Use of shared memory in the context of embedded multi-core processors: exploration of the technology and its limits

Modern embedded systems embrace many-core shared-memory designs. Due to constrained power and area budgets, most of them feature software-managed scratchpad memories instead of data caches to increase the data locality. It is therefore programmers’ responsibility to explicitly manage the memory transfers, and this make programming these platform cumbersome. Moreover, complex modern applications must be adequately parallelized before they can the parallel potential of the platform into actual performance. To support this, programming languages were proposed, which work at a high level of abstraction, and rely on a runtime whose cost hinders performance, especially in embedded systems, where resources and power budget are constrained. This dissertation explores the applicability of the shared-memory paradigm on modern many-core systems, focusing on the ease-of-programming. It focuses on OpenMP, the de-facto standard for shared memory programming. In a first part, the cost of algorithms for synchronization and data partitioning are analyzed, and they are adapted to modern embedded many-cores. Then, the original design of an OpenMP runtime library is presented, which supports complex forms of parallelism such as multi-level and irregular parallelism. In the second part of the thesis, the focus is on heterogeneous systems, where hardware accelerators are coupled to (many-)cores to implement key functional kernels with orders-of-magnitude of speedup and energy efficiency compared to the “pure software” version. However, three main issues rise, namely i) platform design complexity, ii) architectural scalability and iii) programmability. To tackle them, a template for a generic hardware processing unit (HWPU) is proposed, which share the memory banks with cores, and the template for a scalable architecture is shown, which integrates them through the shared-memory system. Then, a full software stack and toolchain are developed to support platform design and to let programmers exploiting the accelerators of the platform. The OpenMP frontend is extended to interact with it.

Technology Development and Consumer Acceptance of Innovation in Fruit Production

Precision Agriculture (PA) and the more specific branch of Precision Horticulture are two very promising sectors. They focus on the use of technologies in agriculture to optimize the use of inputs, so to reach a better efficiency, and minimize waste of resources. This important objective motivated many researchers and companies to search new technology solutions. Sometimes the effort proved to be a good seed, but sometimes an unfeasible idea. So that PA, from its birth more or less 25 years ago, is still a “new” management, interesting for the future, but an actual low adoption rate is still reported by experts and researchers. This work aims to give a contribution in finding the causes of this low adoption rate and proposing a methodological solution to this problem. The first step was to examine prior research about Precision Agriculture adoption, by ex ante and ex post approach. It was supposed as important to find connections between these two phases of a purchase experience. In fact, the ex ante studies dealt with potential consumer’s perceptions before a usage experience occurred, therefore before purchasing a technology, while the ex post studies described the drivers which made a farmer become an end-user of PA technology. Then, an example of consumer research is presented. This was an ex ante research focused on pre-prototype technology for fruit production. This kind of research could give precious information about consumer acceptance before reaching an advanced development phase of the technology, and so to have the possibility to change something with the least financial impact. The final step was to develop the pre-prototype technology that was the subject of the consumer acceptance research and test its technical characteristics.