CS
Authored
18 records found
EDEN
A High-Performance, General-Purpose, NeuroML-Based Neural Simulator
Modern neuroscience employs in silico experimentation on ever-increasing and more detailed neural networks. The high modeling detail goes hand in hand with the need for high model reproducibility, reusability and transparency. Besides, the size of the models and the long timescal
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Zero-Power Defense Done Right
Shielding IMDs from Battery-Depletion Attacks
The wireless capabilities of modern Implantable Medical Devices (IMDs) make them vulnerable to security attacks. One prominent attack, which has disastrous consequences for the patient’s wellbeing, is the battery Denial-of-Service attack whereby the IMD is occupied with continuou
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BrainFrame
A node-level heterogeneous accelerator platform for neuron simulations
Objective. The advent of high-performance computing (HPC) in recent years has led to its increasing use in brain studies through computational models. The scale and complexity of such models are constantly increasing, leading to challenging computational requirements. Even though
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WhiskEras
A New Algorithm for Accurate Whisker Tracking
Rodents engage in active touch using their facial whiskers: they explore their environment by making rapid back-and-forth movements. The fast nature of whisker movements, during which whiskers often cross each other, makes it notoriously difficult to track individual whiskers of
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FlexHH
A Flexible Hardware Library for Hodgkin-Huxley-Based Neural Simulations
The Hodgkin-Huxley (HH) neuron is one of the most biophysically-meaningful models used in computational neuroscience today. Ironically, the model's high experimental value is offset by its disproportional computational complexity. To such an extent that neuroscientists have eithe
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WhiskEras 2.0
Fast and Accurate Whisker Tracking in Rodents
Mice and rats can rapidly move their whiskers when exploring the environment. Accurate description of these movements is important for behavioral studies in neuroscience. Whisker tracking is, however, a notoriously difficult task due to the fast movements and frequent crossings a
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Adding security to implantable medical devices
Can we afford it?
Implantable Medical Devices (IMDs) belong to a class of highly life-critical, resource-constrained, deeply embedded systems out there. Their gradual conversion to wirelessly accessible devices in recent years has made them amenable to numerous successful ethical-hacking attempts.
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Adding security to implantable medical devices
Can we afford it?
Implantable Medical Devices (IMDs) belong to a class of highly life-critical, resource-constrained, deeply embedded systems out there. Their gradual conversion to wirelessly accessible devices in recent years has made them amenable to numerous successful ethical-hacking attempts.
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PlasticNet+
Extending multi-FPGA interconnect architecture via Gigabit transceivers
This paper addresses the communication challenges posed in multi-FPGA systems, by improving a custom FPGA interconnect architecture via the high-speed transceivers available in modern FPGA development boards. The proposed network interconnection, built upon the PlasticNet archite
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PlasticNet+
Extending multi-FPGA interconnect architecture via Gigabit transceivers
This paper addresses the communication challenges posed in multi-FPGA systems, by improving a custom FPGA interconnect architecture via the high-speed transceivers available in modern FPGA development boards. The proposed network interconnection, built upon the PlasticNet archite
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POSTER
IMD Security vs. Energy: Are we tilting at windmills?.
Implantable Medical Devices (IMDs) such as pacemakers and neurostimulators are highly constrained in terms of energy. In addition, the wireless-communication facilities of these devices also impose security requirements considering their life-critical nature. However, security so
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Tricking AI chips into simulating the human brain
A detailed performance analysis
In recent years, significant strides in Artificial Intelligence (AI) have led to various practical applications, primarily centered around training and deployment of deep neural networks (DNNs). These applications, however, require considerable computational resources, predominan
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Tricking AI chips into simulating the human brain
A detailed performance analysis
In recent years, significant strides in Artificial Intelligence (AI) have led to various practical applications, primarily centered around training and deployment of deep neural networks (DNNs). These applications, however, require considerable computational resources, predominan
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Oikonomos
An Opportunistic, Deep-Learning, Resource-Recommendation System for Cloud HPC
The cloud has become a powerful environment for deploying High-Performance Computing (HPC) applications. However, the size and heterogeneity of cloud-hardware offerings poses a challenge in selecting the optimal cloud instance type. Users often lack the knowledge or time necessar
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Oikonomos
An Opportunistic, Deep-Learning, Resource-Recommendation System for Cloud HPC
The cloud has become a powerful environment for deploying High-Performance Computing (HPC) applications. However, the size and heterogeneity of cloud-hardware offerings poses a challenge in selecting the optimal cloud instance type. Users often lack the knowledge or time necessar
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The VINEYARD approach
Versatile, integrated, accelerator-based, heterogeneous data centres
Emerging web applications like cloud computing, Big Data and social networks have created the need for powerful centres hosting hundreds of thousands of servers. Currently, the data centres are based on general purpose processors that provide high flexibility buts lack the energy
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The VINEYARD approach
Versatile, integrated, accelerator-based, heterogeneous data centres
Emerging web applications like cloud computing, Big Data and social networks have created the need for powerful centres hosting hundreds of thousands of servers. Currently, the data centres are based on general purpose processors that provide high flexibility buts lack the energy
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The VINEYARD approach
Versatile, integrated, accelerator-based, heterogeneous data centres
Emerging web applications like cloud computing, Big Data and social networks have created the need for powerful centres hosting hundreds of thousands of servers. Currently, the data centres are based on general purpose processors that provide high flexibility buts lack the energy
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Contributed
2 records found
Real-time Face and Landmark Localization for Eyeblink-Response Detection
A heterogenous CPU-GPU approach
Pavlovian eyeblink conditioning is a powerful experiment used in the field of neuroscience to measure multiple aspects of how we learn in our daily life. To track the movement of the eyelid during an experiment, researchers traditionally made use of potentiometers or electromyogr
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Full-Whisker Tracking System
A new algorithm for accurate whisker tracking in untrimmed head-fixed mice.
The movement of whiskers in head-fixed mice is of high interest for neurological research, as it allows scientists to learn more about learning processes during active touch. However, manual tracking of whiskers in thousands of frames is not feasible, and reliable tracking of ind
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