Title
Hardware design methodology using lightweight dataflow and its integration with low power techniques.
Abstract
Dataflow models of computation are capable of providing high-level descriptions for hardware and software components and systems, facilitating efficient processes for system-level design. The modularity and parallelism of dataflow representations make them suitable for key aspects of design exploration and optimization, such as efficient scheduling, task synchronization, memory and power management. The lightweight dataflow (LWDF) programming methodology provides an abstract programming model that supports dataflow-based design of signal processing hardware and software components and systems. Due to its formulation in terms of abstract application programming interfaces, the LWDF methodology can be integrated with a wide variety of simulation- and implementation-oriented languages, and can be targeted across different platforms, which allows engineers to integrate dataflow modeling approaches relatively easily into existing design processes. Previous work on LWDF techniques has emphasized their application to DSP software implementation (e.g., through integration with C and CUDA). In this paper, we efficiently integrate the LWDF methodology with hardware description languages (HDLs), and we apply this HDL-integrated form of the methodology to develop efficient methods for low power DSP hardware implementation. The effectiveness of the proposed LWDF-based hardware design methodology is demonstrated through a case study of a deep neural network application for vehicle classification.
Year
DOI
Venue
2017
10.1016/j.sysarc.2017.06.003
Journal of Systems Architecture
Keywords
Field
DocType
Dataflow,Deep neural networks,Digital systems design,Low power design,Signal processing,Clock gating,Globally asynchronous locally synchronous
Signal programming,Computer science,Real-time computing,Dataflow,Software,Software development process,Application programming interface,Computer hardware,Hardware description language,Computer architecture,Programming paradigm,Parallel computing,Component-based software engineering,Embedded system
Journal
Volume
ISSN
Citations 
78
1383-7621
1
PageRank 
References 
Authors
0.37
14
10
Name
Order
Citations
PageRank
Tiziana Fanni187.01
Lin Li232.08
Timo Viitanen33611.56
Carlo Sau42210.14
Renjie Xie554.16
Francesca Palumbo66718.37
Luigi Raffo726538.89
Heikki Huttunen824428.20
Jarmo Takala955276.39
Shuvra S. Bhattacharyya101416162.67