Communicating sequential processes
Communicating sequential processes
Fundamentals of digital image processing
Fundamentals of digital image processing
Compaan: deriving process networks from Matlab for embedded signal processing architectures
CODES '00 Proceedings of the eighth international workshop on Hardware/software codesign
Embedded Multiprocessors: Scheduling and Synchronization
Embedded Multiprocessors: Scheduling and Synchronization
Smart Cameras as Embedded Systems
Computer
Mulitdimensional Streams Rooted in Dataflow
PACT '93 Proceedings of the IFIP WG10.3. Working Conference on Architectures and Compilation Techniques for Fine and Medium Grain Parallelism
Mapping multirate dataflow to complex RT level hardware models
ASAP '97 Proceedings of the IEEE International Conference on Application-Specific Systems, Architectures and Processors
Stream-Oriented FPGA Computing in the Streams-C High Level Language
FCCM '00 Proceedings of the 2000 IEEE Symposium on Field-Programmable Custom Computing Machines
CODES '94 Proceedings of the 3rd international workshop on Hardware/software co-design
IEEE Transactions on Signal Processing
Parameterized dataflow modeling for DSP systems
IEEE Transactions on Signal Processing
International Journal of Distributed Systems and Technologies
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We develop a design methodology for mapping computer vision algorithms onto an FPGA through the use of coarse-grain reconfigurable dataflow graphs as a representation to guide the designer. We first describe a new dataflow modeling technique called homogeneous parameterized dataflow (HPDF), which effectively captures the structure of an important class of computer vision applications. This form of dynamic dataflow takes advantage of the property that in a large number of image processing applications, data production and consumption rates can vary, but are equal across dataflow graph edges for any particular application iteration. After motivating and defining the HPDF model of computation, we develop an HPDF-based design methodology that offers useful properties in terms of verifying correctness and exposing performance-enhancing transformations; we discuss and address various challenges in efficiently mapping an HPDF-based application representation into target-specific HDL code; and we present experimental results pertaining to the mapping of a gesture recognition application onto the Xilinx Virtex II FPGA.