17 papers · ranked by Valyu relevance
Jiménez, Arturo Urías
AI acceleration has been dominated by GPUs, but the growing need for lower latency, energy efficiency, and fine-grained hardware control exposes the limits of fixed architectures. In this context, Field-Programmable Gate Arrays (FPGAs) emerge as a reconfigurable platform that allows mapping AI algorithms directly into…
Zhi Qi, Weijian Chen, Rizwan Ali Naqvi, Kamran Siddique
With the swift development of deep learning applications, the convolutional neural network (CNN) has brought a tremendous challenge to traditional processors to fulfil computing requirements. It is urgent to embrace new strategies to improve efficiency and diminish energy consumption. Currently, diverse accelerator…
Kyriakos M. Deliparaschos, Spyros G. Tzafestaş
— This paper focuses on the Field Programmable Gate Array (FPGA) design and implementation of intelligent control system applications on a chip, specifically fuzzy logic and genetic algorithm processing units. Initially, an overview of the FPGA technology is presented, followed by design methodologies, development…
Antonio de la Piedra, An Braeken, Abdellah Touhafi
In this manuscript, we present a survey of designs and implementations of research sensor nodes that rely on FPGAs, either based upon standalone platforms or as a combination of microcontroller and FPGA. Several current challenges in sensor networks are distinguished and linked to the features of modern FPGAs. As it…
Safaa J. Kasbah, Issam Damaj, Ramzi A. Haraty
The problem of finding the solution of Partial Differential Equations (PDEs) plays a central role in modeling real world problems. Over the past years, Multigrid solvers have showed their robustness over other techniques, due to its high convergence rate which is independent of the problem size. For this reason, many…
Marcian Cirstea, Khaled Benkrid, Andrei Dinu, Romeo Ghiriti + 2 more
This paper reviews the evolution of methodologies and tools for modeling, simulation, and design of digital electronic system-on-chip (SoC) implementations, with a focus on industrial electronics applications. Key technological, economic, and geopolitical trends are presented at the outset, before reviewing SoC design…
Gabriel J. García, Carlos A. Jara, Jorge Pomares, Aiman Alabdo + 2 more
'Lucas M. Poggi' 'Fernando Torres'] The current trend in the evolution of sensor systems seeks ways to provide more accuracy and resolution, while at the same time decreasing the size and power consumption. The use of Field Programmable Gate Arrays (FPGAs) provides specific reprogrammable hardware technology that can…
Laraib Khan, Sriram Praneeth Isanaka, Frank Liou, Flavio Esposito + 2 more
'Stefania Campopiano' 'Agostino Iadicicco'] The combination of distributed digital factories (D2Fs) with sustainable practices has been proposed as a revolutionary technique in modern manufacturing. This review paper explores the convergence of D2F with innovative sensor technology, concentrating on the role of Field…
R. Aafreen, R Abhishek, B. Ajithkumar, Arunkumar M. Vaidyanathan + 33 more
'Indrajit V. Barve' 'Sahana Bhattramakki' 'Shashank Bhat' 'B. S. Girish' 'Atul Ghalame' 'Yashwant Gupta' 'Harshal Hayatnagarkar' 'P. A. Kamini' 'A. Karastergiou' 'L. Levin' 'Madhavi Srinivasan' 'M. Mekhala' 'M. B. Mickaliger' 'V. Mugundhan' 'Arun Naidu' 'Julian Oppermann' 'Arul Pandian' 'Nipanjana Patra' 'A.…
Joran Deschamps, Christian Kieser, Philipp Hoess, Takahiro Deguchi + 1 more
Modern microscopy relies increasingly on microscope automation to improve throughput, ensure reproducibility or observe rare events. Automation requires in particular computer control of the important elements of the microscope. Furthermore, optical elements that are usually fixed or manually movable can be placed on…
Abedalmuhdi Almomany, Amin Jarrah, Muhammed Sutcu, Jun Ma
A key benefit of the Open Computing Language (OpenCL) software framework is its capability to operate across diverse architectures. Field programmable gate arrays (FPGAs) are a high-speed computing architecture used for computation acceleration. This study investigates the impact of memory access time on overall…
Nikolaos Alachiotis, Sjoerd van den Belt, Steven van der Vlugt, Reinier van der Walle + 9 more
Future Outlook Authors: ['Nikolaos Alachiotis' 'Sjoerd van den Belt' 'Steven van der Vlugt' 'Reinier van der Walle' 'Mohsen Safari' 'Bruno Endres Forlin' 'Tiziano De Matteis' 'Zaid Al-Ars' 'Roel Jordans' 'António J. Sousa de Almeida' 'Federico Corradi' 'Christiaan Baaij' 'Ana-Lucia Varbanescu'] NIKOLAOS ALACHIOTIS…
Yusuke Shinji, Hirotsugu Okuno, Yutaka Hirata
The cerebellum plays a central role in motor control and learning. Its neuronal network architecture, firing characteristics of component neurons, and learning rules at their synapses have been well understood in terms of anatomy and physiology. A realistic artificial cerebellum with mimetic network architecture and…
Yaniv Swiel, Jean-Tristan Brandenburg, Mahtaab Hayat, Wenlong Carl Chen + 2 more
Genome-wide association studies (GWASs) analyse genetic variation over the genomes of many individuals in an attempt to identify single nucleotide polymorphisms (SNPs) associated with complex phenotypes. To capture a large amount of genetic variation and increase the chance of detecting associated SNPs, modern GWASs…
Shih‐Yi Yuan, Bo-Yu Zhu
We proposes a platform which can generate hardware/software description based on flexible instruction set architectures (ISAs). The platform takes advantage of the flexibility of field programmable gate array (FPGA) to design many micro control units (MCUs) based on different ISAs. The platform can generate many ISAs…
Kisaru Liyanage, Hiruna Samarakoon, Sri Parameswaran, Hasindu Gamaarachchi
minimap2 is the gold-standard software for reference-based sequence mapping in third-generation long-read sequencing. While minimap2 is relatively fast, further speedup is desirable, especially when processing a multitude of large datasets. In this work, we present minimap2-fpga, a hardware-accelerated version of…
David Rotermund, Klaus R. Pawelzik
While inspired by the brain, currently successful artificial neural networks lack key features of the biological original. In particular, the deep convolutional networks (DCNs) neither use pulses as signals exchanged among neurons, nor do they include recurrent connections which are both core properties of real…