7 citations · 10 across the 2 of their papers we have counts for
3 papers
cs.DC2021★ 3 cited
Tuna: A Static Analysis Approach to Optimizing Deep Neural Networks
Yao Wang, Xingyu Zhou, Yanming Wang +3
We introduce Tuna, a static analysis approach to optimizing deep neural network programs. The optimization of tensor operations such as convolutions and matrix multiplications is t…
cs.LG2021★ 7 cited
Accelerating SLIDE Deep Learning on Modern CPUs: Vectorization, Quantizations, Memory Optimizations, and More
Shabnam Daghaghi, Nicholas Meisburger, Mengnan Zhao +4
Deep learning implementations on CPUs (Central Processing Units) are gaining more traction. Enhanced AI capabilities on commodity x86 architectures are commercially appealing due t…
cs.PL2020
Nimble: Efficiently Compiling Dynamic Neural Networks for Model Inference
Haichen Shen, Jared Roesch, Zhi Chen +6
Modern deep neural networks increasingly make use of features such as dynamic control flow, data structures and dynamic tensor shapes. Existing deep learning systems focus on optim…