7 papers · 1 filter
ObfAx: Obfuscation and IP Piracy Detection in Approximate Circuits
Lukas Sekanina, Vojtech Mrazek
Approximate circuits often achieve exceptional trade-offs between computational accuracy and hardware efficiency, making them attractive for deployment as reusable Intellectual Pro…
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…
Exploring Quantization and Mapping Synergy in Hardware-Aware Deep Neural Network Accelerators
Jan Klhufek, Miroslav Safar, Vojtech Mrazek +2
Energy efficiency and memory footprint of a convolutional neural network (CNN) implemented on a CNN inference accelerator depend on many factors, including a weight quantization st…
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…