150 citations · 1.3k across the 73 of their papers we have counts for
4 papers · 1 filter
DeepSketch: A New Machine Learning-Based Reference Search Technique for Post-Deduplication Delta Compression
Jisung Park, Jeoggyun Kim, Yeseong Kim +2
Data reduction in storage systems is becoming increasingly important as an effective solution to minimize the management cost of a data center. To maximize data-reduction efficienc…
EcoFlow: Efficient Convolutional Dataflows for Low-Power Neural Network Accelerators
Lois Orosa, Skanda Koppula, Yaman Umuroglu +5
Dilated and transposed convolutions are widely used in modern convolutional neural networks (CNNs). These kernels are used extensively during CNN training and inference of applicat…
An Experimental Study of Reduced-Voltage Operation in Modern FPGAs for Neural Network Acceleration
Behzad Salami, Erhan Baturay Onural, Ismail Emir Yuksel +6
We empirically evaluate an undervolting technique, i.e., underscaling the circuit supply voltage below the nominal level, to improve the power-efficiency of Convolutional Neural Ne…
The Non-IID Data Quagmire of Decentralized Machine Learning
Kevin Hsieh, Amar Phanishayee, Onur Mutlu +1
Many large-scale machine learning (ML) applications need to perform decentralized learning over datasets generated at different devices and locations. Such datasets pose a signific…