As part of the Informatik-Kolloquiums we would like to invite you to the institute talk

Fostering the use of machine learning on board to satellite: the CloudScout case study and beyond


Luca Fanucci, Space Activities overview at Pisa University and Ingeniars spin-off company
Gianluca Giuffrida, CNN-based on-the-edge clouds detector: the CloudScout case study
Gianmarco Dinelli, FPGA implementation of CloudScout CNN: advantages and disadvantages
Pietro Nannipieri, The ICU4SAT project idea: a Pisa and Brandenburg Universities collaboration
All,  brainstorming

                        Wednesday, 2020-12-09

                       3:00 p.m. - 4:30 p.m.

                         Meeting number: 121 053 7857  Password: 99sTN33kcRM


Fostering the use of machine learning on board to satellite: the CloudScout case study and beyond
Machine Learning (ML) has already demonstrated its capability to solve complex problem in the cloud. With the advancement of dedicated embedded hardware accelerators, the potential of ML can be exploited also at the edge. This opens very interesting scenarios also for space applications, both for communication/control and payload levels. In fact, at control level ML algorithms can be exploited to control the navigation of satellites, using images of target planets or moon craters as reference points. At payload level, instead, ML can be used to simplify Earth Observation for remote sensing applications, directly elaborating data on-board reducing the dependency with the earth: such as cloud detection, fire detection, object detection, land cover / land use classification, etc. For these image-based scenarios Convolutional Neural Networks (CNNs) and theirs derivates represent one of the most promising algorithms.
This seminar will present some research activities on CNN-based algorithms for embedded and low power platforms at the edge recently developed at the University of Pisa. Starting from the CloudScout CNN recently launched on board of the Phisat-1 mission we will discuss several trade-off in terms of output accuracy, power consumption and memory requirements for commercial (e.g. Intel Movidius Myriad-2) and dedicate hardware accelerators based on FPGA. Finally we will present the concept of the Instrumentation Control Unit for Satellite Application (ICU4SAT) project to be developed in collaboration with Brandenburg University of Technology – Cottbus-Senftenberg.

Speakers Short Bio

Luca Fanucci (Fellow, IEEE) received the Laurea and Ph.D. degrees in electronic engineering from the University of Pisa in 1992 and 1996, respectively. From 1992 to 1996, he was a Research Fellow with the European Space Agency (ESTEC), Noordwijk, The Netherlands. From 1996 to 2004, he was a Senior Researcher with the Italian National Research Council, Pisa. He is currently a Professor of microelectronics with the University of Pisa. His research interests include several aspects of design technologies for integrated circuits and electronic systems, with particular emphasis on system-level design, hardware/software co-design and sensor conditioning, and data fusion, and also wireless communications, low-power multimedia, automotive, healthcare, ambient assisted living, and technical aids for independent living. He is the coauthor of more than 400 journal articles and conference papers and a co-inventor of more than 40 patents. He is a member of the Editorial Board of Technology and Disability (IOS Press) Journal. He has served in several technical programme committees of international conferences. He was the Program Chair of DSD 2008 and DATE 2014 and the General Chair of DATE 2016 and HiPEAC 2020.

Gianluca Giuffrida got the bachelor’s degree in computer engineering at the Università degli studi di Catania in 2015. He got the master’s degree in Embedded Computing System at the University of Pisa in 2018. Master’s thesis work was based on an autonomous robotic arm for people with disabilities exploiting machine learning algorithms for object detection. He is currently pursuing the PhD in Information Engineering at the University of Pisa where main research topics are Machine Learning, Artificial Intelligence, Computer Vision and Robotics. Gianluca led the development team of the CloudScout convolutional neural network which was launched on 3 September 2020 on board to the Phisat-1 mission.

Gianmarco Dinelli received the M.Sc. degree (110 cum laude) in electronic engineering from the University of Pisa, where he is currently pursuing the Ph.D. degree with the VLSI Lab, Department of Information Engineering. His work is mainly related to digital system design, from system specifications to hardware implementation on an FPGA device. His research interests include satellite on-board data-handling subsystem and on the design of FPGA-based hardware accelerators for machine learning algorithms (e.g. CNNs), with particular attention to low power and resource-constrained on-the-edge applications.

