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.
ADRENALINE: An OpenVX Environment to Optimize Embedded Vision Applications on Many-core Accelerators / Tagliavini, Giuseppe; Haugou, Germain; Marongiu, Andrea; Benini, Luca. - STAMPA. - (2015), pp. 289-296. (Intervento presentato al convegno 9th IEEE International Symposium on Embedded Multicore/Manycore SoCs, MCSoC 2015 tenutosi a Polytechnic of Turin, ita nel 2015) [10.1109/MCSoC.2015.45].
ADRENALINE: An OpenVX Environment to Optimize Embedded Vision Applications on Many-core Accelerators
Marongiu Andrea;
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.
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