Search

Your search keyword '"Kucza, Nils"' showing total 6 results
Start Over Author "Kucza, Nils" Search Limiters Full Text
6 results on '"Kucza, Nils"'

1. VEDLIoT -- Next generation accelerated AIoT systems and applications

Author

Mika, Kevin, Griessl, René, Kucza, Nils, Porrmann, Florian, Kaiser, Martin, Tigges, Lennart, Hagemeyer, Jens, Trancoso, Pedro, Azhar, Muhammad Waqar, Qararyah, Fareed, Zouzoula, Stavroula, Ménétrey, Jämes, Pasin, Marcelo, Felber, Pascal, Marcus, Carina, Brunnegard, Oliver, Eriksson, Olof, Salomonsson, Hans, Ödman, Daniel, Ask, Andreas, Casimiro, Antonio, Bessani, Alysson, Carvalho, Tiago, Gugala, Karol, Zierhoffer, Piotr, Latosinski, Grzegorz, Tassemeier, Marco, Porrmann, Mario, Heyn, Hans-Martin, Knauss, Eric, Mao, Yufei, and Meierhöfer, Franz

Subjects
Computer Science - Hardware Architecture, Computer Science - Artificial Intelligence, Computer Science - Cryptography and Security
Abstract

The VEDLIoT project aims to develop energy-efficient Deep Learning methodologies for distributed Artificial Intelligence of Things (AIoT) applications. During our project, we propose a holistic approach that focuses on optimizing algorithms while addressing safety and security challenges inherent to AIoT systems. The foundation of this approach lies in a modular and scalable cognitive IoT hardware platform, which leverages microserver technology to enable users to configure the hardware to meet the requirements of a diverse array of applications. Heterogeneous computing is used to boost performance and energy efficiency. In addition, the full spectrum of hardware accelerators is integrated, providing specialized ASICs as well as FPGAs for reconfigurable computing. The project's contributions span across trusted computing, remote attestation, and secure execution environments, with the ultimate goal of facilitating the design and deployment of robust and efficient AIoT systems. The overall architecture is validated on use-cases ranging from Smart Home to Automotive and Industrial IoT appliances. Ten additional use cases are integrated via an open call, broadening the range of application areas., Comment: This publication incorporates results from the VEDLIoT project, which received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 957197. CF'23: 20th ACM International Conference on Computing Frontiers, May 2023, Bologna, Italy

Published
2023
Full Text
View/download PDF

2. VEDLIoT: Very Efficient Deep Learning in IoT

Author

Kaiser, Martin, Griessl, Rene, Kucza, Nils, Haumann, Carola, Tigges, Lennart, Mika, Kevin, Hagemeyer, Jens, Porrmann, Florian, Rückert, Ulrich, dem Berge, Micha vor, Krupop, Stefan., Porrmann, Mario, Tassemeier, Marco, Trancoso, Pedro, Quararyah, Fareed, Zouzoula, Stavroula, Casimiro, Antonio, Bessani, Alysson, Cecilio, Jose, Andersson, Stefan, Brunnegard, Oliver, Eriksson, Olof, Weiss, Roland, Meierhöfer, Franz, Salomonsson, Hans, Malekzadeh, Elaheh, Ödman, Daniel, Khurshid, Anum, Felber, Pascal, Pasin, Marcelo, Schiavoni, Valerio, Ménétrey, Jämes, Gugula, Karol, Zierhoffer, Piotr, Knauss, Eric, and Heyn, Hans-Martin

Subjects
Computer Science - Hardware Architecture, Computer Science - Cryptography and Security, Computer Science - Distributed, Parallel, and Cluster Computing, Computer Science - Performance
Abstract

The VEDLIoT project targets the development of energy-efficient Deep Learning for distributed AIoT applications. A holistic approach is used to optimize algorithms while also dealing with safety and security challenges. The approach is based on a modular and scalable cognitive IoT hardware platform. Using modular microserver technology enables the user to configure the hardware to satisfy a wide range of applications. VEDLIoT offers a complete design flow for Next-Generation IoT devices required for collaboratively solving complex Deep Learning applications across distributed systems. The methods are tested on various use-cases ranging from Smart Home to Automotive and Industrial IoT appliances. VEDLIoT is an H2020 EU project which started in November 2020. It is currently in an intermediate stage with the first results available., Comment: This publication incorporates results from the VEDLIoT project, which received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 957197

