1 code implementation • 15 May 2023 • Francesco Conti, Gianna Paulin, Angelo Garofalo, Davide Rossi, Alfio Di Mauro, Georg Rutishauser, Gianmarco Ottavi, Manuel Eggimann, Hayate Okuhara, Luca Benini
We present Marsellus, an all-digital heterogeneous SoC for AI-IoT end-nodes fabricated in GlobalFoundries 22nm FDX that combines 1) a general-purpose cluster of 16 RISC-V Digital Signal Processing (DSP) cores attuned for the execution of a diverse range of workloads exploiting 4-bit and 2-bit arithmetic extensions (XpulpNN), combined with fused MAC&LOAD operations and floating-point support; 2) a 2-8bit Reconfigurable Binary Engine (RBE) to accelerate 3x3 and 1x1 (pointwise) convolutions in DNNs; 3) a set of On-Chip Monitoring (OCM) blocks connected to an Adaptive Body Biasing (ABB) generator and a hardware control loop, enabling on-the-fly adaptation of transistor threshold voltages.
no code implementations • 24 Mar 2023 • Kanika Dheman, Stefan Walser, Philipp Mayer, Manuel Eggimann, Marko Kozomara, Denise Franke, Thomas Hermanns, Hugo Sax, Simone Schürle, Michele Magno
Here, a deep learning-based algorithm is presented that processes the local BI of the lower abdomen and suppresses artefacts to measure the bladder volume quantitatively, non-invasively and without the continuous need for additional personnel.
no code implementations • 18 Oct 2021 • Davide Rossi, Francesco Conti, Manuel Eggimann, Alfio Di Mauro, Giuseppe Tagliavini, Stefan Mach, Marco Guermandi, Antonio Pullini, Igor Loi, Jie Chen, Eric Flamand, Luca Benini
Vega achieves SoA-leading efficiency of 615 GOPS/W on 8-bit INT computation (boosted to 1. 3TOPS/W for 8-bit DNN inference with hardware acceleration).
no code implementations • 4 Feb 2021 • Manuel Eggimann, Abbas Rahimi, Luca Benini
Hyperdimensional computing (HDC) is a brain-inspired computing paradigm based on high-dimensional holistic representations of vectors.
1 code implementation • 25 Jun 2020 • Moritz Scherer, Michele Magno, Jonas Erb, Philipp Mayer, Manuel Eggimann, Luca Benini
Furthermore, the gesture recognition classifier has been implemented on a Parallel Ultra-Low Power Processor, demonstrating that real-time prediction is feasible with only 21 mW of power consumption for the full TCN sequence prediction network, while a system-level power consumption of less than 100 mW is achieved.
no code implementations • 28 Feb 2020 • Michele Magno, Xiaying Wang, Manuel Eggimann, Lukas Cavigelli, Luca Benini
This work presents InfiniWolf, a novel multi-sensor smartwatch that can achieve self-sustainability exploiting thermal and solar energy harvesting, performing computationally high demanding tasks.
no code implementations • 10 Dec 2019 • Xiaying Wang, Lukas Cavigelli, Manuel Eggimann, Michele Magno, Luca Benini
Synthetic aperture radar (SAR) data is becoming increasingly available to a wide range of users through commercial service providers with resolutions reaching 0. 5m/px.