首先，确保AMD显卡被识别，使用命令DRI_PRIME=1 glxinfo | grep "OpenGL renderer"输出如代码块所示。
如果不存在glxinfo命令，可以安装它sudo apt install glxinfo
ikewendy@likewendy-PC:~$ DRI_PRIME=1 glxinfo | grep "OpenGL renderer"
OpenGL renderer string: AMD Radeon RX 7600M XT (radeonsi, navi33, LLVM 17.0.6, DRM 3.54, 6.6.47-amd64-desktop-hwe)
然后，使用AMD给的docker镜像，这样可以确保环境是可靠的，且不用安装rocm。
不过镜像比较大，预估10G左右。
拉取镜像并创建携带参数 --rm 的docker, 即插即用。
⚠️携带了 --rm参数旨在测试cuda是否可用，不要添加任何你的代码文件进去，退出bash容器就会销毁。
docker run -it --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --device=/dev/kfd --device=/dev/dri --group-add video --ipc=host --shm-size 8G --rm rocm/pytorch:latest
然后进入交互式python测试显卡是否正常工作
likewendy@likewendy-PC:~$ docker run -it --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --device=/dev/kfd --device=/dev/dri --group-add video --ipc=host --shm-size 8G --rm rocm/pytorch:latest
root@321932035db4:/var/lib/jenkins# python
Python 3.10.15 (main, Oct 3 2024, 07:27:34) [GCC 11.2.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import torch
>>> torch.cuda.is_available()
True
>>> exit()
root@321932035db4:/var/lib/jenkins# exit
exit
likewendy@likewendy-PC:~$
如果不能请留言。如代码块所示，我的可以。
能正常工作之后，就可以创建用于深度学习的容器了
这是我的：
docker run -d \
--name xxx \ #容器名
--cap-add=SYS_PTRACE \
--security-opt seccomp=unconfined \
--device=/dev/kfd \
--device=/dev/dri \
--group-add video \
--ipc=host \
--shm-size 8G \
-v "$HOME/Desktop/深度学习/dataset":/root/dataset:ro \ # ro 只读
-v "$HOME/Desktop/xxx":/root \
--network host \
rocm/pytorch:latest \
tail -f /dev/null
rocm还有一些好玩的命令
root@likewendy-PC:~# rocminfo
ROCk module is loaded
=====================
HSA System Attributes
=====================
Runtime Version: 1.14
Runtime Ext Version: 1.6
System Timestamp Freq.: 1000.000000MHz
Sig. Max Wait Duration: 18446744073709551615 (0xFFFFFFFFFFFFFFFF) (timestamp count)
Machine Model: LARGE
System Endianness: LITTLE
Mwaitx: DISABLED
DMAbuf Support: YES
==========
HSA Agents
==========
*******
Agent 1
*******
Name: 13th Gen Intel(R) Core(TM) i9-13900H
Uuid: CPU-XX
Marketing Name: 13th Gen Intel(R) Core(TM) i9-13900H
Vendor Name: CPU
Feature: None specified
Profile: FULL_PROFILE
Float Round Mode: NEAR
Max Queue Number: 0(0x0)
Queue Min Size: 0(0x0)
Queue Max Size: 0(0x0)
Queue Type: MULTI
Node: 0
Device Type: CPU
Cache Info:
L1: 49152(0xc000) KB
Chip ID: 0(0x0)
ASIC Revision: 0(0x0)
Cacheline Size: 64(0x40)
Max Clock Freq. (MHz): 5200
BDFID: 0
Internal Node ID: 0
Compute Unit: 20
SIMDs per CU: 0
Shader Engines: 0
Shader Arrs. per Eng.: 0
WatchPts on Addr. Ranges:1
Memory Properties:
Features: None
Pool Info:
Pool 1
Segment: GLOBAL; FLAGS: FINE GRAINED
Size: 32576660(0x1f11494) KB
Allocatable: TRUE
Alloc Granule: 4KB
Alloc Recommended Granule:4KB
Alloc Alignment: 4KB
Accessible by all: TRUE
Pool 2
Segment: GLOBAL; FLAGS: KERNARG, FINE GRAINED
Size: 32576660(0x1f11494) KB
Allocatable: TRUE
Alloc Granule: 4KB
Alloc Recommended Granule:4KB
Alloc Alignment: 4KB
Accessible by all: TRUE
Pool 3
Segment: GLOBAL; FLAGS: COARSE GRAINED
Size: 32576660(0x1f11494) KB
Allocatable: TRUE
Alloc Granule: 4KB
Alloc Recommended Granule:4KB
Alloc Alignment: 4KB
Accessible by all: TRUE
ISA Info:
*******
Agent 2
*******
Name: gfx1102
Uuid: GPU-XX
