FG Technische Informatik
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Institute
VLSI for Next Generation CE
(2020)
Analysis of Hardware Implementations to Accelerate Convolutional and Recurrent Neuronal Networks
(2017)
Towards a Perspective of the Role of Mathematics in Computer Science and Engineering (CSE) Education
(2016)
An Application Specific Framework for HLS-based FPGA Design of Articulated Robot Inverse” Kinematics
(2018)
A Modular Software Library for Effective High-Level Synthesis of Convolutional Neural Networks
(2020)
Approximate on-the-fly coarse-grained reconfigurable acceleration for general-purpose applications
(2018)
The Potential of Accelerating Image-Processing Applications by Using Approximate Function Reuse
(2016)
Scaling minimum features of ICs down to the 10nm- area and below has allowed high integration rates in electronics. Scaling at supply voltages of 1V and below also implies a rising level of stress which drives aging effects that reduce switching speed and the expected life time. Additionally, vulnerability from particle radiation is increased. Hence, fault detection and on- line correction become a must for many applications. However, not only fault tolerance but self-awareness becomes also an advantage. Provided that by being aware of its own healthy state allow optimized configurations regarding system operation modes and configurable hardware mechanism. This paper shows a preliminary work in a configurable circuit and explores its configuration possibilities when integrated into a complete system.
RESCUE: Interdependent Challenges of Reliability, Security and Quality in Nanoelectronic Systems
(2019)
RESCUE: Cross-Sectoral PhD Training Concept for Interdependent Reliability, Security and Quality
(2018)