SoC Self Test Based on a Test-Processor

Author(s):  
Tobial Koal ◽  
Rene Kothe ◽  
Heinrich Theodor Vierhaus

Testing complex systems on a chip (SoCs) with up to billions of transistors has been a challenge to IC test technology for more than a decade. Most of the research work in IC test technology has focused on problems of production testing, while the problem of self test in the field of application has found much less attention. With SoCs being used also in long-living systems for safety critical applications, such enhanced self test capabilities become essential for the dependability of the host system. For example, automotive electronic systems must be capable of performing a fast and effective start-up self test. For future self-repairing systems, fault diagnosis will become necessary, since it is the base for dedicated system re-configuration. One way to solve this problem is a hierarchical self-test scheme for embedded SoCs, based on hardware and software. The core of the test architecture then is a test processor device, which is optimised to organize and control test functions efficiently and at minimum cost. This device must be highly reliable by itself. The chapter introduces the basic concept of hierarchical HW / SW based self test, the test processor concept and architecture, and its role in a hierarchical self test scheme for SoCs.

2020 ◽  
Vol 2020 (3) ◽  
pp. 60408-1-60408-10
Author(s):  
Kenly Maldonado ◽  
Steve Simske

The principal objective of this research is to create a system that is quickly deployable, scalable, adaptable, and intelligent and provides cost-effective surveillance, both locally and globally. The intelligent surveillance system should be capable of rapid implementation to track (monitor) sensitive materials, i.e., radioactive or weapons stockpiles and person(s) within rooms, buildings, and/or areas in order to predict potential incidents proactively (versus reactively) through intelligence, locally and globally. The system will incorporate a combination of electronic systems that include commercial and modifiable off-the-shelf microcomputers to create a microcomputer cluster which acts as a mini supercomputer which leverages real-time data feed if a potential threat is present. Through programming, software, and intelligence (artificial intelligence, machine learning, and neural networks), the system should be capable of monitoring, tracking, and warning (communicating) the system observer operations (command and control) within a few minutes when sensitive materials are at potential risk for loss. The potential customer is government agencies looking to control sensitive materials and/or items in developing world markets intelligently, economically, and quickly.


Author(s):  
Jack Parkin

Newly emerging cryptocurrencies and blockchain technology present a challenging research problem in the field of digital politics and economics. Bitcoin—the first widely implemented cryptocurrency and blockchain architecture—seemingly separates itself from the existing territorial boundedness of nation-state money via a process of algorithmic decentralisation. Proponents declare that the utilisation of cryptography to advance financial transactions will disrupt the modern centralised structures by which capitalist economies are currently organised: corporations, governments, commercial banks, and central banks. Allegedly, software can create a more stable and democratic global economy; a world free from hierarchy and control. In Money Code Space, Jack Parkin debunks these utopian claims by approaching distributed ledger technologies as a spatial and social problem where power forms unevenly across their networks. First-hand accounts of online communities, open-source software governance, infrastructural hardware operations, and Silicon Valley start-up culture are used to ground understandings of cryptocurrencies in the “real world.” Consequently, Parkin demonstrates how Bitcoin and other blockchains are produced across a multitude of tessellated spaces from which certain stakeholders exercise considerable amounts of power over their networks. While money, code, and space are certainly transformed by distributed ledgers, algorithmic decentralisation is rendered inherently paradoxical because it is predicated upon centralised actors, practices, and forces.


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