# RCCLX: Innovating GPU Communications on AMD Platforms

DevFeed: [RCCLX: Innovating GPU Communications on AMD Platforms](<https://devfeed.tech/articles/rcclx-innovating-gpu-communications-on-amd-platforms-30493.md>)

Original publisher: [Read original article](<https://engineering.fb.com/2026/02/24/data-center-engineering/rrcclx-innovating-gpu-communications-amd-platforms-meta/>)

Author: Sudharssun Subramanian; Subodh Iyengar; Cen Zhao; Srinath Bayareddy; James Hongyi Zeng

Published: 2026-02-24T21:30:54Z

Content type: article

Language: en

Sources: [Meta AI Research](<https://devfeed.tech/sources/meta-ai-research.md>)

Topics: [GPU](<https://devfeed.tech/topics/gpu.md>), [Meta](<https://devfeed.tech/topics/meta.md>), [communications](<https://devfeed.tech/topics/communications.md>), [AI Models](<https://devfeed.tech/topics/ai-models.md>), [Latency](<https://devfeed.tech/topics/latency.md>), [Inference](<https://devfeed.tech/topics/inference.md>), [Large Language Model](<https://devfeed.tech/topics/llm.md>), [Transformer](<https://devfeed.tech/topics/transformer.md>)

Tags: [accelerate](<https://devfeed.tech/tags/accelerate.md>), [ai](<https://devfeed.tech/tags/ai.md>), [ai-models](<https://devfeed.tech/tags/ai-models.md>), [ai-research](<https://devfeed.tech/tags/ai-research.md>), [communications](<https://devfeed.tech/tags/communications.md>), [data-center-engineering](<https://devfeed.tech/tags/data-center-engineering.md>), [gpu](<https://devfeed.tech/tags/gpu.md>), [inference](<https://devfeed.tech/tags/inference.md>), [large-language-model](<https://devfeed.tech/tags/large-language-model.md>), [latency](<https://devfeed.tech/tags/latency.md>), [layer](<https://devfeed.tech/tags/layer.md>), [meta](<https://devfeed.tech/tags/meta.md>), [ml-applications](<https://devfeed.tech/tags/ml-applications.md>), [networking-traffic](<https://devfeed.tech/tags/networking-traffic.md>), [open-source](<https://devfeed.tech/tags/open-source.md>), [parallelism](<https://devfeed.tech/tags/parallelism.md>)

## AI overview

Meta describes the initial open-source release of RCCLX, an enhanced version of RCCL for AMD platforms integrated with Torchcomms. The article presents Direct Data Access algorithms and Low Precision Collectives, including approaches intended to reduce communication latency during large language model inference.

## Source excerpt

We are open-sourcing the initial version of RCCLX - an enhanced version of RCCL that we developed and tested on Meta's internal workloads. RCCLX is fully integrated with Torchcomms and aims to empower researchers and developers to accelerate innovation, regardless of their chosen backend. Communication patterns for AI models are constantly evolving, as are hardware [...] Read More... The post RCCLX: Innovating GPU Communications on AMD Platforms appeared first on Engineering at Meta.