Practical applications of multi-agent systems in electric power systems

The transformation of energy networks from passive to active systems requires the embedding of intelligence within the network. One suitable approach to integrating distributed intelligent systems is multi-agent systems technology, where components of functionality run as autonomous agents capable of interaction through messaging. This provides loose coupling between components that can benefit the complex systems envisioned for the smart grid. This paper reviews the key milestones of demonstrated agent systems in the power industry and considers which aspects of agent design must still be addressed for widespread application of agent technology to occur

Room Temperature InP DFB Laser Array Directly Grown on (001) Silicon

Fully exploiting the silicon photonics platform requires a fundamentally new approach to realize high-performance laser sources that can be integrated directly using wafer-scale fabrication methods. Direct band gap III-V semiconductors allow efficient light generation but the large mismatch in lattice constant, thermal expansion and crystal polarity makes their epitaxial growth directly on silicon extremely complex. Here, using a selective area growth technique in confined regions, we surpass this fundamental limit and demonstrate an optically pumped InP-based distributed feedback (DFB) laser array grown on (001)-Silicon operating at room temperature and suitable for wavelength-division-multiplexing applications. The novel epitaxial technology suppresses threading dislocations and anti-phase boundaries to a less than 20nm thick layer not affecting the device performance. Using an in-plane laser cavity defined by standard top-down lithographic patterning together with a high yield and high uniformity provides scalability and a straightforward path towards cost-effective co-integration with photonic circuits and III-V FINFET logic

Analysis and Mitigation of Soft-Errors on High Performance Embedded GPUs

Multiprocessor system-on-chip such as embedded GPUs are becoming very popular in safety-critical applications, such as autonomous and semi-autonomous vehicles. However, these devices can suffer from the effects of soft-errors, such as those produced by radiation effects. These effects are able to generate unpredictable misbehaviors. Fault tolerance oriented to multi-threaded software introduces severe performance degradations due to the redundancy, voting and correction threads operations. In this paper, we propose a new fault injection environment for NVIDIA GPGPU devices and a fault tolerance approach based on error detection and correction threads executed during data transfer operations on embedded GPUs. The fault injection environment is capable of automatically injecting faults into the instructions at SASS level by instrumenting the CUDA binary executable file. The mitigation approach is based on concurrent error detection threads running simultaneously with the memory stream device to host data transfer operations. With several benchmark applications, we evaluate the impact of softerrors classifying Silent Data Corruption, Detection, Unrecoverable Error and Hang. Finally, the proposed mitigation approach has been validated by soft-error fault injection campaigns on an NVIDIA Pascal Architecture GPU controlled by Quad-Core A57 ARM processor (JETSON TX2) demonstrating an advantage of more than 37% with respect to state of the art solution

Product assurance technology for custom LSI/VLSI electronics

The technology for obtaining custom integrated circuits from CMOS-bulk silicon foundries using a universal set of layout rules is presented. The technical efforts were guided by the requirement to develop a 3 micron CMOS test chip for the Combined Release and Radiation Effects Satellite (CRRES). This chip contains both analog and digital circuits. The development employed all the elements required to obtain custom circuits from silicon foundries, including circuit design, foundry interfacing, circuit test, and circuit qualification