arxiv arXiv cs.LG · 53d ago · src: 54d ago · research

MGUP: Momentum-Gradient Alignment for Selective Optimization

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MGUP introduces a selective update mechanism that applies larger step-sizes to a fixed proportion of parameters in stochastic optimization, while using smaller, non-zero step-sizes for the rest. It integrates seamlessly with optimizers like AdamW, Lion, and Muon, providing theoretical convergence guarantees for MGUP-AdamW and demonstrating superior or more stable performance in training large language models and MAE pretraining tasks.

Importance 2/3 New harness with differentiators arXiv cs.LG Microsoft Research NVIDIA OpenAI Inference efficiency Research paper Training methods

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arxiv arXiv cs.LG · 52d ago

FoMoE Breaks Full-Replica Barrier with Partitioned Expert Layers

FoMoE introduces a system that partitions expert layers across workers to avoid full model replicas, reducing communication costs by up to 1.42x over baselines and 45.44x over DDP. It achieves up to 1.4x throughput speedups via a skip-token mechanism and demonstrates stable routing, with projected benefits extending to 100B-scale models through system modeling.

media r/LocalLLaMA · 50d ago · 3 views

Fixing Long-Context Decode Cliff on Radeon R9700 with vLLM 0.22.1

A long-context decode performance cliff on AMD Radeon AI PRO R9700 (RDNA4) was resolved by enabling AITER Unified Attention in vLLM 0.22.1. The fix involves relaxing a CDNA gate to include RDNA4, disabling other attention backends, and using bf16 KV cache, resulting in significant speedups across all context lengths. FP8 KV is ineffective on this hardware, and the model's native 262K context is fully achievable with bf16, offering ~2.9× concurrency without needing FP8.

arxiv arXiv cs.AI · 51d ago · 2 views

UltraQuant: 4-bit KV Caching for Context-Heavy Agents

UltraQuant enables 4-bit KV caching for context-heavy agents, reducing P50 time-to-first-token by 3.47x in late rounds and boosting output throughput by 1.63x over FP8 KV baseline. It achieves this using FP8 queries, FP4 KV tensors, UE8M0 group scales, and native scaled-MFMA on AMD CDNA4 GPUs, with optimizations for decode-attention kernels and robust design choices like asymmetric K/V treatment and Walsh-Hadamard rotation.

arxiv arXiv cs.LG · 51d ago · 1 view

UltraQuant: 4-bit KV Caching for Context-Heavy Agents

UltraQuant introduces a 4-bit KV caching method tailored for context-heavy agent workloads. It achieves 3.47x reduction in P50 time-to-first-token in late rounds and 1.63x higher output throughput compared to FP8 KV caching, using FP8 queries, FP4 KV tensors, and native AMD CDNA4 scaled-MFMA support.

arxiv arXiv cs.LG · 51d ago · 3 views

Execution-State Capsules for Low-Latency On-Device AI Serving

Execution-state capsules enable graph-bound checkpointing and restoration of complete execution state, including KV, recurrent, and convolution states, for low-latency, small-batch on-device AI serving. On RTX 5090 and Jetson AGX Thor, capsule restore achieves byte-exact and token-identical correctness, with sub-millisecond GPU operations and TTFT speedups up to 27x at 16k tokens, demonstrating significant latency reduction in interactive AI workflows.