R-Blocks: an Energy-Efficient, Flexible, and Programmable CGRA

Research output: Contribution to journalArticleAcademicpeer-review

152 Downloads (Pure)

Abstract

Emerging data-driven applications in the embedded, e-Health, and internet of things (IoT) domain require complex on-device signal analysis and data reduction to maximize energy efficiency on these energy-constrained devices. Coarse-grained reconfigurable architectures (CGRAs) have been proposed as a good compromise between flexibility and energy efficiency for ultra-low power (ULP) signal processing. Existing CGRAs are often specialized and domain-specific or can only accelerate simple kernels, which makes accelerating complete applications on a CGRA while maintaining high energy efficiency an open issue. Moreover, the lack of instruction set architecture (ISA) standardization across CGRAs makes code generation using current compiler technology a major challenge.

This work introduces R-Blocks; a ULP CGRA with HW/SW co-design tool-flow based on the OpenASIP toolset. This CGRA is extremely flexible due to its well-established VLIW-SIMD execution model and support for flexible SIMD-processing, while maintaining an extremely high energy efficiency using software bypassing, optimized instruction delivery, and local scratchpad memories. R-Blocks is synthesized in a commercial 22-nm FD-SOI technology and achieves a full-system energy efficiency of 115 MOPS/mW on a common FFT benchmark, 1.45x higher than a highly tuned embedded RISC-V processor. Comparable energy efficiency is obtained on multiple complex workloads, making R-Blocks a promising acceleration target for general-purpose computing.
Original languageEnglish
Article number34
Pages (from-to)1-34
Number of pages34
JournalACM Transactions on Reconfigurable Technology and Systems
Volume17
Issue number2
Early online date10 May 2024
DOIs
Publication statusPublished - Jun 2024

Keywords

  • Coarse-grained reconfigurable architecture
  • HW/SW co-design
  • Code generation
  • Energy efficiency
  • code generation

Fingerprint

Dive into the research topics of 'R-Blocks: an Energy-Efficient, Flexible, and Programmable CGRA'. Together they form a unique fingerprint.

Cite this