Nowadays Embedded Computer Vision (ECV) is considered a technology enabler for next generation killer apps, and scientific and industrial communities are showing a growing interest in developing applications on high-end embedded systems. Modern many-core accelerators are a promising target for running common ECV algorithms, since their architectural features are particularly suitable in terms of data access patterns and program control flow. In this work we propose a set of software optimization techniques, mainly based on data tiling and local buffering policies, which are specifically targeted to accelerate the execution of OpenVX-based ECV applications by exploiting the memory hierarchy of STHORM many-core accelerator.
Tagliavini, G., Haugou, G., Benini, L. (2014). Supporting localized openvx kernel execution for efficient computer vision application development on sthorm many-core platform. Association for Computing Machinery [10.1145/2597917.2597947].
Supporting localized openvx kernel execution for efficient computer vision application development on sthorm many-core platform
TAGLIAVINI, GIUSEPPE;BENINI, LUCA
2014
Abstract
Nowadays Embedded Computer Vision (ECV) is considered a technology enabler for next generation killer apps, and scientific and industrial communities are showing a growing interest in developing applications on high-end embedded systems. Modern many-core accelerators are a promising target for running common ECV algorithms, since their architectural features are particularly suitable in terms of data access patterns and program control flow. In this work we propose a set of software optimization techniques, mainly based on data tiling and local buffering policies, which are specifically targeted to accelerate the execution of OpenVX-based ECV applications by exploiting the memory hierarchy of STHORM many-core accelerator.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
