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Heterogeneous Computing Meets Near-Memory Acceleration and High-Level Synthesis in the Post-Moore Era.

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Title: Heterogeneous Computing Meets Near-Memory Acceleration and High-Level Synthesis in the Post-Moore Era.
Authors: Kim, Nam Sung1, Chen, Deming1, Xiong, Jinjun2, Hwu, Wen-mei W.1
Source: IEEE Micro. Jul2017, Vol. 37 Issue 4, p10-18. 9p.
Subjects: Moore's law, Application software, Energy consumption, Compilers (Computer programs), Performance evaluation
Abstract: As the trends driven by Moore’s law come to an end, increased heterogeneity at all levels of computing is required to deliver the computing performance needed for emerging applications, leading to the proliferation of various application- or domain-specific accelerators. This in turn demands more memory bandwidth, as heterogeneous computing with accelerators consumes data at a much higher rate than traditional homogeneous computing, limiting the computing performance. To tackle this challenge, this article presents a conceptual near-memory acceleration architecture; demonstrates its practicality and plausibility using a recent experimental platform from IBM, as well as its potential impact on performance and energy efficiency; and discusses the need for adopting a high-level synthesis approach for such a near-memory acceleration architecture. Subsequently, this article concludes with future research directions for broad adoption of near-memory acceleration. [ABSTRACT FROM PUBLISHER]
Copyright of IEEE Micro is the property of IEEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: <searchLink fieldCode="JN" term="%22IEEE+Micro%22">IEEE Micro</searchLink>. Jul2017, Vol. 37 Issue 4, p10-18. 9p.
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  Data: <searchLink fieldCode="DE" term="%22Moore's+law%22">Moore's law</searchLink><br /><searchLink fieldCode="DE" term="%22Application+software%22">Application software</searchLink><br /><searchLink fieldCode="DE" term="%22Energy+consumption%22">Energy consumption</searchLink><br /><searchLink fieldCode="DE" term="%22Compilers+%28Computer+programs%29%22">Compilers (Computer programs)</searchLink><br /><searchLink fieldCode="DE" term="%22Performance+evaluation%22">Performance evaluation</searchLink>
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  Data: As the trends driven by Moore’s law come to an end, increased heterogeneity at all levels of computing is required to deliver the computing performance needed for emerging applications, leading to the proliferation of various application- or domain-specific accelerators. This in turn demands more memory bandwidth, as heterogeneous computing with accelerators consumes data at a much higher rate than traditional homogeneous computing, limiting the computing performance. To tackle this challenge, this article presents a conceptual near-memory acceleration architecture; demonstrates its practicality and plausibility using a recent experimental platform from IBM, as well as its potential impact on performance and energy efficiency; and discusses the need for adopting a high-level synthesis approach for such a near-memory acceleration architecture. Subsequently, this article concludes with future research directions for broad adoption of near-memory acceleration. [ABSTRACT FROM PUBLISHER]
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  Data: <i>Copyright of IEEE Micro is the property of IEEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – SubjectFull: Energy consumption
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