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dc.contributor.authorPaolo, Savio-
dc.contributor.authorAlberto, Scionti-
dc.contributor.authorGiacomo, Vitali-
dc.date.accessioned2023-03-30T04:09:16Z-
dc.date.available2023-03-30T04:09:16Z-
dc.date.issued2023-
dc.identifier.urihttps://link.springer.com/article/10.1007/s11227-022-04925-2-
dc.identifier.urihttps://dlib.phenikaa-uni.edu.vn/handle/PNK/7329-
dc.descriptionCC BYvi
dc.description.abstractHeterogeneous computing is the major driving factor in designing new energy-efficient high-performance computing systems. Despite the broad adoption of GPUs and other specialized architectures, the interest in spatial architectures like field-programmable gate arrays (FPGAs) has grown. While combining high performance, low power consumption and high adaptability constitute an advantage, these devices still suffer from a weak software ecosystem, which forces application developers to use tools requiring deep knowledge of the underlying system, often leaving legacy code (e.g., Fortran applications) unsupported.vi
dc.language.isoenvi
dc.publisherSpringervi
dc.subjectenergy-efficient high-performance computing systemsvi
dc.subjectFPGAsvi
dc.titleAccelerating legacy applications with spatial computing devicesvi
dc.typeBookvi
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