Recent trends in deep learning (DL) imposed hardware accelerators as the most viable
solution for several classes of high-performance computing (HPC) applications such as …

Computing is an indispensable tool in addressing climate change, but it also contributes to a
significant and steadily increasing carbon footprint, partly due to the exponential growth in …

Autonomous systems, such as Unmanned Aerial Vehicles (UAVs), are expected to run
complex reinforcement learning (RL) models to execute fully autonomous position …

The rapid advancement of energy-efficient parallel ultra-low-power (ULP) controllers units
(MCUs) is enabling the development of autonomous nano-sized unmanned aerial vehicles …

The new generation of domain-specific AI accelerators is characterized by rapidly increasing
demands for bulk data transfers, as opposed to small, latency-critical cache line transfers …

We present a scalable methodology for the agile physical design of tile-based
heterogeneous system-on-chip (SoC) architectures that simplifies the reuse and integration …

On-chip power-management techniques have evolved over several processor generations.
However, response time and scalability constraints have made it difficult to translate existing …

Heterogeneous, multicore SoC architectures are a critical component of today's computing
landscape. However, supporting both increasing heterogeneity and multicore execution are …

Resource-constrained system-on-chips (SoCs) are increasingly heterogeneous with
specialized accelerators for various tasks. Acceleration taxes due to control and data …

This article introduces an open-source, low-latency Network-on-Chip (NoC) designed to
tackle bandwidth challenges faced by traditional narrow and serialized NoCs. The authors …