5 papers · 1 filter
Accelerating RL Post-Training Rollouts via System-Integrated Speculative Decoding
Hayate Iso, Tiyasa Mitra, Sudipta Mondal +15
RL post-training of frontier language models is increasingly bottlenecked by autoregressive rollout generation, making rollout acceleration a central systems challenge. Many existi…
Nemotron 3 Super: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic Reasoning
NVIDIA, :, Aakshita Chandiramani +544
We describe the pre-training, post-training, and quantization of Nemotron 3 Super, a 120 billion (active 12 billion) parameter hybrid Mamba-Attention Mixture-of-Experts model. Nemo…
LatentMoE: Toward Optimal Accuracy per FLOP and Parameter in Mixture of Experts
Venmugil Elango, Nidhi Bhatia, Roger Waleffe +13
Mixture of Experts (MoEs) have become a central component of many state-of-the-art open-source and proprietary large language models. Despite their widespread adoption, it remains…
ATTENTION2D: Communication Efficient Distributed Self-Attention Mechanism
Venmugil Elango
Transformer-based models have emerged as a leading architecture for natural language processing, natural language generation, and image generation tasks. A fundamental element of t…
PaSE: Parallelization Strategies for Efficient DNN Training
Venmugil Elango
Training a deep neural network (DNN) requires substantial computational and memory requirements. It is common to use multiple devices to train a DNN to reduce the overall training…