Zobrazeno 1 - 10
of 6 841
pro vyhledávání: '"Design Space Exploration"'
Publikováno v:
Applied Mechanics, Vol 5, Iss 1, Pp 192-211 (2024)
Composite curing through infrared radiation (IR) has become a popular autoclave alternative due to lower energy costs and short curing cycles. As such, understanding and measuring the effect of all parameters involved in the process can aid in select
Externí odkaz:
https://doaj.org/article/1e210afe67954e028232e3a595e291a3
Publikováno v:
IEEE Access, Vol 12, Pp 82584-82598 (2024)
A cooperative intelligent transport system (C-ITS) enables information sharing among ITS subsystems, such as vehicle and roadside infrastructure, with vehicle-to-everything (V2X) communications. Novel C-ITS applications aim to reduce traffic congesti
Externí odkaz:
https://doaj.org/article/0e8579604f7d4a0bad7c7682dadabbf8
Autor:
Choonghoon Park, Soonhoi Ha
Publikováno v:
IEEE Access, Vol 12, Pp 38773-38785 (2024)
Contemporary smartphones integrate dedicated AI accelerators alongside CPUs and GPUs, in response to the growing demand for deep learning applications. While existing software development kits (SDKs) for these devices provide neural network optimizat
Externí odkaz:
https://doaj.org/article/0232cf24e5a14772a05553e6b6b28af4
Design Space Exploration for Edge Machine Learning Featured by MathWorks FPGA DL Processor: A Survey
Autor:
Stefano Bertazzoni, Lorenzo Canese, Gian Carlo Cardarilli, Luca Di Nunzio, Rocco Fazzolari, Marco Re, Sergio Spano
Publikováno v:
IEEE Access, Vol 12, Pp 9418-9439 (2024)
This paper proposes a Design Space Exploration for Edge machine learning through the utilization of the novel MathWorks FPGA Deep Learning Processor IP, featured in the HDL Deep Learning toolbox. With the ever-increasing demand for real-time machine
Externí odkaz:
https://doaj.org/article/154825a88684484eaaaf5bb2425c3f6a
Publikováno v:
Sensors, Vol 24, Iss 7, p 2239 (2024)
Convolutional neural networks (CNNs) have significantly advanced various fields; however, their computational demands and power consumption have escalated, posing challenges for deployment in low-power scenarios. To address this issue and facilitate
Externí odkaz:
https://doaj.org/article/859f6de3f2bb444f80daf4191b127def
Autor:
Malte Wabnitz, Tobias Gemmeke
Publikováno v:
Memories - Materials, Devices, Circuits and Systems, Vol 5, Iss , Pp 100066- (2023)
The capabilities of artificial neural networks are rapidly evolving, so are the expectations for them to solve ever more challenging tasks in numerous everyday situations. Larger, more complex networks and the need to execute them efficiently on edge
Externí odkaz:
https://doaj.org/article/325a9e28400b493eb489081ab4de8f55
Publikováno v:
IEEE Access, Vol 11, Pp 55361-55369 (2023)
Techniques, like pruning and dimension reduction, and characteristics of data for applications, like natural language processing and object detection, introduce sparsity in deep learning models inherently. Sparse tensor accelerators leverage sparsity
Externí odkaz:
https://doaj.org/article/ef3196c486e14386993891207a41f6e1
Autor:
Rubens Vicente De Liz Bomer, Cesar Albenes Zeferino, Laio Oriel Seman, Valderi Reis Quietinho Leithardt
Publikováno v:
IEEE Access, Vol 11, Pp 25120-25131 (2023)
Network-on-Chip (NoC) is the ideal interconnection architecture for many-core systems due to its superior scalability and performance. An NoC must deliver critical messages from a real-time application within specific deadlines. A violation of this r
Externí odkaz:
https://doaj.org/article/d6f5d930c74e4cfa909bd4c884815d4a
Publikováno v:
IEEE Access, Vol 11, Pp 19301-19311 (2023)
For fixed-application scenarios in embedded soft-realtime computing, the ideal (w.r.t. energy consumption) heterogeneous multi-core CPU design within given chip dimensions can be configured by composing it from given pre-layouted, rectangular chip su
Externí odkaz:
https://doaj.org/article/a24d309924e942e8bbfe74d9c44b57ee
Autor:
Muhammad Awais Rajput, Sultan Alyami, Qazi Arbab Ahmed, Hani Alshahrani, Yousef Asiri, Asadullah Shaikh
Publikováno v:
IEEE Access, Vol 11, Pp 18291-18299 (2023)
Design methodologies for approximation of medium to large-scale accelerators have largely relied on search-based design space exploration. Due to the enormously sized solution space, Artificial Intelligence (AI) based heuristic search has remained on
Externí odkaz:
https://doaj.org/article/824d6d668eca4ace91c66d45281c1535