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Comment by cpburns2009 | Hacker News Reader

cpburns2009

Just a point of clarification. I believe the 128GB Strix Halo can only allocate up to 96GB of RAM to the GPU.

108 GB or so under Linux.

The BIOS allows pre-allocating 96 GB max, and I'm not sure if that's the maximum for Windows, but under Linux, you can use `amdttm.pages_limit` and `amdttm.page_pool_size` [1]

[1] https://www.jeffgeerling.com/blog/2025/increasing-vram-alloc...

I have been doing a couple of tests with pytorch allocations, it let me go as high as 120GB [1] (assuming the allocations were small enough) without crashing. The main limitation was mostly remaining system memory:

    htpc@htpc:~% free -h
                   total        used        free      shared  buff/cache   available
    Mem:           125Gi       123Gi       920Mi        66Mi       1.6Gi       1.4Gi
    Swap:           19Gi       4.0Ki        19Gi

[1] https://bpa.st/LZZQ

Thanks for the correction. I was under the impression the GPU memory had to be preallocated in the BIOS, and 96 GB was the maximum number I read about.

Some older software stacks require static allocation in BIOS, but things are moving pretty quickly and allow dynamic allocation. Newer versions (or patches to) pytorch, ollama, and related, which I think might depend on a newer kernel (6.13 or so). Does seem like there's been quite a bit of progress in the last month.

In Linux, you can allocate as much as you want with `ttm`:

In 4K pages for example:

    options ttm pages_limit=31457280
    options ttm page_pool_size=15728640

This will allow up to 120GB to be allocated and pre-allocate 60GB (you could preallocate none or all depending on your needs and fragmentation size. I believe `amdgpu.vm_fragment_size=9` (2MiB) is optimal.

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