97 citations · 193 across the 8 of their papers we have counts for
4 papers · 1 filter
Mind Mappings: Enabling Efficient Algorithm-Accelerator Mapping Space Search
Kartik Hegde, Po-An Tsai, Sitao Huang +3
Modern day computing increasingly relies on specialization to satiate growing performance and efficiency requirements. A core challenge in designing such specialized hardware archi…
HarDNN: Feature Map Vulnerability Evaluation in CNNs
Abdulrahman Mahmoud, Siva Kumar Sastry Hari, Christopher W. Fletcher +7
As Convolutional Neural Networks (CNNs) are increasingly being employed in safety-critical applications, it is important that they behave reliably in the face of hardware errors. T…
SparseTrain:Leveraging Dynamic Sparsity in Training DNNs on General-Purpose SIMD Processors
Zhangxiaowen Gong, Houxiang Ji, Christopher Fletcher +2
Our community has greatly improved the efficiency of deep learning applications, including by exploiting sparsity in inputs. Most of that work, though, is for inference, where weig…
Morph: Flexible Acceleration for 3D CNN-based Video Understanding
Kartik Hegde, Rohit Agrawal, Yulun Yao +1
The past several years have seen both an explosion in the use of Convolutional Neural Networks (CNNs) and the design of accelerators to make CNN inference practical. In the archite…