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New Solutions for Cross-Layer System-Level and High-Level Synthesis

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Emerging Technology and Architecture for Big-data Analytics

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Abstract

The rise of the Internet of Things—billions of internet connected sensors constantly monitoring the physical environment has coincided with the rise of big data and advanced data analytics that can effectively gather, analyze, generate insights about the data, and perform decision making. Data analytics allows analysis and optimization of massive datasets: deep analysis has led to advancements in business operations optimization, natural language processing, computer vision applications such as object classification, etc. Furthermore, data-processing platforms such as Apache Hadoop (White, Hadoop: the definitive guide. O’Reilly Media, Sebastopol, 2009) have become primary datacenter applications, but the rise of massive data processing also has a major impact on the increasing demand for both datacenter computation and data processing in edge devices to improve scalability of massive sensing applications.

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Notes

  1. 1.

    AutoPilot was acquired by Xilinx, and is now Vivado HLS.

  2. 2.

    A basic block is a portion of the code within a program with only one entry point, only one exit point and without conditional branches.

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Acknowledgements

This work was supported in part by the CFAR Center, one of six centers of STARnet, a Semiconductor Research Corporation program sponsored by MARCO and DARPA, and by A*STAR under the Human-Centered Cyber-Physical Systems (HCCS) grant.

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Authors and Affiliations

  1. Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Champaign, IL, USA

    Wei Zuo

  2. Advanced Digital Sciences Center, Singapore, Singapore

    Swathi Gurumani & Kyle Rupnow

  3. University of Illinois at Urbana Champaign, Champaign, IL, USA

    Deming Chen

Authors
  1. Wei Zuo
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  2. Swathi Gurumani
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  3. Kyle Rupnow
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  4. Deming Chen
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Corresponding author

Correspondence to Deming Chen .

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Editors and Affiliations

  1. School of Computer Science and Engineering, School of Physical and Mathematical Sciences, Nanyang Technological University, Singapore, Singapore

    Anupam Chattopadhyay

  2. School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore

    Chip Hong Chang

  3. School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore

    Hao Yu

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Zuo, W., Gurumani, S., Rupnow, K., Chen, D. (2017). New Solutions for Cross-Layer System-Level and High-Level Synthesis. In: Chattopadhyay, A., Chang, C., Yu, H. (eds) Emerging Technology and Architecture for Big-data Analytics. Springer, Cham. https://doi.org/10.1007/978-3-319-54840-1_5

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  • DOI: https://doi.org/10.1007/978-3-319-54840-1_5

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