Arch Linux User Repository

I have created new packages for the ROCm technology preview release stream - currently ROCm 7.13.0. I assume with time they will be able (and forced) to replace the current opencl-amd-dev PKGBUILD.

• rocm-bin for Multi Arch
• rocm-gfx101x-bin for RDNA 1
• rocm-gfx103x-bin for RDNA 2
• rocm-gfx120x-bin for RDNA 4
• rocm-gfx110x-bin for RDNA 3
• rocm-gfx1150-bin for Ryzen AI - Strix Point
• rocm-gfx1151-bin for Ryzen AI Max -Strix Halo
• rocm-gfx1152-bin for Ryzen AI - Krackan Point

Latest release: 7.2.1. It uses 16.38GB of disk.

Issues with current release:

• libxml2-legacy is required by LLVM compiler.
• libamdpython.so is missing. Needs manual intervention for rocgdb to function.
• ROCm needs OpenCV libraries. Possible solution is install opencv then create symbolic links to the Arch Linux libraries.

https://www.reddit.com/r/Amd/comments/rd7mmi/heres_something_you_dont_see_every_day_pytorch/ as far as I can tell it should work on gfx1030, people are patching it to add support for other Navi GPUs. Could it be that pytorch installed from pip can't find ROCm stuff in /opt ? I'm not sure, I'm no expert.

There is an issue here that has some suggestions. I will try to take a better look later tonight.

I'm having the same error as you do. I think it's normal because ROCM doesn't support RDNA GPUs yet. I'm not 100% sure though, so I'm open to suggestions :)

You can verify that HIP is working though by running some samples in the package. /opt/rocm/hip/

This is my rocminfo:

ROCk module is loaded
=====================    
HSA System Attributes    
=====================    
Runtime Version:         1.1
System Timestamp Freq.:  1000.000000MHz
Sig. Max Wait Duration:  18446744073709551615 (0xFFFFFFFFFFFFFFFF) (timestamp count)
Machine Model:           LARGE                              
System Endianness:       LITTLE                             

==========               
HSA Agents               
==========               
*******                  
Agent 1                  
*******                  
  Name:                    AMD Ryzen 7 3700X 8-Core Processor 
  Uuid:                    CPU-XX                             
  Marketing Name:          AMD Ryzen 7 3700X 8-Core Processor 
  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:                      32768(0x8000) KB                   
  Chip ID:                 0(0x0)                             
  Cacheline Size:          64(0x40)                           
  Max Clock Freq. (MHz):   3600                               
  BDFID:                   0                                  
  Internal Node ID:        0                                  
  Compute Unit:            16                                 
  SIMDs per CU:            0                                  
  Shader Engines:          0                                  
  Shader Arrs. per Eng.:   0                                  
  WatchPts on Addr. Ranges:1                                  
  Features:                None
  Pool Info:               
    Pool 1                   
      Segment:                 GLOBAL; FLAGS: FINE GRAINED        
      Size:                    32848796(0x1f53b9c) KB             
      Allocatable:             TRUE                               
      Alloc Granule:           4KB                                
      Alloc Alignment:         4KB                                
      Accessible by all:       TRUE                               
    Pool 2                   
      Segment:                 GLOBAL; FLAGS: KERNARG, FINE GRAINED
      Size:                    32848796(0x1f53b9c) KB             
      Allocatable:             TRUE                               
      Alloc Granule:           4KB                                
      Alloc Alignment:         4KB                                
      Accessible by all:       TRUE                               
    Pool 3                   
      Segment:                 GLOBAL; FLAGS: COARSE GRAINED      
      Size:                    32848796(0x1f53b9c) KB             
      Allocatable:             TRUE                               
      Alloc Granule:           4KB                                
      Alloc Alignment:         4KB                                
      Accessible by all:       TRUE                               
  ISA Info:                
*******                  
Agent 2                  
*******                  
  Name:                    gfx1030                            
  Uuid:                    GPU-XX                             
  Marketing Name:          AMD Radeon RX 6900 XT              
  Vendor Name:             AMD                                
  Feature:                 KERNEL_DISPATCH                    
  Profile:                 BASE_PROFILE                       
  Float Round Mode:        NEAR                               
  Max Queue Number:        128(0x80)                          
  Queue Min Size:          4096(0x1000)                       
  Queue Max Size:          131072(0x20000)                    
  Queue Type:              MULTI                              
  Node:                    1                                  
  Device Type:             GPU                                
  Cache Info:              
    L1:                      16(0x10) KB                        
    L2:                      4096(0x1000) KB                    
    L3:                      131072(0x20000) KB                 
  Chip ID:                 29631(0x73bf)                      
  Cacheline Size:          64(0x40)                           
  Max Clock Freq. (MHz):   2660                               
  BDFID:                   2816                               
  Internal Node ID:        1                                  
  Compute Unit:            80                                 
  SIMDs per CU:            2                                  
  Shader Engines:          8                                  
  Shader Arrs. per Eng.:   2                                  
  WatchPts on Addr. Ranges:4                                  
  Features:                KERNEL_DISPATCH 
  Fast F16 Operation:      FALSE                              
  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                                 
  Pool Info:               
    Pool 1                   
      Segment:                 GLOBAL; FLAGS: COARSE GRAINED      
      Size:                    16760832(0xffc000) KB              
      Allocatable:             TRUE                               
      Alloc Granule:           4KB                                
      Alloc Alignment:         4KB                                
      Accessible by all:       FALSE                              
    Pool 2                   
      Segment:                 GROUP                              
      Size:                    64(0x40) KB                        
      Allocatable:             FALSE                              
      Alloc Granule:           0KB                                
      Alloc Alignment:         0KB                                
      Accessible by all:       FALSE                              
  ISA Info:                
    ISA 1                    
      Name:                    amdgcn-amd-amdhsa--gfx1030         
      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 ***      

I installed python 3.9 from the AUR package and then installed pytorch with the same command you posted but it is not working:

(venv) esistgut@nibiru:~/coding/python/fastai$ python --version
Python 3.9.9
(venv) esistgut@nibiru:~/coding/python/fastai$ cat asd.py 
import torch

if torch.opencl.is_available():
    device = torch.device("opencl")
else:
    device = torch.device("cpu")

print(device)
(venv) esistgut@nibiru:~/coding/python/fastai$ python asd.py 
"hipErrorNoBinaryForGpu: Unable to find code object for all current devices!"
Aborted (core dumped)

Hi @esistgut, Yes, it should provide all files necessary. However I don't have a supported GPU to test if everything works, so feel free to report your experience :)

Personally I've installed Python 3.9 which is necessary, then Pytorch by running the command:

python39 pip install --pre torch torchvision -f https://download.pytorch.org/whl/nightly/rocm4.2/torch_nightly.html

Hi, first off: thank you for your work. Can I ask if this provides support for the hip/rocm environment? I'm trying to use pytorch/rocm https://pytorch.org/get-started/locally/#linux-pip but installing it from the other Arch packages is too resource intensive so I'm looking for a way to install the prebuilt binary from AMD.