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From the 1 of 11 linked papers with an AI index.

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20242026
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11 papers

cs.AI2026

Are LLM-Generated GPU Kernels Production-Ready? A Trace-Driven Benchmark and Optimization Agent

Lingyun Yang, Yuxiao Wang, Shenghao Liang +8

The paper introduces Atrex-Bench, a trace-driven GPU kernel benchmark derived from real production inference workloads, and evaluates LLM-generated kernels, revealing a large perfo…

cs.CL2026

Ling and Ring 2.6 Technical Report: Efficient and Instant Agentic Intelligence at Trillion-Parameter Scale

Ang Li, Ben Liu, Bin Han +215

Efficient and scalable agentic intelligence requires models that can deliver both low-latency responses and strong reasoning capabilities while remaining practical to train, serve,…

cs.PF2026

PipeWeave: Synergizing Analytical and Learning Models for Unified GPU Performance Prediction

Kaixuan Zhang, Yunfan Cui, Shuhao Zhang +8

The rapid expansion of Transformer-based large language models has dramatically increased the need for high-performance GPUs. As a result, there is growing demand for fast, accurat…

cs.PF2026

WaveTune: Wave-aware Bilinear Modeling for Efficient GPU Kernel Auto-tuning

Kaixuan Zhang, Chutong Ding, Shiyou Qian +6

The rapid adoption of Large Language Models (LLMs) has made GPU inference efficiency an increasingly critical system concern. The runtime of LLM workloads is largely dominated by t…

cs.DC2026

LegoDiffusion: Micro-Serving Text-to-Image Diffusion Workflows

Lingyun Yang, Suyi Li, Tianyu Feng +10

Text-to-image generation executes a diffusion workflow comprising multiple models centered on a base diffusion model. Existing serving systems treat each workflow as an opaque mono…

cs.DC2026

Huawei Cloud Model-as-a-Service on the CloudMatrix384 SuperPod

Ao Xiao, Bangzheng He, Baoquan Zhang +125

Scaled-out MoE LLMs and scaled-up SuperPods create new systems challenges for production Model-as-a-Service (MaaS), requiring disaggregation, low-latency communication, and decentr…