Concept
Booting process of Linux
Related publications (23)
End-to-end kernel learning via generative random Fourier features
Random Fourier features (RFFs) provide a promising way for kernel learning in a spectral case. Current RFFs-based kernel learning methods usually work in a two-stage way. In the first-stage process, learn-ing an optimal feature map is often formulated as a ...
ELSEVIER SCI LTD2023SecureCells: A Secure Compartmentalized Architecture
Babak Falsafi, Mathias Josef Payer, Yuanlong Li, Florian Hofhammer, Siddharth Gupta, Atri Bhattacharyya, Andrés Sánchez Marín
Modern programs are monolithic, combining code of varied provenance without isolation, all the while running on network-connected devices. A vulnerability in any component may compromise code and data of all other components. Compartmentalization separates ...
2023USBFuzz: A Framework for Fuzzing USB Drivers by Device Emulation
The Universal Serial Bus (USB) connects external devices to a host. This interface exposes the OS kernels and device drivers to attacks by malicious devices. Unfortunately, kernels and drivers were developed under a security model that implicitly trusts co ...
USENIX ASSOC2020Energy- and Cost-Efficient VLSI DSP Systems Design with Approximate Computing
Technology scaling has progressed to enable integrated circuits with extremely high density enabling systems of tremendous complexity with manageable power consumption. With the continuation of Moore's law for many years, electronic chips have been able to ...
EPFL2020i-DPs CGRA: An Interleaved-Datapaths Reconfigurable Accelerator for Embedded Bio-signal Processing
David Atienza Alonso, Giovanni Ansaloni, Miguel Peon Quiros, Soumya Subhra Basu, Loris Gérard Duch
Smart edge sensors for bio-signal monitoring must support complex signal processing routines within an extremely small energy envelope. Coarse-Grained Reconfigurable Arrays (CGRAs) are good candidates for tackling these conflicting objectives because, than ...
2019Kernel Modeling Super-Resolution on Real Low-Resolution Images
Deep convolutional neural networks (CNNs), trained on corresponding pairs of high- and low-resolution images, achieve state-of-the-art performance in single-image super- resolution and surpass previous signal-processing based approaches. However, their per ...
IEEE COMPUTER SOC2019Advancing the State of Network Switch ASIC Offloading in the Linux Kernel
Modern data-center network operating systems rely on proprietary user-space daemons wrapping SDKs from switch vendors. Linux-based variants of these operating systems have benefited from increasing and simplified dataplane offloading support in recent year ...
2018A Synchronization-Based Hybrid-Memory Multi-Core Architecture for Energy-Efficient Biomedical Signal Processing
David Atienza Alonso, Giovanni Ansaloni, Ruben Braojos Lopez, Luca Benini
In the last decade, improvements on technology scaling have enabled the design of a novel generation of wearable bio-sensing monitors. These smart Wireless Body Sensor Nodes (WBSNs) are able to acquire and process biological signals, such as electrocardiog ...
Institute of Electrical and Electronics Engineers2017A Multi-Core Reconfigurable Architecture for Ultra-Low Power Bio-Signal Analysis
David Atienza Alonso, Giovanni Ansaloni, Ruben Braojos Lopez, Soumya Subhra Basu, Loris Gérard Duch
This paper introduces a novel computing architecture devoted to the ultra-low power analysis of multiple bio-signals. Its structure comprises several processors interfaced with a shared acceleration resource, implemented as a Coarse Grained Reconfigurable ...
2016Hardware/Software Co-Design of Ultra-Low Power Biomedical Monitors
Ongoing changes in world demographics and the prevalence of unhealthy lifestyles are imposing a paradigm shift in healthcare delivery. Nowadays, chronic ailments such as cardiovascular diseases, hypertension and diabetes, represent the most common causes o ...
EPFL2016