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20242026
most citedEfficient Serving of LLM Applications with Probabilistic Demand Modeling

1 citations · 2 across the 13 of their papers we have counts for

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cs.DC2026

GPU-Tile-Sim: A Tile-Centric GPU Simulation Framework for LLM Hardware-Software Co-Design

Yitong Ding, Jiawei Huang, Renyang Guan +7

Modern LLM (large language model) workloads increasingly rely on optimized GPU kernels through hardware-software co-design. These kernels achieve high-performance through fine-grai…

cs.DC2026

GF-DiT: Scheduling Parallelism for Diffusion Transformer Serving

Xinwei Qiang, Yifan Hu, Shixuan Sun +6

Diffusion Transformers (DiTs) have become the dominant architecture for image and video generation, creating growing demand for efficient DiT serving. Existing systems assign each…

cs.DC2026

InfiniLoRA: Disaggregated Multi-LoRA Serving for Large Language Models

Hongyu Chen, Letian Ruan, Zilin Xu +6

LoRA enables efficient customization of LLMs and is widely used in multi-tenant and multi-task serving. However, emerging model architectures such as MoE significantly increase LoR…

cs.DC2025

LiquidGEMM: Hardware-Efficient W4A8 GEMM Kernel for High-Performance LLM Serving

Huanqi Hu, Bowen Xiao, Shixuan Sun +8

Quantization is a critical technique for accelerating LLM inference by reducing memory footprint and improving computational efficiency. Among various schemes, 4-bit weight and 8-b…

cs.DC2025

ClusterFusion: Expanding Operator Fusion Scope for LLM Inference via Cluster-Level Collective Primitive

Xinhao Luo, Zihan Liu, Yangjie Zhou +8

Large language model (LLM) decoding suffers from high latency due to fragmented execution across operators and heavy reliance on off-chip memory for data exchange and reduction. Th…

cs.DC2025★ 1 cited

Efficient Serving of LLM Applications with Probabilistic Demand Modeling

Yifei Liu, Zuo Gan, Zhenghao Gan +8

Applications based on Large Language Models (LLMs) contains a series of tasks to address real-world problems with boosted capability, which have dynamic demand volumes on diverse b…

cs.DC2024

vTensor: Flexible Virtual Tensor Management for Efficient LLM Serving

Jiale Xu, Rui Zhang, Cong Guo +11

Large Language Models (LLMs) are widely used across various domains, processing millions of daily requests. This surge in demand poses significant challenges in optimizing throughp…