2 citations · 4 across the 6 of their papers we have counts for
8 papers
CUTh-Solver: GPU-Accelerated Sparse Matrix Solver for High-Resolution Thermal Simulation of 3D ICs
Chenghan Wang, Zhen Zhuang, Shui Jiang +9
Coarse-grained thermal simulation tends to underestimate localized thermal issues, potentially missing critical hotspots. Accurate analysis, therefore, demands fine-grained informa…
3D-ICE 4.0: Accurate and efficient thermal modeling for 2.5D/3D heterogeneous chiplet systems
Kai Zhu, Darong Huang, Luis Costero +1
The increasing power densities and intricate heat dissipation paths in advanced 2.5D/3D chiplet systems necessitate thermal modeling frameworks that deliver detailed thermal maps w…
CloudFormer: An Attention-based Performance Prediction for Public Clouds with Unknown Workload
Amirhossein Shahbazinia, Darong Huang, Luis Costero +1
Cloud platforms are increasingly relied upon to host diverse, resource-intensive workloads due to their scalability, flexibility, and cost-efficiency. In multi-tenant cloud environ…
GreenLLM: SLO-Aware Dynamic Frequency Scaling for Energy-Efficient LLM Serving
Qunyou Liu, Darong Huang, Marina Zapater +1
Large Language Models (LLMs) are becoming the backbone of modern cloud services, yet their inference costs are dominated by GPU energy. Unlike traditional GPU workloads, LLM infere…
A 20-Year Retrospective on Power and Thermal Modeling and Management
David Atienza, Kai Zhu, Darong Huang +1
As processor performance advances, increasing power densities and complex thermal behaviors threaten both energy efficiency and system reliability. This survey covers more than two…
e-GPU: An Open-Source and Configurable RISC-V Graphic Processing Unit for TinyAI Applications
Simone Machetti, Pasquale Davide Schiavone, Lara Orlandic +4
Graphics processing units (GPUs) excel at parallel processing, but remain largely unexplored in ultra-low-power edge devices (TinyAI) due to their power and area limitations, as we…
Saving GPU Hours in LLM Inference System Development and Online Workloads with Simulation and DBMS-Inspired Cache Replacement Policies
Kyoungmin Kim, Jiacheng Li, Kijae Hong +3
LLMs are increasingly used world-wide from daily tasks to agentic systems and data analytics, requiring significant GPU resources. While LLM inference systems are capable of servin…
CloudProphet: A Machine Learning-Based Performance Prediction for Public Clouds
Darong Huang, Luis Costero, Ali Pahlevan +2
Computing servers have played a key role in developing and processing emerging compute-intensive applications in recent years. Consolidating multiple virtual machines (VMs) inside…