News

30.04.2019

Two new papers accepted at the SAMOS 2019 Conference

We got two papers addressing different aspects of manycore architectures accepted at SAMOS XIX, the 19th edition of the SAMOS Conference. One of the accepted papers, authored by Akshay Srivatsa, Sven Rheindt, Dirk...[more]

Category: Aktuelles

25.04.2019

Paper accepted at Learning Classifier Systems workshop

The paper titled "LCS-Based Automatic Configuration of Approximate Computing Parameters for FPGA System Designs" authored by Simon Conrady, Arne Kreddig, Manu Manuel and Walter Stechele has been accepted for publication...[more]

Category: Aktuelles

17.04.2019

LIS organized SelPhyS 2019, the workshop on "Self-Awareness in Cyber-Physical Systems"

On April 15 and 16, 2019 we organized SelPhyS 2019, the 4th edition of the workshop on applying self-awareness in the design of embedded and cyber-physical systems, in the Theresianum on the TUM City Campus. The concept of...[more]

Category: Aktuelles

09.04.2019

New paper on CNNs accepted at SAIAD workshop

Our authors A. Frickenstein, MR Vemparala, C. Unger, F. Ayar and W. Stechele got their paper titled "DSC Dense-Sparse Convolution for Vectorized Inference of Convolutional Neural Networks" accepted at the Workshop on...[more]

Category: Aktuelles

02.04.2019

Paper accepted at Computer and Robot Vision Conference

The paper "Resource-Aware Multicriterial Optimization of DNNs for Low-Cost Embedded Applications" authored by Alexander Frickenstein, Christian Unger and Walter Stechele, has been accepted at the 16th edition of the...[more]

Category: Aktuelles

25.01.2019

Invited Talk by Prof. Herkersdorf at HiPEAC 2019

Prof. Herkersdorf gave an invited talk on self-aware MPSoC system optimization at the RAPIDO workshop of HiPEAC 2019 Conference in Valencia, Spain. The focus of the RAPIDO workshop is on methods and tools for rapid simulation and...[more]

Category: Aktuelles

16.01.2019

New research project "Optimization of neural networks for automotive applications"

To improve traffic safety, Deep Neural Networks (DNN) are being developed worldwide for automotive applications. The challenge is that DNNs are compute- and memory-intensive, but the computing capacity in the vehicle remains...[more]

Category: Aktuelles

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