English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Generation of optimal codes is a well known problem in coding theory. Manycomputational approaches exist in the literature for finding record breakingcodes. However generating codes with long lengths $n$ using serial algorithmsis computationally very expensive, for example the worst case time complexityof a Greedy algorithm is $\mathcal{O}(n\; 4^n)$. In order to improve theefficiency of generating codes with long lengths, we propose and investigatesome parallel algorithms using General Purpose Graphic Processing Units(GPGPU). This paper considers the implementation of parallel Greedy algorithmusing GPGPU-CUDA (Computed Unified Device Architecture) framework and discussesvarious optimization techniques to accelerate the GPU code. The performanceachieved for optimized parallel implementations is more than two to threeorders of magnitude faster than that of serial implementation and shows a greatpotential of GPGPU in the field of coding theory applications.

Generating Binary Optimal Codes Using Heterogeneous Parallel Computing