Deploying RDMA for Distributed Inference and Training At Scale

cs.LG, cs.DC, cs.NI, cs.SY, eess.SY

Submitted: 2026-10-08

Updated: 2026-10-12

Comments: 14 pages, 16 figures

Code: https://github.com/mjansson/rpmalloc

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Sources

• Deep Learning Training in Facebook Data Centers: Design of Scale-up and Scale-out Systems

Related papers

• Polynomial-Augmented Neural Networks (PANNs) with Weak Orthogonality Constraints for Enhanced Function and PDE Approximation
• AIRL-S: Unifying Reinforcement Learning and Search-Based Test-Time Scaling via Adversarial Inverse Reinforcement Learning
• Transformers as Bayesian In-Context Experimenters: Smoothness-Adaptive Efficient ATE Estimation
• Convergence issues in Relational Concept Analysis based on AOC-posets
• Beliefs Beyond Posteriors: The Predictive Cost of ELBO Binding
• Understanding Diffusion Models via Ratio-Based Function Approximation with SignReLU Networks