Manu Manuel, M.Sc.

Research Associate

Technical University of Munich
Department of Electrical and Computer Engineering
Chair of Integrated Systems
Arcisstr. 21
80333 Munich
Germany

Phone: +49.89.289.28338
Fax: +49.89.289.28323
Building: N1 (Theresienstr. 90)
Room: N2116
Email: manu.manuel@tum.de

Curriculum Vitae

Manu Manuel has started his Ph.D. work in the topic "Approximate computing for professional image processing" in February 2019 at the Chair of Integrated Systems, Technical University of Munich. He received his Master of Science (M.Sc.) in Embedded Systems from the Chemnitz University of Technology in 2018. Manu has been involved in different projects at Hilti Deutschland AG, Kaufering and Robert Bosch GmbH, Hildesheim for eight months each as internships and thesis, and he completed his master thesis on the topic "Invalid Status Identification of Traffic Signs". Moreover, his master research project was the development of a novel computer vision algorithm for breath rate detection using the RGB data. In 2012, he completed his bachelor of technology (B. Tech) in Electronics and Communication Engineering from Mahatma Gandhi University (Amal Jyothi College of Engineering), India.

TEACHING

Research

Approximate computing on FPGA for image processing
Dynamic reconfiguration of FPGA
Image processing, computer vision and machine learning

Offered Works

Ongoing Works

BAMAIDPFPIPSEMSHK
Title

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Power Modeling on FPGA for Approximate Computing

Open thesis as PDF.

Power Modeling on FPGA for Approximate Computing

Keywords:
ACIP

Description

Approximate computing provides a new design paradigm by performing inexact calculations instead of the actual one. As a result, fewer resources are used in the FPGA devices, more functions can be implemented, and the energy efficiency of the calculations is improved.

This work is a part of approximate computing for image processing (ACIP) project and aims to develop a modular-based power model on FPGA in order to account for the power benefits from the different approximations.

Supervisor:

Manu Manuel

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Evolutionary Functional Approximation of Digital Circuits

Open thesis as PDF.

Evolutionary Functional Approximation of Digital Circuits

Keywords:
Genetic Algorithm, CGP, Approximate Computing

Short Description:
Application of CGP in Approximate Computing

Description

Approximate computing provides a new design paradigm by performing inexact calculations instead of the actual one at the expense of output application quality. As a result, fewer resources are used, more functions can be implemented, and the energy efficiency of the calculations is improved. However, the output quality is preserved above a certain threshold. Cartesian Genetic Programming(CGP) is an evolutionary approach that is employed in digital circuit design and optimization.

This research work aims to bring the CGP together with AC and evaluate the effect of CGP in the optimization of the approximated digital circuits.

Supervisor:

Manu Manuel

PUBLICATIONS

Simon Conrady, Manu Manuel, Arne Kreddig, Walter Stechele: LCS-Based Automatic Configuration of Approximate Computing Parameters for FPGA System Designs. Proceedings of the Genetic and Evolutionary Computation Conference Companion (GECCO '19), 2019, 1271 -- 1279 more… BibTeX Full text ( DOI )
Wiede, Christian; Richter, Julia; Manuel, Manu; Hirtz, Gangolf: Remote Respiration Rate Determination in Video Data - Vital Parameter Extraction based on Optical Flow and Principal Component Analysis. Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - VISAPP, (VISIGRAPP 2017), SCITEPRESS - Science and Technology Publications, 2017, 326-333 more… BibTeX Full text ( DOI )