High Performance Heterogeneous Multicore Architectures: A Study

Research output: Contribution to ConferencePaperpeer-review


The significant increase in the need for high- performance and energy-efficient computing systems has introduced heterogenous computing. However, the incorporation of different architectures into one system complicates the distribution of the workload between architectures. To address this challenge while meeting the goals of high-performance computing systems, several research contributions have been made. This paper reviews some of the proposed workload partitioning approaches for GPU-based, DSP-based and FPGA-based heterogenous systems. This research also covers some comparison studies regarding the FPGA versus DSP and FPGA versus GPU debates, showing that sometimes collaboration between these architectures seems to be the key. The aim of this study is to provide academic and industrial researchers with an insight of techniques to achieve the workload balancing in heterogenous systems and motivate them for further research in the field.
Original languageEnglish
Number of pages5
Publication statusPublished - 25 Sep 2019
EventInternational Symposium on Computer Science and Intelligent Control - Amsterdam, Netherlands
Duration: 25 Sep 201927 Sep 2019


ConferenceInternational Symposium on Computer Science and Intelligent Control
Abbreviated titleISCSIC 2019
Internet address


  • CPU
  • GPU
  • DSP
  • FPGA
  • Processing Unit
  • Workload Partitioning
  • Processing Capabilities


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