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The widespread diffusion of compute-intensive edge-AI workloads and the stringent demands of modern autonomous systems require advanced heterogeneous embedded architectures. Such architectures must support high-performance and reliable…

Cryptographic operations are critical for securing IoT, edge computing, and autonomous systems. However, current RISC-V platforms lack efficient hardware support for comprehensive cryptographic algorithm families and post-quantum…

This paper presents a novel System-on-Chip (SoC) architecture for accelerating complex deep learning models for edge computing applications through a combination of hardware and software optimisations. The hardware architecture tightly…

In deep learning frameworks, weight pruning is a widely used technique for improving computational efficiency by reducing the size of large models. This is especially critical for convolutional operators, which often act as performance…

The upcoming many-core architectures require software developers to exploit concurrency to utilize available computational power. Today's high-level language virtual machines (VMs), which are a cornerstone of software development, do not…

In-cache computing technology transforms existing caches into long-vector compute units and offers low-cost alternatives to building expensive vector engines for mobile CPUs. Unfortunately, existing long-vector Instruction Set Architecture…

Whilst RISC-V has become popular in fields such as embedded computing, it is yet to find mainstream success in High Performance Computing (HPC). However, the 64-core RISC-V Sophon SG2042 is a potential game changer as it provides a…

Whilst RISC-V has grown phenomenally quickly in embedded computing, it is yet to gain significant traction in High Performance Computing (HPC). However, as we move further into the exascale era, the flexibility offered by RISC-V has the…

Architectural simulators help in better understanding the behaviour of existing architectures and the design of new architectures. Virtualization has regained importance and this has put a pressing demand for the simulation of virtualized…

RISC-V is a promising open-source architecture primarily targeted for embedded systems. Programs compiled using the RISC-V toolchain can run bare-metal on the system, and, as such, can be vulnerable to several memory corruption…

RISC-V GPUs present a promising path for supporting GPU applications. Traditionally, GPUs achieve high efficiency through the SPMD (Single Program Multiple Data) programming model. However, modern GPU programming increasingly relies on…

Flexible Electronics (FE) technology offers uniquecharacteristics in electronic manufacturing, providing ultra-low-cost, lightweight, and environmentally-friendly alternatives totraditional rigid electronics. These characteristics enable a…

The Advanced Encryption Standard (AES) is a widely adopted cryptographic algorithm essential for securing embedded systems and IoT platforms. However, existing AES hardware accelerators often face limitations in performance, energy…

The RISC-V Instruction Set Architecture (ISA) has enjoyed phenomenal growth in recent years, however it still to gain popularity in HPC. Whilst adopting RISC-V CPU solutions in HPC might be some way off, RISC-V based PCIe accelerators offer…

In the past decades, there has been a significant increase in sensor density and sensor deployment, driven by a significant miniaturization and decrease in size down to the chip level, addressing ubiquitous computing, edge computing, as…

Multimodal Large Language Models (MLLMs) are undergoing rapid progress and represent the frontier of AI development. However, their training and inference efficiency have emerged as a core bottleneck in making MLLMs more accessible and…

In computer architecture courses, we usually teach RISC processors using a five-stage pipeline, neglecting alternative organizations. This design choice, rooted in the 1980s technology, may not be optimal today, and it is certainly not the…

The emergence of heterogeneity and domain-specific architectures targeting deep learning inference show great potential for enabling the deployment of modern CNNs on resource-constrained embedded platforms. A significant development is the…

RISC-V is an open instruction set architecture recently developed for embedded real-time systems. To achieve a lasting security on these systems and design efficient countermeasures, a better understanding of vulnerabilities to novel and…

Software stacks embedded on microcontroller-based hardware typically provide rudimentary APIs programmed in C/C++, basic connectivity and, sometimes, a firmware update mechanism. Such coarse mechanisms contrast with widely used APIs and…