Embedded reconfigurable computing: The ERA approach
Paper in proceeding, 2013

The growing complexity and diversity of embedded systems-combined with continuing demands for higher performance and lower power consumption-places increasing pressure on embedded platforms designers. The target of the ERA project is to offer a holistic, multi-dimensional methodology to address these problems in a unified framework exploiting the inter-and intra-synergism between the reconfigurable hardware (core, memory, and network resources), the reconfigurable software (compiler and tools), and the run-time system. Starting from the hardware level, we design our platform via a structured approach that allows integration of reconfigurable computing elements, network fabrics, and memory hierarchy components. These hardware elements can adapt their composition, organization, and even instruction-set architectures to exploit tradeoffs in performance and power. Appropriate hardware resources can be selected both statically at design time and dynamically at run time. Hardware details are exposed to our custom operating system, our custom runtime system, and our adaptive compiler, and are even visible all the way up to the application level. The design philosophy followed in the ERA project proved efficient enough not only to enable a better choice of power/performance trade-offs but also to support fast platform prototyping of high-efficiency embedded system designs. In this paper, we present a brief overview of the design approach, the major outcomes, and the lessons learned in the ERA project.

Adaptive embedded platform

Hardware-software codesign

Reconfigurable computing.

Author

G. Keramidas

Industrial Systems Institute

S. Wong

Delft University of Technology

F. Anjam

Delft University of Technology

Anthony Brandon

Delft University of Technology

R. Seedorf

Delft University of Technology

Claudio Scordino

L. Carro

Universidade Federal do Rio Grande do Sul (UFRGS)

Debora Matos

Universidade Federal do Rio Grande do Sul (UFRGS)

R. Giorgi

University of Siena

Stamatis Kavvadias

University of Siena

Sally A McKee

Chalmers, Computer Science and Engineering (Chalmers), Computer Engineering (Chalmers)

Bhavishya Goel

Chalmers, Computer Science and Engineering (Chalmers), Computer Engineering (Chalmers)

Vasileios Spiliopoulos

Uppsala University

IEEE International Conference on Industrial Informatics (INDIN)

19354576 (ISSN)

827-832

Subject Categories

Computer and Information Science

DOI

10.1109/INDIN.2013.6889116

More information

Latest update

10/5/2023