Sudharssun integrated the RCClx backend into the facebookresearch/param repository’s communication framework, expanding distributed processing capabilities in PyTorch. By updating the backend selection logic and adding targeted param bench tests for RCClx, Sudharssun enabled broader backend support and improved test coverage, which helps reduce production risk. The work focused on backend development and distributed computing, leveraging Python and PyTorch to ensure seamless integration and maintainability. Although the contribution was limited to a single feature over one month, the implementation addressed a specific need for enhanced backend flexibility in distributed environments, demonstrating a focused and technically sound approach to extending existing infrastructure.