间):
cd /usr/local/Ascend/mindie/latest/mindie-service/bin&&./mindieservice_daemon
成功标志:
Daemon start success!

在web浏览器中访问:
http://192.168.2.71:8080
点击开始使用

首次需要创建管理员账户:
名称:sakway
电子邮箱:[email protected]
密码:ABC123
点击创建管理员账户,此时会提示注册成功,已登录
点击确认,开始使用

点击右上角带颜色的圆圈图标(选择管理员面板)
点击上面那一排右边的设置
点击左侧的外部链接
将"管理OpenAI API连接"修改为实际的IP
https://api.openai.com/v1修改为http://192.168.2.71:1040/v1
点击该行最右边的"设置",点击刷新,在弹出的“编辑连接”页面中点击保存

新开一个浏览器在web上访问http://192.168.2.71:8080开启对话
该局域网内的其他的PC用户也可以在浏览器打开http://192.168.2.71:8080开启新对话

以上大语言模型顺利跑成功

跑成功0.jpg
跑成功1.jpg


############################################################################################

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