This paper examines the complexity of the South
In Agenda 2063 the African Union (AU) prioritised the utilisation of the resources in oceans as the new frontier of its blue economy. Africa's "inland waterways" were added to the scope of the blue economy in the 2050 AIM Strategy. Most of Africa's marine ecosystems and large water spaces are shared by different countries which requires the transcendence of national interests, the harmonisation of national and regional policies and multi stakeholder participation in strong institutions guided by a legal framework. The protection, securitisation and sustainable utilisation of blue spaces are key pillars for the governance of the blue economy. The first part focuses on the contribution of Africa's blue spaces to the development of the continent, the growing challenges to these spaces in the twenty-first century and UNCLOS' legal zoning of oceans to manage their protection and utilisation. The second part focuses on the governance of Africa's blue economy and the security challenges to Africa's oceans. The last part focuses on the Benguela Current Large Marine Ecosystem (BCLME) and finds the Benguela Current Commission (BCC) to be legitimate, accountable and its * Rentia Pretorius, Lecturer in the Department of Political Sciences, University of Pretoria, holds an MA degree in Political Science and her research interests are Africa, environmental sustainability, global warming, diplomacy and the global economy.
In both high-performance computing (HPC) environments and the public cloud, the duration of time to retrieve or save your results is simultaneously unpredictable and important to your over all resource budget. It is generally accepted ("Google: Taming the Long Latency Tail -When More Machines Equals Worse Results", Todd Hoff, highscalability.com 2012) , but without a robust explanation, that identical parallel tasks do take different durations to complete -a phenomena known as variability. This paper advances understanding of this topic. We carefully choose a model from which system-level complexity emerges that can be studied directly. We find that a generalized extreme value (GEV) model for variability naturally emerges. Using the public cloud, we find real-world observations have excellent agreement with our model. Since the GEV distribution is a limit distribution this suggests a universal property of parallel systems gated by the slowest communication element of some sort. Hence, this model is applicable to a variety of processing and IO tasks in parallel environments. These findings have important implications, ranging from characterizing ideal performance for parallel codes to detecting degraded behaviour at extreme scales.
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