Published
2022
Full Text
View/download PDF

3. LEGaTO

Author

Cristal, Adrian, Unsal, Osman S., Martorell, Xavier, Carpenter, Paul, De La Cruz, Raul, Bautista, Leonardo, Jimenez, Daniel, Alvarez, Carlos, Salami, Behzad, Madonar, Sergi, Pericàs, Miquel, Trancoso, Pedro, vor dem Berge, Micha, Billung-Meyer, Gunnar, Krupop, Stefan, Christmann, Wolfgang, Klawonn, Frank, Mihklafi, Amani, Becker, Tobias, Gaydadjiev, Georgi, Salomonsson, Hans, Dubhashi, Devdatt, Port, Oron, Etsion, Yoav, Nowack, Vesna, Fetzer, Christof, Hagemeyer, Jens, Jungeblut, Thorsten, Kucza, Nils, Kaiser, Martin, Porrmann, Mario, Pasin, Marcelo, Schiavoni, Valerio, Rocha, Isabelly, Göttel, Christian, Felber, Pascal, Kaeli, David, and Barcelona Supercomputing Center

Subjects
010302 applied physics, 020203 distributed computing, business.industry, Dataflow, Computer science, Software ecosystem, Software Engineering, Cloud computing, Symmetric multiprocessor system, Fault tolerance, 02 engineering and technology, 01 natural sciences, Legato, LEGATO project, Supercomputadors, Computer Systems, Informàtica [Àrees temàtiques de la UPC], Embedded system, 0103 physical sciences, 0202 electrical engineering, electronic engineering, information engineering, Programming paradigm, High performance computing, Embedded Systems, business, Efficient energy use
Abstract

LEGaTO is a three-year EU H2020 project which started in December 2017. The LEGaTO project will leverage task-based programming models to provide a software ecosystem for Made-in-Europe heterogeneous hardware composed of CPUs, GPUs, FPGAs and dataflow engines. The aim is to attain one order of magnitude energy savings from the edge to the converged cloud/HPC.

Published
2018

4. LEGaTO - first steps towards energy-efficient toolset for heterogeneous computing

Author

Cristal, Adrian, Unsal, Osman S., Martorell, Xavier, Carpenter, Paul, De La Cruz, Raul, Bautista, Leonardo, Jimenez, Daniel, Alvarez, Carlos, Salami, Behzad, Madonar, Sergi, Pericàs, Miquel, Trancoso, Pedro, vor dem Berge, Micha, Billung-Meyer, Gunnar, Krupop, Stefan, Christmann, Wolfgang, Klawonn, Frank, Mihklafi, Amani, Becker, Tobias, Gaydadjiev, Georgi, Salomonsson, Hans, Dubhashi, Devdatt, Port, Oron, Hadar, Elad, Etsion, Yoav, Fetzer, Christof, Hagemeyer, Jens, Jungeblut, Thorsten, Kucza, Nils, Kaiser, Martin, Porrmann, Mario, Pasin, Marcelo, Schiavoni, Valerio, Rocha, Isabelly, Göttel, Christian, Felber, Pascal, Mudge, Trevor, Pnevmatikatos, Dionisios N., and Barcelona Supercomputing Center

Subjects
010302 applied physics, LEGaTO project, Computer science, Dataflow, business.industry, Software ecosystem, Cloud computing, Symmetric multiprocessor system, 02 engineering and technology, 7. Clean energy, 01 natural sciences, Legato, 020202 computer hardware & architecture, Supercomputadors, Computer architecture, Informàtica [Àrees temàtiques de la UPC], 0103 physical sciences, 0202 electrical engineering, electronic engineering, information engineering, Programming paradigm, High performance computing, Field-programmable gate array, business, Efficient energy use
Abstract

LEGaTO is a three-year EU H2020 project which started in December 2017. The LEGaTO project will leverage task-based programming models to provide a software ecosystem for Made-in-Europe heterogeneous hardware composed of CPUs, GPUs, FPGAs and dataflow engines. The aim is to attain one order of magnitude energy savings from the edge to the converged cloud/HPC.

