25 citations · 37 across the 7 of their papers we have counts for
7 papers
SYNFI: Pre-Silicon Fault Analysis of an Open-Source Secure Element
Pascal Nasahl, Miguel Osorio, Pirmin Vogel +4
Fault attacks are active, physical attacks that an adversary can leverage to alter the control-flow of embedded devices to gain access to sensitive information or bypass protection…
Network-Accelerated Non-Contiguous Memory Transfers
Salvatore Di Girolamo, Konstantin Taranov, Andreas Kurth +7
Applications often communicate data that is non-contiguous in the send- or the receive-buffer, e.g., when exchanging a column of a matrix stored in row-major order. While non-conti…
Ara: A 1 GHz+ Scalable and Energy-Efficient RISC-V Vector Processor with Multi-Precision Floating Point Support in 22 nm FD-SOI
Matheus Cavalcante, Fabian Schuiki, Florian Zaruba +2
In this paper, we present Ara, a 64-bit vector processor based on the version 0.5 draft of RISC-V's vector extension, implemented in GlobalFoundries 22FDX FD-SOI technology. Ara's…
NTX: An Energy-efficient Streaming Accelerator for Floating-point Generalized Reduction Workloads in 22nm FD-SOI
Fabian Schuiki, Michael Schaffner, Luca Benini
Specialized coprocessors for Multiply-Accumulate (MAC) intensive workloads such as Deep Learning are becoming widespread in SoC platforms, from GPUs to mobile SoCs. In this paper w…
On the Feasibility of FPGA Acceleration of Molecular Dynamics Simulations
Michael Schaffner, Luca Benini
Classical molecular dynamics (MD) simulations are important tools in life and material sciences since they allow studying chemical and biological processes in detail. However, the…
A Scalable Near-Memory Architecture for Training Deep Neural Networks on Large In-Memory Datasets
Fabian Schuiki, Michael Schaffner, Frank K. Gürkaynak +1
Most investigations into near-memory hardware accelerators for deep neural networks have primarily focused on inference, while the potential of accelerating training has received r…
Hydra: An Accelerator for Real-Time Edge-Aware Permeability Filtering in 65nm CMOS
Manuel Eggimann, Christelle Gloor, Florian Scheidegger +4
Many modern video processing pipelines rely on edge-aware (EA) filtering methods. However, recent high-quality methods are challenging to run in real-time on embedded hardware due…