29 citations · 93 across the 8 of their papers we have counts for
8 papers
ByteTransformer: A High-Performance Transformer Boosted for Variable-Length Inputs
Yujia Zhai, Chengquan Jiang, Leyuan Wang +5
Transformers have become keystone models in natural language processing over the past decade. They have achieved great popularity in deep learning applications, but the increasing…
Bolt: Bridging the Gap between Auto-tuners and Hardware-native Performance
Jiarong Xing, Leyuan Wang, Shang Zhang +3
Today's auto-tuners (e.g., AutoTVM, Ansor) generate efficient tensor programs by navigating a large search space to identify effective implementations, but they do so with opaque h…
UNIT: Unifying Tensorized Instruction Compilation
Jian Weng, Animesh Jain, Jie Wang +3
Because of the increasing demand for computation in DNN, researchers develope both hardware and software mechanisms to reduce the compute and memory burden. A widely adopted approa…
HAWQV3: Dyadic Neural Network Quantization
Zhewei Yao, Zhen Dong, Zhangcheng Zheng +8
Current low-precision quantization algorithms often have the hidden cost of conversion back and forth from floating point to quantized integer values. This hidden cost limits the l…
Fast Gunrock Subgraph Matching (GSM) on GPUs
Leyuan Wang, John D. Owens
In this paper, we propose a GPU-efficient subgraph isomorphism algorithm using the Gunrock graph analytic framework, GSM (Gunrock Subgraph Matching), to compute graph matching on G…
Fast BFS-Based Triangle Counting on GPUs
Leyuan Wang, John D. Owens
In this paper, we propose a novel method to compute triangle counting on GPUs. Unlike previous formulations of graph matching, our approach is BFS-based by traversing the graph in…
A Unified Optimization Approach for CNN Model Inference on Integrated GPUs
Leyuan Wang, Zhi Chen, Yizhi Liu +4
Modern deep learning applications urge to push the model inference taking place at the edge devices for multiple reasons such as achieving shorter latency, relieving the burden of…
Gunrock: GPU Graph Analytics
Yangzihao Wang, Yuechao Pan, Andrew Davidson +8
For large-scale graph analytics on the GPU, the irregularity of data access and control flow, and the complexity of programming GPUs, have presented two significant challenges to d…