Join the conversation

Join the community of Machine Learners and AI enthusiasts.

Sign Up
badaouiΒ 
posted an update 8 days ago
Post
2288
432 GB of ultra-fast HBM4 and up to 23.3 TB/s of memory bandwidth on a single GPU 🀯.

Two weeks ago, we got early access to AMD's new Instinct MI455X, and our first goal was simple: make sure πŸ€— Transformers works on day one.

Over the past few weeks, we worked closely with the AMD team to validate the platform, enable Flash Attention, add torchcodec support for multimodal models, and resolve issues uncovered during testing.

The result:
βœ… 99.5% success rate across our 24 core Transformers model architectures - already on par with our daily CI on previous AMD and NVIDIA platforms.

The hardware is just as exciting. With 432 GB of HBM per GPU, our early capacity experiments showed more than 3Γ— the concurrent long-context requests compared to MI300, thanks to the much larger KV cache capacity.

A huge thanks to the AMD team for the early access and the great collaboration!

Read the full blog πŸ‘‡
https://huggingface.co/blog/badaoui/transformers-on-amd-mi455

3x the concurrent long-context requests from a bigger KV cache is a capacity number.

Whether it lands as 3x more served requests under a real workload depends on whether the scheduler can actually pack that many concurrent decode streams without stalling. KV cache room and scheduler throughput are different bottlenecks, and one can look fine while the other caps you.

Was the 3x measured as raw concurrent capacity, or under a fixed p99-latency SLO where scheduling overhead would also show up?