Technology

34821 readers

17 users here now

This is the official technology community of Lemmy.ml for all news related to creation and use of technology, and to facilitate civil, meaningful discussion around it.

Ask in DM before posting product reviews or ads. All such posts otherwise are subject to removal.

Rules:

1: All Lemmy rules apply

2: Do not post low effort posts

3: NEVER post naziped*gore stuff

4: Always post article URLs or their archived version URLs as sources, NOT screenshots. Help the blind users.

5: personal rants of Big Tech CEOs like Elon Musk are unwelcome (does not include posts about their companies affecting wide range of people)

6: no advertisement posts unless verified as legitimate and non-exploitative/non-consumerist

7: crypto related posts, unless essential, are disallowed

founded 5 years ago

MODERATORS

[email protected]

New ROCm™ 5.6 Release Brings Enhancements and Optimizations for AI and HPC Workloads (community.amd.com)

submitted 1 year ago by [email protected] to c/[email protected]

2 comments fedilink hide all child comments

Huge news for AMD fans and those who are hoping to see a real* open alternative to CUDA that isn't OpenCL!

*: Intel doesn't count, they still have to get their shit together in rendering things correctly with their GPUs.

We plan to expand ROCm support from the currently supported AMD RDNA 2 workstation GPUs: the Radeon Pro v620 and w6800 to select AMD RDNA 3 workstation and consumer GPUs. Formal support for RDNA 3-based GPUs on Linux is planned to begin rolling out this fall, starting with the 48GB Radeon PRO W7900 and the 24GB Radeon RX 7900 XTX, with additional cards and expanded capabilities to be released over time.

you are viewing a single comment's thread
view the rest of the comments

[–] [email protected] 2 points 1 year ago

I've used ROCm for pytorch and stable diffusion. Using the pre-built docker images is definitely the way to go. Once setup, it's worked great for me.

You just have to understand that most projects are going to assume Nvidia (CUDA), so you'll have to jump through more hoops and still may not be able to do everything.