30 citations · 30 across the 5 of their papers we have counts for
5 papers
PassNet: Scaling Large Language Models for Graph Compiler Pass Generation
Yiqun Liu, Yingsheng Wu, Ruqi Yang +11
Modern tensor compilers such as TorchInductor deliver substantial speedups on mainstream models, yet face a systematic performance ceiling on long-tail workloads -- our profiling s…
GraphNet: A Large-Scale Computational Graph Dataset for Tensor Compiler Research
Xinqi Li, Yiqun Liu, Shan Jiang +6
We introduce GraphNet, a dataset of 2.7K real-world deep learning computational graphs with rich metadata, spanning six major task categories across multiple deep learning framewor…
CCQ: Convolutional Code for Extreme Low-bit Quantization in LLMs
Zhaojing Zhou, Xunchao Li, Minghao Li +8
The rapid scaling of Large Language Models (LLMs) elevates inference costs and compounds substantial deployment barriers. While quantization to 8 or 4 bits mitigates this, sub-3-bi…
Efficient AlphaFold2 Training using Parallel Evoformer and Branch Parallelism
Guoxia Wang, Zhihua Wu, Xiaomin Fang +4
The accuracy of AlphaFold2, a frontier end-to-end structure prediction system, is already close to that of the experimental determination techniques. Due to the complex model archi…
HelixFold: An Efficient Implementation of AlphaFold2 using PaddlePaddle
Guoxia Wang, Xiaomin Fang, Zhihua Wu +6
Accurate protein structure prediction can significantly accelerate the development of life science. The accuracy of AlphaFold2, a frontier end-to-end structure prediction system, i…