Zobrazeno 1 - 10
of 1 084
pro vyhledávání: '"Dataflow architecture"'
Autor:
Dionysios Filippas, Christodoulos Peltekis, Vasileios Titopoulos, Ioannis Kansizoglou, Georgios CH. Sirakoulis, Antonios Gasteratos, Giorgos Dimitrakopoulos
Publikováno v:
IEEE Access, Vol 12, Pp 57194-57208 (2024)
Convolution neural networks (CNNs) are widely applied in many machine learning applications. Hardware acceleration for CNNs is crucial, given their high computational intensity and the demand for enhanced energy efficiency and reduced latency in appl
Externí odkaz:
https://doaj.org/article/33c1766733254d368409fdccc04d5072
Akademický článek
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Akademický článek
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Autor:
Lantsov R.A.
Publikováno v:
Naučno-tehničeskij Vestnik Informacionnyh Tehnologij, Mehaniki i Optiki, Vol 18, Iss 6, Pp 1023-1033 (2018)
The paper considers open computing systems, which provide the necessary growth of performance and memory by mechanical addition of new units without affecting the existing software environment. Such computing systems are based on the application of a
Externí odkaz:
https://doaj.org/article/658d9a15aae6464dbf21292675756cf0
Autor:
Krste Asanovic, Tae Jun Ham, Brendan Sweeney, Seong Hoon Seo, Jae W. Lee, David Bruns-Smith, U Gyeong Song, Yejin Lee, Young H. Oh, Lisa Wu Wills
Publikováno v:
IEEE Micro. 41:42-49
This article presents a framework, Genesis (genome analysis), to efficiently and flexibly accelerate generic data manipulation operations that have become performance bottlenecks in the genomic data processing pipeline utilizing FPGAs-as-a-service. G
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f2609ebf2c11f4de7233b6488ef54b5d
https://doi.org/10.1109/mm.2021.3072385
https://doi.org/10.1109/mm.2021.3072385
Publikováno v:
Information Sciences. 547:1136-1153
Dataflow architecture has native advantages in achieving high instruction parallelism and power efficiency for today’s emerging applications such as high performance computing and deep neural network. In dataflow computing, the execution of instruc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::554647d0fcff03567c060e0b1880d0dc
https://doi.org/10.1016/j.ins.2020.09.029
https://doi.org/10.1016/j.ins.2020.09.029
Akademický článek
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Publikováno v:
Future Generation Computer Systems. 112:580-588
Dataflow architecture has been proved to be promising in high-performance computing. Traditional dataflow architectures are not efficient enough in typical scientific applications such as stencil and FFT due to low utilization of function units. Base
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e5d01ddff717b2076ebefc27f2958c32
https://doi.org/10.1016/j.future.2020.03.023
https://doi.org/10.1016/j.future.2020.03.023
Publikováno v:
IEEE Journal of Solid-State Circuits. 55:2691-2702
A scalable deep-learning accelerator supporting the training process is implemented for device personalization of deep convolutional neural networks (CNNs). It consists of three processor cores operating with distinct energy-efficient dataflow for di
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2faba91d3997c0fa3e6879117daa6214
https://doi.org/10.1109/jssc.2020.3005786
https://doi.org/10.1109/jssc.2020.3005786
Publikováno v:
CCF Transactions on High Performance Computing. 2:362-375
Graph processing is widely used in modern society, such as social networks, bioinformatics, and information networks. It is observed that the dataflow architecture has been demonstrated to effectively resolve the challenges of low instruction-level p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::04d1d8bec8b2c42996ac5bb17ff479d2
https://doi.org/10.1007/s42514-020-00041-w
https://doi.org/10.1007/s42514-020-00041-w