activity
20192026
most citedALWANN: Automatic Layer-Wise Approximation of Deep Neural Network Accelerators without Retraining

129 citations · 462 across the 26 of their papers we have counts for

collaborators
Showing 2020Show all

7 papers · 1 filter

cs.LG2020★ 16 cited

DESCNet: Developing Efficient Scratchpad Memories for Capsule Network Hardware

Alberto Marchisio, Vojtech Mrazek, Muhammad Abdullah Hanif +1

Deep Neural Networks (DNNs) have been established as the state-of-the-art algorithm for advanced machine learning applications. Recently proposed by the Google Brain's team, the Ca…

cs.LG2020★ 39 cited

NASCaps: A Framework for Neural Architecture Search to Optimize the Accuracy and Hardware Efficiency of Convolutional Capsule Networks

Alberto Marchisio, Andrea Massa, Vojtech Mrazek +3

Deep Neural Networks (DNNs) have made significant improvements to reach the desired accuracy to be employed in a wide variety of Machine Learning (ML) applications. Recently the Go…

cs.NE2020★ 16 cited

Semantically-Oriented Mutation Operator in Cartesian Genetic Programming for Evolutionary Circuit Design

David Hodan, Vojtech Mrazek, Zdenek Vasicek

Despite many successful applications, Cartesian Genetic Programming (CGP) suffers from limited scalability, especially when used for evolutionary circuit design. Considering the mu…

cs.AR2020★ 32 cited

ApproxFPGAs: Embracing ASIC-Based Approximate Arithmetic Components for FPGA-Based Systems

Bharath Srinivas Prabakaran, Vojtech Mrazek, Zdenek Vasicek +2

There has been abundant research on the development of Approximate Circuits (ACs) for ASICs. However, previous studies have illustrated that ASIC-based ACs offer asymmetrical gains…

cs.AR2020★ 12 cited

Using Libraries of Approximate Circuits in Design of Hardware Accelerators of Deep Neural Networks

Vojtech Mrazek, Lukas Sekanina, Zdenek Vasicek

Approximate circuits have been developed to provide good tradeoffs between power consumption and quality of service in error resilient applications such as hardware accelerators of…

cs.NE2020★ 5 cited

Adaptive Verifiability-Driven Strategy for Evolutionary Approximation of Arithmetic Circuits

Milan Ceska, Jiri Matyas, Vojtech Mrazek +3

We present a novel approach for designing complex approximate arithmetic circuits that trade correctness for power consumption and play important role in many energy-aware applicat…