The acceleration of Computer Vision algorithms is an important enabler to support the more and more pervasive applications of the embedded vision domain. Heterogeneous systems featuring a clustered many-core accelerator are a very promising target for embedded vision workloads, but the code optimization for these platforms is a challenging task. In this work we introduce ADRENALINE, a novel framework for fast prototyping and optimization of OpenVX applications for heterogeneous SoCs with many-core accelerators. ADRENALINE consists of an optimized OpenVX run-time system and a virtual platform, and it is intended to provide support to a wide range of end users. We highlight the benefits of this approach in different optimization contexts.
Tagliavini, G., Haugou, G., Marongiu, A., Benini, L. (2015). ADRENALINE: An OpenVX Environment to Optimize Embedded Vision Applications on Many-core Accelerators. Institute of Electrical and Electronics Engineers Inc. [10.1109/MCSoC.2015.45].
ADRENALINE: An OpenVX Environment to Optimize Embedded Vision Applications on Many-core Accelerators
Tagliavini, Giuseppe;Marongiu, Andrea;Benini, Luca
2015
Abstract
The acceleration of Computer Vision algorithms is an important enabler to support the more and more pervasive applications of the embedded vision domain. Heterogeneous systems featuring a clustered many-core accelerator are a very promising target for embedded vision workloads, but the code optimization for these platforms is a challenging task. In this work we introduce ADRENALINE, a novel framework for fast prototyping and optimization of OpenVX applications for heterogeneous SoCs with many-core accelerators. ADRENALINE consists of an optimized OpenVX run-time system and a virtual platform, and it is intended to provide support to a wide range of end users. We highlight the benefits of this approach in different optimization contexts.File | Dimensione | Formato | |
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