Related papers: Enabling Effective FPGA Debug using Overlays: Oppo…
The capacity to adapt can greatly influence the success of systems that need to compensate for damaged parts, learn how to achieve robust performance in new environments, or exploit novel opportunities that originate from new technological…
In this work, we present a systematic study of this trade-off from a deployment-centric perspective, focusing on an autonomous driving scenario. Instead of treating overlay and customized acceleration as isolated design points, we analyze…
While significant progress has been made in automating various aspects of software development through coding agents, there is still significant room for improvement in their bug fixing capabilities. Debugging and investigation of runtime…
The edge computing paradigm has emerged to handle cloud computing issues such as scalability, security and low response time among others. This new computing trend heavily relies on ubiquitous embedded systems on the edge. Performance and…
Modern generations of field-programmable gate arrays (FPGAs) allow for partial reconfiguration. In an online context, where the sequence of modules to be loaded on the FPGA is unknown beforehand, repeated insertion and deletion of modules…
Artificial Intelligence has gained a lot of traction in the recent years, with machine learning notably starting to see more applications across a varied range of fields. One specific machine learning application that is of interest to us…
Overlay measurements are a critical part of modern semiconductor fabrication, but overlay targets have not scaled down in the way devices have. In this work, we produce overlay targets with very small footprint, consisting of just a few…
The new vision presented is aimed to overcome the logic overhead issues that previous works exhibit when applying GALS techniques to programmable logic devices. The proposed new view relies in a 2-phase, bundled data parity based protocol…
Overlay architectures implemented on FPGA devices have been proposed as a means to increase FPGA adoption in general-purpose computing. They provide the benefits of software such as flexibility and programmability, thus making it easier to…
In this work, we propose a configurable many-core overlay for high-performance embedded computing. The size of internal memory, supported operations and number of ports can be configured independently for each core of the overlay. The…
The ability to incorporate quantum phenomena in computing unlocks a host of new ways to make mistakes. This work surveys existing studies and approaches to debugging quantum programs. It then presents a set of examples that stem from…
Growing global concerns about climate change highlight the need for environmentally sustainable computing. The ecological impact of computing, including operational and embodied, is a key consideration. Field Programmable Gate Arrays…
Multiverse analysis, a paradigm for statistical analysis that considers all combinations of reasonable analysis choices in parallel, promises to improve transparency and reproducibility. Although recent tools help analysts specify…
As the one-chip integration of HW-modules designed by different companies becomes more and more popular reliability of a HW-design and evaluation of the timing behavior during the prototype stage are absolutely necessary. One way to…
We present a tool flow and results for a model-based hardware design for FPGAs from Simulink descriptions which nicely integrates into existing environments. While current commercial tools do not exploit some high-level optimizations, we…
FPGA accelerators are gaining increasing attention in both cloud and edge computing because of their hardware flexibility, high computational throughput, and low power consumption. However, the design flow of FPGAs often requires specific…
A substantial fraction of the time that computational modellers dedicate to developing their models is actually spent trouble-shooting and debugging their code. However, how this process unfolds is seldom spoken about, maybe because it is…
Robotic computing has reached a tipping point, with a myriad of robots (e.g., drones, self-driving cars, logistic robots) being widely applied in diverse scenarios. The continuous proliferation of robotics, however, critically depends on…
With the rapid development of in-depth learning, neural network and deep learning algorithms have been widely used in various fields, e.g., image, video and voice processing. However, the neural network model is getting larger and larger,…
Today, artificial neural networks are one of the major innovators pushing the progress of machine learning. This has particularly affected the development of neural network accelerating hardware. However, since most of these architectures…