34 citations · 79 across the 27 of their papers we have counts for
14 papers · 1 filter
OACM: Optimistic Asynchronous Communication Model for Large-Scale SNN Simulation
Guangnan Feng, Yangle Zeng, Honghui Liang +2
Spiking Neural Network (SNN) simulation serves as a crucial tool for understanding brain dynamics and advancing neuromorphic computing, but faces significant scalability challenges…
Communication-Aware Placement and Pruning for Efficient Mixture-of-Experts Inference
Xiao Shi, Yingying Sun, Jiangsu Du +2
As MoE models scale to hundreds of experts, placement and pruning decisions increasingly dictate communication volume, affecting the performance of distributed inference across GPU…
Extreme-Scale Atomistic Simulation of Real-Temperature Magnetic Skyrmion Dynamics by Coupled Spin-Lattice Modeling
Pin Chen, Cheng-bing Chen, Hai Liu +9
Real-temperature topological magnetic dynamics in functional materials is governed by coupled lattice and spin evolution, yet remains inaccessible to predictive simulation at devic…
AlignedServe: Orchestrating Prefix-aware Batching to Build a High-throughput and Computing-efficient LLM Serving System
Fengyao Bai, Hongbin Zhang, Zhitao Chen +3
High-throughput inference serving is essential for applications built on large language models (LLMs). Existing serving frameworks reduce request-level and batch-level bubbles thro…
POLAR-PIC: A Holistic Framework for Matrixized PIC with Co-Designed Compute, Layout, and Communication
Yizhuo Rao, Xingjian Cui, Shangzhi Pang +8
Particle-in-Cell (PIC) simulations are fundamental to plasma physics but often suffer from limited scalability due to particle-grid interaction bottlenecks and particle redistribut…
Matrix-PIC: Harnessing Matrix Outer-product for High-Performance Particle-in-Cell Simulations
Yizhuo Rao, Xingjian Cui, Jiabin Xie +5
Particle-in-Cell (PIC) simulations spend most of their execution time on particle--grid interactions, where fine-grained atomic updates become a major bottleneck on traditional man…
PolyKAN: Efficient Fused GPU Operators for Polynomial Kolmogorov-Arnold Network Variants
Mingkun Yu, Heming Zhong, Dan Huang +2
Kolmogorov-Arnold Networks (KANs) promise higher expressive capability and stronger interpretability than Multi-Layer Perceptron, particularly in the domain of AI for Science. Howe…
TD-Pipe: Temporally-Disaggregated Pipeline Parallelism Architecture for High-Throughput LLM Inference
Hongbin Zhang, Taosheng Wei, Zhenyi Zheng +3
As the model size continuously increases, pipeline parallelism shows great promise in throughput-oriented LLM inference due to its low demand on communications. However, imbalanced…
gLLM: Global Balanced Pipeline Parallelism System for Distributed LLM Serving with Token Throttling
Tianyu Guo, Xianwei Zhang, Jiangsu Du +3
Pipeline parallelism has emerged as a predominant approach for deploying large language models (LLMs) across distributed nodes, owing to its lower communication overhead compared t…
EcoServe: Enabling Cost-effective LLM Serving with Proactive Intra- and Inter-Instance Orchestration
Jiangsu Du, Hongbin Zhang, Taosheng Wei +4
Existing LLM serving strategies can be categorized based on whether prefill and decode phases are disaggregated: non-disaggregated (NoDG) or fully disaggregated (FuDG). However, th…
Boosting LLM Serving through Spatial-Temporal GPU Resource Sharing
Zejia Lin, Hongxin Xu, Guanyi Chen +3
Modern LLM serving systems confront inefficient GPU utilization due to the fundamental mismatch between compute-intensive prefill and memory-bound decode phases. While current prac…
UNR: Unified Notifiable RMA Library for HPC
Guangnan Feng, Jiabin Xie, Dezun Dong +1
Remote Memory Access (RMA) enables direct access to remote memory to achieve high performance for HPC applications. However, most modern parallel programming models lack schemes fo…
Galaxy: A Resource-Efficient Collaborative Edge AI System for In-situ Transformer Inference
Shengyuan Ye, Jiangsu Du, Liekang Zeng +4
Transformer-based models have unlocked a plethora of powerful intelligent applications at the edge, such as voice assistant in smart home. Traditional deployment approaches offload…
SAIH: A Scalable Evaluation Methodology for Understanding AI Performance Trend on HPC Systems
Jiangsu Du, Dongsheng Li, Yingpeng Wen +4
Novel artificial intelligence (AI) technology has expedited various scientific research, e.g., cosmology, physics and bioinformatics, inevitably becoming a significant category of…