Design Tools and Architectures for Coarse-Grained Reconfigurable Computing

Dear Colleagues,

Emerging applications are pushing the limits of computing platforms. The scalability of integrated circuit technology has slowed down because of the power wall and the cost wall. Performance is no longer the main metric driving the design of computing platforms, being replaced by energy efficiency and cost. On the other side, emergent applications have a fast-evolving cycle, which reduces the lifecycle of application-specific integrated circuits, increasing their cost.

Reconfigurable computing offers good tradeoffs between cost, energy efficiency, and performance, compared to other computing platforms (GPP, GPU, DSP, etc.). Field-programmable gate arrays are the most used reconfigurable devices. Their fine granularity offers a very flexible hardware device but they are difficult to program and high-density FPGAs are expensive. ASICs have a high non-recurring engineering (NRE) cost that is difficult to support with the new emergent applications with a short lifecycle.

Coarse-grained reconfigurable architectures (CGRAs) offer performance and energy efficiency close to those of ASICs and a programmability level closer to application software, offering a good trade-off between NRE and device cost. However, CGRAs have not yet been widely adopted because of a lack of mature architectures and programming tools.

The objective of this Special Issue is to bring together the latest advances in coarse-grained reconfigurable computing (CGRC), including design tools, architectures, and applications.

CGRC topics include, but are not limited to:

• Coarse-grained reconfigurable architectures;
• Fine-grained versus coarse-grained computing;
• Spatial and temporal computation in CGRA;
• Run-time reconfiguration/adaptation of CGRA;
• Models of computation for CGRA;
• Programming tools and compilers for CGRA;
• Energy-aware compilation for CGRA;
• Simulation tools for CGRA;
• CGRA for domain-specific applications (image processing, deep-learning, network processing, etc.);
• Edge computing and high-performance computing with CGRA.

Prof. Dr. Mário Véstias
Prof. Dr. José Teixeira de Sousa
Guest Editors

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