We are in a new era of harnessing computing power and New Zealand can take advantage applying it to our primary industry, across all areas -from genetics and breeding optimization to operations research and financial modeling, with a common pattern -to fully unveil the potential of multicore architectures.
Distributed and parallel computing advance the state of the art in bioinformatics and genomics: New DNA instruments now sequence in days and at low cost, compared to the years of effort and billions of dollars spent to sequence the first human genome.
Open Parallel uses big data management as a bridge between business intelligence and modern business analysis in real-time using high-performance parallel algorithms designed for the cloud. With massively parallel execution and mathematical talent, we fast-track companies into the big data age but..., can we improve Fonterra's $20bn annual revenue in i.e. 3%?
Would a common approach to multicore software and hardware help to achieve this goal?
We are witnessing a rapid increase in the amount of genomic data, and its use in breeding value evaluation. Use of this data is and will be computing intensive and from a computational software development we are still looking at what is the best way to use genomic data. Amount of genomic data keeps changing. There are approaches to use all data, but as number of genotyped animals increases, our computing solutions become inefficient. Thus, today's solutions may be obsolete tomorrow.
Combining existing research like "Parallel computing applied to breeding value estimation in dairy cattle" (Stranden) with “Contribution Margin Optimisation at Fonterra” (Ross, Freimer) we search for common patterns that can be significantly improved with multicore. Cross-pollination between i.e. operations research and breeding optimisation can create improvement of the overall economic results of a given organisation