Published
2018
Full Text
View/download PDF

5. LEGaTO: first steps towards energy-efficient toolset for heterogeneous computing

Author

Barcelona Supercomputing Center, Cristal, Adrian, Unsal, Osman S., Martorell, Xavier, Carpenter, Paul Matthew, de la Cruz, Raul, Bautista Gomez, Leonardo, Jimenez, Daniel, Alvarez, Carlos, Salami, Behzad, Madonar, Sergi, Pericàs Gleim, Miquel, Trancoso, Pedro, vor dem Berge, Micha, Billung-Meyer, Gunnar, Krupop, Stefan, Christmann, Wolfgang, Klawonn, Frank, Mihklafi, Amani, Becker, Tobias, Gaydadjiev, Georgi, Salomonsson, Hans, Dubhashi, Devdatt, Port, Oron, Hadar, Elad, Etsion, Yoav, Fetzer, Christof, Hagemeyer, Jens, Jungeblut, Thorsten, Kucza, Nils, Kaiser, Martin, Porrmann, Mario, Pasin, Marcelo, Schiavoni, Valerio, Rocha, Isabelly, Göttel, Christian, Felber, Pascal, Barcelona Supercomputing Center, Cristal, Adrian, Unsal, Osman S., Martorell, Xavier, Carpenter, Paul Matthew, de la Cruz, Raul, Bautista Gomez, Leonardo, Jimenez, Daniel, Alvarez, Carlos, Salami, Behzad, Madonar, Sergi, Pericàs Gleim, Miquel, Trancoso, Pedro, vor dem Berge, Micha, Billung-Meyer, Gunnar, Krupop, Stefan, Christmann, Wolfgang, Klawonn, Frank, Mihklafi, Amani, Becker, Tobias, Gaydadjiev, Georgi, Salomonsson, Hans, Dubhashi, Devdatt, Port, Oron, Hadar, Elad, Etsion, Yoav, Fetzer, Christof, Hagemeyer, Jens, Jungeblut, Thorsten, Kucza, Nils, Kaiser, Martin, Porrmann, Mario, Pasin, Marcelo, Schiavoni, Valerio, Rocha, Isabelly, Göttel, Christian, and Felber, Pascal

Abstract

LEGaTO is a three-year EU H2020 project which started in December 2017. The LEGaTO project will leverage task-based programming models to provide a software ecosystem for Made-in-Europe heterogeneous hardware composed of CPUs, GPUs, FPGAs and dataflow engines. The aim is to attain one order of magnitude energy savings from the edge to the converged cloud/HPC., Peer Reviewed, Postprint (author's final draft)

Published
2018

6. LEGaTO: towards energy-efficient, secure, fault-tolerant toolset for heterogeneous computing

Author

Barcelona Supercomputing Center, Cristal Kestelman, Adrián, Unsal, Osman S., Martorell, Xavier, Carpenter, Paul Matthew, de la Cruz, Raul, Bautista Gomez, Leonardo, Jimenez, Daniel, Alvarez, Carlos, Salami, Behzad, Madonar, Sergi, Pericàs, Miquel, Trancoso, Pedro, von dem Berge, Micha, Billung-Meyer, Gunnar, Krupop, Stefan, Christmann, Wolfgang, Klawonn, Frank, Mihklafi, Amani, Becker, Tobias, Gaydadjiev, Georgi, Salomonsson, Hans, Dubhashi, Devdatt, Port, Oron, Etsion, Yoav, Nowack, Vesna, Fetzer, Christof, Hagemeyer, Jens, Jungeblut, Thorsten, Kucza, Nils, Kaiser, Martin, Porrmann, Mario, Pasin, Marcelo, Schiavoni, Valerio, Rocha, Isabelly, Göttel, Christian, Felber, Pascal, Barcelona Supercomputing Center, Cristal Kestelman, Adrián, Unsal, Osman S., Martorell, Xavier, Carpenter, Paul Matthew, de la Cruz, Raul, Bautista Gomez, Leonardo, Jimenez, Daniel, Alvarez, Carlos, Salami, Behzad, Madonar, Sergi, Pericàs, Miquel, Trancoso, Pedro, von dem Berge, Micha, Billung-Meyer, Gunnar, Krupop, Stefan, Christmann, Wolfgang, Klawonn, Frank, Mihklafi, Amani, Becker, Tobias, Gaydadjiev, Georgi, Salomonsson, Hans, Dubhashi, Devdatt, Port, Oron, Etsion, Yoav, Nowack, Vesna, Fetzer, Christof, Hagemeyer, Jens, Jungeblut, Thorsten, Kucza, Nils, Kaiser, Martin, Porrmann, Mario, Pasin, Marcelo, Schiavoni, Valerio, Rocha, Isabelly, Göttel, Christian, and Felber, Pascal

Abstract

LEGaTO is a three-year EU H2020 project which started in December 2017. The LEGaTO project will leverage task-based programming models to provide a software ecosystem for Made-in-Europe heterogeneous hardware composed of CPUs, GPUs, FPGAs and dataflow engines. The aim is to attain one order of magnitude energy savings from the edge to the converged cloud/HPC., Peer Reviewed, Postprint (author's final draft)

Published
2018

Catalog

Books, media, physical & digital resources
See catalog results