Pietro Nannipieri got his Ph.D. in Information Engineering from University of Pisa in 2020 cum laude. His interests are digital and VLSI design as well as electronics for space applications. Pietro spent several Months in 2019 as Visiting Researcher in the TEC-EDP Section in ESTEC (ESA), where he carried out different qualification test on the SpaceFibre technology. He is currently a Post-doc researcher in the VLSI lab of the information engineering department, University of Pisa. His work mainly focuses on the development of IPs for satellite on-board data handling, (i.e. SpaceFibre), but also on signal processing and hardware cryptography.


As part of the IT colloquium, we would like to invite you to a lecture by Frau Dr. Alexandra Kourfali (Universität Ghent, Belgien)


     Novel Hardware Verification Methods for FPGAs”


                        Monday, 2020-03-02

                        11:00 a.m.

                       Verfügungsgebäude 1C, room 1.24

Due to the continuously shrinking transistor sizes, anomalies are caused in the design that needs contingency plans. These contingency plans need to be available as soon as possible in the design of an IC, to avoid costly redesigns and other associated delays. Additionally, as the number of transistors inside ICs increases, thus allowing more complex digital designs to be realized, debugging and verifying these designs has become an increasingly difficult task. Moreover, multiple designs contain a safety-critical feature. They are in need to comply with specific safety-critical standards, making IC reliability a fundamental concern in the design and manufacturing process. Various hardware verification techniques exist, that can be used based on the requirements of each design and at different stages in the design flow. There is a trade-off between speed, design complexity, internal signal observability, and required fault coverage.

This talk will address these issues, and discuss the creation of verification methods that cover bugs, permanent faults, and soft errors. With interest in commercial SRAM-based FPGAs, this talk addresses the problems of providing continuous operation after an error occurred by achieving a runtime reconfigurable recovery from a failure, and to ensure that bugs that have escaped pre-silicon validation are detected. In particular, emulation-based verification techniques that are dependent on a long verification cycle and need significant resources are addressed throughout the talk, namely fault injection, fault tolerance, and in-circuit debugging.
The objectives for this work are focused on providing novel methods, tools, and design techniques for hardware verification that can be either applied for FPGA prototyping during ASIC verification or when an FPGA is the final product. They address major industry bottlenecks, namely area and time overhead, limited internal observability, long recompilation/reconfiguration times, and intolerance to soft errors and other radiation effects.

We cordially invite all interested parties to the colloquium on Monday, January 13th, 2020.

Prof. Paolo Rech, Universidade Federal do Rio Grande do Sul (Brasilien)

Reliability of Computing Systems in the Era of Autonomous Vehicles and Supercomputers

 10:00 a.m.
 Verfügungsgebäude 1C, room 0.01

Reliability is one of the major concerns for both safety-critical and High-Performance Computing applications. A neutron impact can generate faults in computing devices, leading to application crashes, wrong results, and system hangs. Several evidence showed that neutron-induced faults have corrupted large-server operations, have caused unexpected behaviours in airplanes, lead to car accidents, and even influenced politics results. In the talk we will briefly cover the effects of neutron impact on computing systems and applications. Particular emphasis will be given to self-driven cars, which is the newest trend in the automotive industry. We will present the results of several experiments on object-detection frameworks for automotive applications and show that neutrons can effectively change the way a vehicle senses objects, potentially leading to accidents. Lately, novel architectural solutions, such as heterogeneous computing and mixed-precision architectures, have been introduced to increase devices computational efficiency. We will discuss if and how we can take advantage of these novel architectural solutions to improve applications' reliability without unnecessary overhead. Particular attention will be given to the reliability of Xilinx Field-Programmable Gate-Arrays (FPGA), Intel Xeon Phis, NVIDIA Graphics Processing Units (GPUs), ARM embedded devices, and AMD heterogeneous devices.

This website uses cookies. Those have two functions: On the one hand they are providing basic functionality for this website. On the other hand they allow us to improve our content for you by saving and analyzing anonymized user data. You can redraw your consent to using these cookies at any time. Find more information regarding cookies on our Data Protection Declaration and regarding us on the Imprint.


These cookies are needed for a smooth operation of our website.


Name Purpose Lifetime Type Provider
_pk_id Used to store a few details about the user such as the unique visitor ID. 13 months HTML Matomo
_pk_ref Used to store the attribution information, the referrer initially used to visit the website. 6 months HTML Matomo
_pk_ses Short lived cookie used to temporarily store data for the visit. 30 minutes HTML Matomo