These groundbreaking results were obtained by further optimizing the code mainly through the removal of redundant code and function calls as well as through the improved memory use of IMEC’s earlier (mid 2007) SVC source code. This code was already two times faster than the reference code.
The first optimization was based on (re)structuring the SVC code into more concise functional blocks. This facilitated extra optimizations, including removing redundant code and function calls. The application of DTSE (Data Transfer and Storage Exploration) transformations enabled intelligent (re)use of the memory footprint. As a result of the increased data locality, the total memory footprint was significantly reduced to one tenth, leading to much better cache behavior and higher performance. This will also contribute to reducing the silicon cost area when using SVC functions for ASIC (application-specific integrated circuit) implementations.
The optimized decoder has been benchmarked against the reference decoder on a normal end user PC platform. Compliancy to the SVC standard was also verified. The configurations that were tested included the three scalability types of SVC, being spatial, temporal and quality scalability. The preliminary performance evaluation shows that IMEC’s decoder is up to 20 times faster than the reference software, while consuming only a tenth of the memory.
The optimized source code is available as starting point for product development by industry via a licensing program and can be delivered as source code. The code is of typical interest for system integrators of mobile devices or telecommunication applications and fabless IC makers to help them extend their multimedia reference platforms to comply with the SVC standard.
Katrien Marent | alfa
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The quantum world is fragile; error correction codes are needed to protect the information stored in a quantum object from the deteriorating effects of noise. Quantum physicists in Innsbruck have developed a protocol to pass quantum information between differently encoded building blocks of a future quantum computer, such as processors and memories. Scientists may use this protocol in the future to build a data bus for quantum computers. The researchers have published their work in the journal Nature Communications.
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