9 citations · 9 across the 4 of their papers we have counts for
5 papers
ComFuse: Fusing Complex Memory-Intensive Subgraphs with Compute-Intensive Kernels For Modern GPU Architectures
Di Mu, Tengyuan Jin, Zhenkun Wang +6
Modern deep learning workloads increasingly comprise heterogeneous computation graphs that combine compute-intensive operators with memory-intensive subgraphs. Existing deep learni…
Demystifying and Enhancing the Efficiency of Large Language Model Based Search Agents
Tiannuo Yang, Zebin Yao, Bowen Jin +4
Large Language Model (LLM)-based search agents have shown remarkable capabilities in solving complex tasks by dynamically decomposing problems and addressing them through interleav…
PlainUSR: Chasing Faster ConvNet for Efficient Super-Resolution
Yan Wang, Yusen Li, Gang Wang +1
Reducing latency is a roaring trend in recent super-resolution (SR) research. While recent progress exploits various convolutional blocks, attention modules, and backbones to unloc…
VDTuner: Automated Performance Tuning for Vector Data Management Systems
Tiannuo Yang, Wen Hu, Wangqi Peng +4
Vector data management systems (VDMSs) have become an indispensable cornerstone in large-scale information retrieval and machine learning systems like large language models. To enh…
On the Opportunities of Green Computing: A Survey
You Zhou, Xiujing Lin, Xiang Zhang +38
Artificial Intelligence (AI) has achieved significant advancements in technology and research with the development over several decades, and is widely used in many areas including…