Abstract
This paper presents shared-variable synchronization approaches for dataflow programming. The mechanisms do not require any substantial model of computation (MoC) modification, and is portable across both for hardware (HW) and
software (SW) low-level code synthesis. With the shared-variable
formalization, the benefits of the dataflow MoC are maintained,
however the space and energy efficiency of an application can be
significantly improved. The approach targets Dynamic Process
Network (DPN) dataflow applications, thus making them also suitable for less expressive models e.g. synchronous and cyclo-static dataflow that DPN subsumes. The approach is validated through the analysis and optimization of a High-Efficiency Video Coding (HEVC) decoder implemented in the RVC-CAL dataflow language targeting a multi-core platform. Experimental results show how, starting from an initial design that does not use
the shared-variable formalism, frames per second throughput
performance is increased by a factor of 21.
software (SW) low-level code synthesis. With the shared-variable
formalization, the benefits of the dataflow MoC are maintained,
however the space and energy efficiency of an application can be
significantly improved. The approach targets Dynamic Process
Network (DPN) dataflow applications, thus making them also suitable for less expressive models e.g. synchronous and cyclo-static dataflow that DPN subsumes. The approach is validated through the analysis and optimization of a High-Efficiency Video Coding (HEVC) decoder implemented in the RVC-CAL dataflow language targeting a multi-core platform. Experimental results show how, starting from an initial design that does not use
the shared-variable formalism, frames per second throughput
performance is increased by a factor of 21.
| Original language | English |
|---|---|
| Title of host publication | Workshop on Signal Processing Systems 2018 |
| Publisher | IEEE |
| Publication status | Published - Oct 2018 |
| Event | IEEE Workshop on Signal Processing Systems 2018 - Cape Town, South Africa Duration: 21 Oct 2018 → 24 Oct 2018 |
Workshop
| Workshop | IEEE Workshop on Signal Processing Systems 2018 |
|---|---|
| Abbreviated title | IEEE SiPS |
| Country/Territory | South Africa |
| City | Cape Town |
| Period | 21/10/18 → 24/10/18 |
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