Marketing Name: AMD Radeon™ RX 7600M XT
Vendor Name: AMD
Feature: KERNEL_DISPATCH
Profile: BASE_PROFILE
Float Round Mode: NEAR
Max Queue Number: 128(0x80)
Queue Min Size: 64(0x40)
Queue Max Size: 131072(0x20000)
Queue Type: MULTI
Node: 1
Device Type: GPU
Cache Info:
L1: 32(0x20) KB
L2: 2048(0x800) KB
Chip ID: 29824(0x7480)
ASIC Revision: 0(0x0)
Cacheline Size: 64(0x40)
Max Clock Freq. (MHz): 2330
BDFID: 1536
Internal Node ID: 1
Compute Unit: 32
SIMDs per CU: 2
Shader Engines: 2
Shader Arrs. per Eng.: 2
WatchPts on Addr. Ranges:4
Coherent Host Access: FALSE
Memory Properties:
Features: KERNEL_DISPATCH
Fast F16 Operation: TRUE
Wavefront Size: 32(0x20)
Workgroup Max Size: 1024(0x400)
Workgroup Max Size per Dimension:
x 1024(0x400)
y 1024(0x400)
z 1024(0x400)
Max Waves Per CU: 32(0x20)
Max Work-item Per CU: 1024(0x400)
Grid Max Size: 4294967295(0xffffffff)
Grid Max Size per Dimension:
x 4294967295(0xffffffff)
y 4294967295(0xffffffff)
z 4294967295(0xffffffff)
Max fbarriers/Workgrp: 32
Packet Processor uCode:: 232
SDMA engine uCode:: 18
IOMMU Support:: None
Pool Info:
Pool 1
Segment: GLOBAL; FLAGS: COARSE GRAINED
Size: 8372224(0x7fc000) KB
Allocatable: TRUE
Alloc Granule: 4KB
Alloc Recommended Granule:2048KB
Alloc Alignment: 4KB
Accessible by all: FALSE
Pool 2
Segment: GLOBAL; FLAGS: EXTENDED FINE GRAINED
Size: 8372224(0x7fc000) KB
Allocatable: TRUE
Alloc Granule: 4KB
Alloc Recommended Granule:2048KB
Alloc Alignment: 4KB
Accessible by all: FALSE
Pool 3
Segment: GLOBAL; FLAGS: FINE GRAINED
Size: 8372224(0x7fc000) KB
Allocatable: TRUE
Alloc Granule: 4KB
Alloc Recommended Granule:2048KB
Alloc Alignment: 4KB
Accessible by all: FALSE
Pool 4
Segment: GROUP
Size: 64(0x40) KB
Allocatable: FALSE
Alloc Granule: 0KB
Alloc Recommended Granule:0KB
Alloc Alignment: 0KB
Accessible by all: FALSE
ISA Info:
ISA 1
Name: amdgcn-amd-amdhsa--gfx1102
Machine Models: HSA_MACHINE_MODEL_LARGE
Profiles: HSA_PROFILE_BASE
Default Rounding Mode: NEAR
Default Rounding Mode: NEAR
Fast f16: TRUE
Workgroup Max Size: 1024(0x400)
Workgroup Max Size per Dimension:
x 1024(0x400)
y 1024(0x400)
z 1024(0x400)
Grid Max Size: 4294967295(0xffffffff)
Grid Max Size per Dimension:
x 4294967295(0xffffffff)
y 4294967295(0xffffffff)
z 4294967295(0xffffffff)
FBarrier Max Size: 32
*** Done ***
root@likewendy-PC:~# rocm-smi
======================================== ROCm System Management Interface ========================================
================================================== Concise Info ==================================================
Device Node IDs Temp Power Partitions SCLK MCLK Fan Perf PwrCap VRAM% GPU%
(DID, GUID) (Edge) (Avg) (Mem, Compute, ID)
==================================================================================================================
0 1 0x7480, 48769 27.0°C 2.0W N/A, N/A, 0 0Mhz 96Mhz 29.8% auto 120.0W 0% 0%
==================================================================================================================
============================================== End of ROCm SMI Log ===============================================
root@likewendy-PC:~/kolors_data_set_search_demo#
另外，如果你是因为“AMD Yes”购买了搭载AMD显卡的学妹，可以加我微信。
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