Real-Time High-Resolution Multiple-Camera Depth Map Estimation Hardware and Its Applications

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Driven by the demand for real-time processing and the need to minimize latency in AI algorithms, edge computing has experienced remarkable progress. Decision-making AI applications stand out for their heavy reliance on data-centric operations, predominantl ...

Modern integrated circuits are tiny yet incredibly complex technological artifacts, composed of millions and billions of individual structures working in unison. Managing their complexity and facilitating their design drove part of the co-evolution of mode ...

In this thesis, we give new protocols that offer a quantum advantage for problems in ML, Physics, and Finance. Quantum mechanics gives predictions that are inconsistent with local realism. The experiment proving this fact (Bell, 1964) gives a quantum proto ...

Decision-making permeates every aspect of human and societal development, from individuals' daily choices to the complex decisions made by communities and institutions. Central to effective decision-making is the discipline of optimization, which seeks th ...

Recent advancements in deep learning have revolutionized 3D computer vision, enabling the extraction of intricate 3D information from 2D images and video sequences. This thesis explores the application of deep learning in three crucial challenges of 3D com ...

Shared Virtual Memory (SVM) is a mechanism that allows host-side applications and FPGA accelerators to access the same virtual address space. It enables accelerating algorithms with unpredictable memory access patterns by making transparent pointer sharing ...

The increasing complexity of transformer models in artificial intelligence expands their computational costs, memory usage, and energy consumption. Hardware acceleration tackles the ensuing challenges by designing processors and accelerators tailored for t ...

Verification and testing of hardware heavily relies on cycle-accurate simulation of RTL. As single-processor performance is growing only slowly, conventional, single-threaded RTL simulation is becoming impractical for increasingly complex chip designs and ...

Machine learning algorithms such as Convolutional Neural Networks (CNNs) are characterized by high robustness towards quantization, supporting small-bitwidth fixed-point arithmetic at inference time with little to no degradation in accuracy. In turn, small ...

Dehydration is a frequent condition in the elderly and can lead to serious health complications if not compensated timely. Early diagnosis can be problematic, as medical examinations in the hospital would be needed. Fully wearable low-cost multisensing dev ...

Cloud computing environments increasingly provision field-programmable gate arrays (FPGAs) for their programmability and hardware-level parallelism. While FPGAs are typically used by one tenant at a time, multitenant schemes supporting spatial sharing of c ...

Given a sequence of functions

f_1,\ldots,f_n

with

f_i:\mathcal{D}\mapsto \mathbb{R}

, finite-sum minimization seeks a point

{x}^\star \in \mathcal{D}

minimizing

\sum_{j=1}^nf_j(x)/n

. In this work, we propose a key twist into the finite-sum minimizat ...

Dynamical system (DS) based motion planning offers collision-free motion, with closed-loop reactivity thanks to their analytical expression. It ensures that obstacles are not penetrated by reshaping a nominal DS through matrix modulation, which is construc ...

Embedded memories occupy an increasingly dominant part of the area and power budgets of modern systems-on-chips (SoCs). Multi-ported embedded memories, commonly used by media SoCs and graphical processing units, occupy even more area and consume higher pow ...

The miniaturization of integrated circuits (ICs) and their higher performance and energy efficiency, combined with new machine learning algorithms and applications, have paved the way to intelligent, interconnected edge devices. In the medical domain, they ...

In this paper, we propose an analytical stochastic dynamic programming (SDP) algorithm to address the optimal management problem of price-maker community energy storage. As a price-maker, energy storage smooths price differences, thus decreasing energy arb ...

Real-Time High-Resolution Multiple-Camera Depth Map Estimation Hardware and Its Applications

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EdgeAI-Aware Design of In-Memory Computing Architectures

Graph generative deep learning models with an application to circuit topologies

Quantum Protocols for ML, Physics, and Finance

Reliable data-driven decision-making through optimal transport

Advancing Self-Supervised Deep Learning for 3D Scene Understanding

FlexiMem: Flexible Shared Virtual Memory for PCIe-attached FPGAs

Accelerator-driven Data Arrangement to Minimize Transformers Run-time on Multi-core Architectures

Highly Parallel RTL Simulation

DBFS: Dynamic Bitwidth-Frequency Scaling for Efficient Software-defined SIMD

Design and in vitro Characterization of a Wearable Multisensing System for Hydration Monitoring

X-Attack 2.0: The Risk of Power Wasters and Satisfiability Don’t-Care Hardware Trojans to Shared Cloud FPGAs

Efficient Continual Finite-Sum Minimization

Reactive collision-free motion generation in joint space via dynamical systems and sampling-based MPC

Multi-Ported GC-eDRAM Bitcell with Dynamic Port Configuration and Refresh Mechanism

Exploring brain-inspired multi-core heterogeneous hardware templates for low-power biomedical embedded systems

Energy Management of Price-Maker Community Energy Storage by Stochastic Dynamic Programming