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17 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
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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
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4. VEDLIoT

Author

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

Published
2023
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5. eProcessor

Author

Alvarez, Lluc, primary, Ruiz, Abraham, additional, Bigas-Soldevilla, Arnau, additional, Kuroedov, Pavel, additional, Gonzalez, Alberto, additional, Mahale, Hamsika, additional, Bustamante, Noe, additional, Aguilera, Albert, additional, Minervini, Francesco, additional, Salamero, Javier, additional, Palomar, Oscar, additional, Papaefstathiou, Vassilis, additional, Psathakis, Antonis, additional, Dimou, Nikolaos, additional, Giaourtas, Michalis, additional, Mastorakis, Iasonas, additional, Ieronymakis, Georgios, additional, Matzouranis, Georgios-Michail, additional, Flouris, Vasilis, additional, Kossifidis, Nick, additional, Marazakis, Manolis, additional, Goel, Bhavishya, additional, Manivannan, Madhavan, additional, Ejaz, Ahsen, additional, Strikos, Panagiotis, additional, Vázquez, Mateo, additional, Sourdis, Ioannis, additional, Trancoso, Pedro, additional, Stenström, Per, additional, Hagemeyer, Jens, additional, Tigges, Lennart, additional, Kucza, Nils, additional, Philippe, Jean-Marc, additional, and Papaefstathiou, Ioannis, additional

Published
2023
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6. Evaluation of heterogeneous AIoT Accelerators within VEDLIoT

Author

Griessl, René, Porrmann, Florian, Kucza, Nils, Mika, Kevin, Hagemeyer, Jens, Kaiser, Martin, Porrmann, M., Tassemeier, M., Flottmann, M., Qararyah, F., Waqar, M., Trancoso, P., Ödman, D., Gugala, K., and Latosinski, G.

Abstract

Within VEDLIoT, a project targeting the development of energy-efficient Deep Learning for distributed AIoT applications, several accelerator platforms based on technologies like CPUs, embedded GPUs, FPGAs, or specialized ASICs are evaluated. The VEDLIoT approach is based on modular and scalable cognitive IoT hardware platforms. Modular microserver technology enables the integration of different, heterogeneous accelerators into one platform. Benchmarking of the different accelerators takes into account performance, energy efficiency and accuracy. The results in this paper provide a solid overview regarding available accelerator solutions and provide guidance for hardware selection for AIoT applications from far edge to cloud. VEDLIoT is an H2020 EU project which started in November 2020. It is currently in an intermediate stage. The focus is on the considerations of the performance and energy efficiency of hardware accelerators. Apart from the hardware and accelerator focus presented in this paper, the project also covers toolchain, security and safety aspects. The resulting technology is tested on a wide range of AIoT applications.

Published
2023

7. Asynchronous network-on-chips (NoCs) for resource efficient many core architectures

Author

Ax, Johannes, Kucza, Nils, Porrmann, Mario, Rückert, Ulrich, Jungeblut, Thorsten, Di, Jia, and Smith, Scott C.

Subjects
Router, business.industry, Computer science, Clock rate, Hardware_PERFORMANCEANDRELIABILITY, ComputerSystemsOrganization_PROCESSORARCHITECTURES, MPSoC, Reduction (complexity), Asynchronous communication, Embedded system, Scalability, Hardware_INTEGRATEDCIRCUITS, Place and route, State (computer science), business
Abstract

In this chapter, different GALS approaches for the implementation of embedded NoC architectures were presented. The GALS approach allows for the reduction of the resource requirements at an increased scalability of the NoC without sacrificing performance. The three approaches of synchronous, mesochronous, and asynchronous NoCs were compared. For the mesochronous NoC special synchronizers between the links were implemented. For the asynchronous NoC, the routers were completely realized as an asynchronous circuits. The results have shown that modern design methods (CCOpt design fl ow) allow a good scaling of MPSoCs even for synchronous NoCs. Nevertheless, the asynchronous NoC showed lower area and energy requirement compared to the mesochronous and synchronous implementation, while still providing a comparable performance. When comparing a place and route of an MPSoC, the asynchronous NoC leads to 3.1% less area requirements. The power consumption of an asynchronous router is only 22.4% (0.94 mW in idle state) or 53% (3.94 mW during communication) of the power consumption of a clock -based router. In the last section of the chapter, the global clock tree for an MPSoC with 256 CPUs was examined. The synchronous and mesochronous NoC show almost the same power consumption of about 7.7 mW. Using the asynchronous NoC reduces the power consumption by about 25% (5.78 mW). In addition, the mesochronous and asynchronous variants achieve a 2.6% higher clock frequency.

Published
2019

8. 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

9. 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
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10. 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

11. 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

12. LEGaTO

Author

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

Published
2018
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15. 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, 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

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17. 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, and Felber, Pascal

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