Hardware Support for Big Data

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Big data workloads requires hardware acceleration through heterogeneous computing systems. The group will focus in developing new hardware architectures specialized for big data workloads.

Summary

Next-generation analytics and big data workloads will require hardware acceleration, including using GPUs, many-core accelerators, FPGAs, neuromorphic computing, and specialized ASICs.  This change is driven by a slowdown in Moore’s Law and Dennard scaling, which increases the return-on-investment from specialization and tuning.  The trend towards accelerators is already visible, as Microsoft is employing FPGAs to accelerate Bing searches, and Intel expects a third of cloud service providers to be using hybrid CPU—FPGA servers by 2020. The group will focus in developing new hardware architectures specialized for big data workloads.

Objectives

  • Develop Hardware for Big Data
  • HW/SW Codesign for Big Data Kernels
    • ADRIAN CRISTAL KESTELMAN's picture
    • Contact
    • ADRIAN CRISTAL KESTELMAN
    • Computer Arquitecture For Parallel Paradigms Group Manager
    • Tel: +34 934054292
    • OSMAN UNSAL's picture
    • Contact
    • OSMAN UNSAL
    • Computer Architecture For Parallel Paradigms Group Manager
    • Tel: +34 934054293