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Reconfigurable Computing

Multi-core and even many-core processors have been successfully used in other domains. Reconfigurable array processors, for instance, have been actively researched and used as an on-chip accelerator for stream processing applications and embedded processors, due to their extremely low power and high performance execution, compared to general purpose processors or even DSPs (digital signal processors).

However, the main challenge in such accelerator-type reconfigurable processors is compilation — the problem of how to map applications onto the architecture. At the heart of this problem is the 2D placement-and-routing problem, which is traditionally recognized as a CAD problem, which is why this problem is often discussed in the design automation communities. Still the problem needs more research and development efforts (such as mature tool chains) for more wide-spread adoption of the architecture.

The ECL Lab is actively pursuing research on this topic, with a few specific goals in mind. We have two granted projects on this, partially in collaboration with other labs.


Figure 1: An accelerator-type reconfigurable processor architecture (Bougard et al. ’08).

Research Questions

  • how to compile the usual C programs (“legacy”) onto coarse-grained reconfigurable architectures?
  • can there be good architectural solutions (such as architecture extensions) to make it much easier to map programs to these architectures (“compiler-friendly architectures”)?
  • what are the real bottleneck to enhancing performance through these processors and how to address them?
    • application level mapping problem


  • Compiling Control-Intensive Loops for CGRAs with State-Based Full Predication, Kyuseung Han, Kiyoung Choi, and Jongeun Lee, Proc. of Design, Automation and Test in Europe (DATE ’13), March, 2013.
  • Architecture Customization of On-Chip Reconfigurable Accelerators, Jonghee W. Yoon, Jongeun Lee*, Sanghyun Park, Yongjoo Kim, Jinyong Lee, Yunheung Paek, and Doosan Cho, ACM Transactions on Design Automation of Electronic Systems (TODAES), 18(4), pp. 52:1-52:22, ACM, October, 2013.
  • Improving Performance of Nested Loops on Reconfigurable Array Processors, Yongjoo Kim, Jongeun Lee*, Toan X. Mai, and Yunheung Paek, ACM Transactions on Architecture and Code Optimization (TACO), 8(4), pp. 32:1-32:23, ACM, January, 2012.
  • Exploiting Both Pipelining and Data Parallelism with SIMD Reconfigurable Architecture, Yongjoo Kim, Jongeun Lee*, Jinyong Lee, Toan X. Mai, Ingoo Heo, and Yunheung Paek, Proc. of International Symposium on Applied Reconfigurable Computing (ARC ’12), Lecture Notes in Computer Science, vol. 7199, pp. 40-52, March, 2012.
  • High Throughput Data Mapping for Coarse-Grained Reconfigurable Architectures, Yongjoo Kim, Jongeun Lee*, Aviral Shrivastava, Jonghee W. Yoon, Doosan Cho, and Yunheung Paek, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), 30(11), pp. 1599-1609, IEEE, November, 2011.
  • Memory Access Optimization in Compilation for Coarse Grained Reconfigurable Architectures, Yongjoo Kim, Jongeun Lee*, Aviral Shrivastava, and Yunheung Paek, ACM Transactions on Design Automation of Electronic Systems (TODAES), 16(4), pp. 42:1-42:27, ACM, October, 2011.

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