74 citations · 102 across the 5 of their papers we have counts for
7 papers · 1 filter
TRAPTI: Time-Resolved Analysis for SRAM Banking and Power Gating Optimization in Embedded Transformer Inference
Jan Klhufek, Alberto Marchisio, Vojtech Mrazek +2
Transformer neural networks achieve state-of-the-art accuracy across language and vision tasks, but their deployment on embedded hardware is hindered by stringent area, latency, an…
ApproxGNN: A Pretrained GNN for Parameter Prediction in Design Space Exploration for Approximate Computing
Ondrej Vlcek, Vojtech Mrazek
Approximate computing offers promising energy efficiency benefits for error-tolerant applications, but discovering optimal approximations requires extensive design space exploratio…
AxMED: Formal Analysis and Automated Design of Approximate Median Filters using BDDs
Vojtech Mrazek, Zdenek Vasicek
The increasing demand for energy-efficient solutions has led to the emergence of an approximate computing paradigm that enables power-efficient implementations in various applicati…
Late Breaking Result: FPGA-Based Emulation and Fault Injection for CNN Inference Accelerators
Filip Masar, Vojtech Mrazek, Lukas Sekanina
A new field programmable gate array (FPGA)-based emulation platform is proposed to accelerate fault tolerance analysis of inference accelerators of convolutional neural networks (C…
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…
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…