The open EEGLAB portal Interface: High-Performance computing with EEGLAB

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HDTorch: Accelerating Hyperdimensional Computing with GP-GPUs for Design Space Exploration

David Atienza Alonso, William Andrew Simon, Una Pale, Tomas Teijeiro Campo

The HyperDimensional Computing (HDC) Machine Learning (ML) paradigm is highly interesting for applications involving continuous, semi-supervised learning for long-term monitoring. However, its accuracy is not yet on par with other ML approaches, necessitat ...

Association for Computing MachineryNew YorkNYUnited States2022

DFAulted: Analyzing and Exploiting CPU Software Faults Caused by FPGA-Driven Undervolting Attacks

Mirjana Stojilovic, Dina Gamaleldin Ahmed Shawky Mahmoud

Field-programmable gate arrays (FPGAs) combine hardware reconfigurability with a high degree of parallelism. Consequently, FPGAs offer performance gains and power savings for many applications. A recent trend has been to leverage the hardware versatility o ...

2022

An Open-Source Whole Slide Image Registration Workflow at Cellular Precision Using Fiji, QuPath and Elastix

Olivier Burri, Jessica Sordet, Arne Seitz, Romain Guiet, Nicolas René Chiaruttini

Image analysis workflows for Histology increasingly require the correlation and combination of measurements across several whole slide images. Indeed, for multiplexing, as well as multimodal imaging, it is indispensable that the same sample is imaged multi ...

FRONTIERS MEDIA SA2022

Utilizing XMG-based Synthesis to Preserve Self-Duality for RFET-Based Circuits

Giovanni De Micheli, Heinz Riener, Alessandro Tempia Calvino, Akash Kumar

Individual transistors based on emerging reconfigurable nanotechnologies exhibit electrical conduction for both types of charge carriers. These transistors (referred to as Reconfigurable Field-Effect Transistors (RFETs)) enable dynamic reconfiguration to d ...

2022

Common workflows for computing material properties using different quantum engines

Sebastiaan Philippe Huber, Nicola Marzari, Gian-Marco Rignanese, Giovanni Pizzi, Aliaksandr Yakutovich, Berend Smit, Martin Uhrin, Conrad Johnston, Austin Jacob Zadoks, Samuel Poncé, Kristjan Eimre, Marnik Bercx, Christopher John Sewell

The prediction of material properties based on density-functional theory has become routinely common, thanks, in part, to the steady increase in the number and robustness of available simulation packages. This plurality of codes and methods is both a boon ...

2021

NetCracker: A Peek into the Routing Architecture of Xilinx 7-Series FPGAs

Mirjana Stojilovic, Stefan Nikolic

Novel applications have triggered significant changes at the system level of FPGA architecture design, such as the introduction of embedded VLIW processor arrays and hardened NoCs. However, the routing architecture of the soft logic fabric has largely rema ...

2021

Stimulus evoked causality estimation in stereo-EEG

Silvestro Micera, Fiorenzo Artoni

Objective. Stereo-electroencephalography (SEEG) has recently gained importance in analyzing brain functions. Its high temporal resolution and spatial specificity make it a powerful tool to investigate the strength, direction, and spectral content of brain ...

IOP PUBLISHING LTD2021

Learning from History for Byzantine Robust Optimization

Lie He, Sai Praneeth Reddy Karimireddy, Martin Jaggi

Byzantine robustness has received significant attention recently given its importance for distributed and federated learning. In spite of this, we identify severe flaws in existing algorithms even when the data across the participants is identically distri ...

JMLR-JOURNAL MACHINE LEARNING RESEARCH2021

EaRL: An Open-Source Software for Earthquake Risk, Loss and Lifecycle Assessment

Dimitrios Lignos, Ahmed Mohamed Ahmed Elkady

Evaluating earthquake-induced losses, such as structural repair costs, downtime and casualties, is becoming a standard practice within the performance-based earthquake engineering framework. Nonetheless, this evaluation is a demanding task that requires de ...

2021

Programming Heterogeneous CPU-GPU Systems by High-Level Dataflow Synthesis

Marco Mattavelli, Endri Bezati, Aurélien François Gilbert Bloch

Heterogeneous processing platforms combining in various architectures CPUs, GPUs, and programmable logic, are continuously evolving providing at each generation higher theoretical levels of computing performance. However, the challenge of how efficiently s ...

IEEE2020

Multiparty Homomorphic Encryption from Ring-Learning-with-Errors

Jean-Pierre Hubaux, Jean-Philippe Léonard Bossuat, Christian Vincent Mouchet, Juan Ramón Troncoso-Pastoriza

We propose and evaluate a secure-multiparty-computation (MPC) solution in the semi-honest model with dishonest majority that is based on multiparty homomorphic encryption (MHE). To support our solution, we introduce a multiparty version of the Brakerski-Fa ...

2021