Photonic integrated reconfigurable linear processors as neural network accelerators

Reconfigurable linear optical processors can be used to perform linear transformations and are instrumental in effectively computing matrix–vector multiplications required in each neural network layer. In this paper, we characterize and compare two thermally tuned photonic integrated processors realized in silicon-on-insulator and silicon nitride platforms suited for extracting feature maps in convolutional neural networks. The reduction in bit resolution when crossing the processor is mainly due to optical losses, in the range 2.3–3.3 for the silicon-on-insulator chip and in the range 1.3–2.4 for the silicon nitride chip. However, the lower extinction ratio of Mach–Zehnder elements in the latter platform limits their expressivity (i.e., the capacity to implement any transformation) to 75%, compared to 97% of the former. Finally, the silicon-on-insulator processor outperforms the silicon nitride one in terms of footprint and energy efficiency

Bidirectional Transmission in an Optical Network on Chip With Bus and Ring Topologies

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Albumin and mammalian cell culture: implications for biotechnology applications

Albumin has a long historical involvement in design of media for the successful culture of mammalian cells, in both the research and commercial fields. The potential application of albumins, bovine or human serum albumin, for cell culture is a by-product of the physico-chemical, biochemical and cell-specific properties of the molecule. In this review an analysis of these features of albumin leads to a consideration of the extracellular and intracellular actions of the molecule, and importantly the role of its interactions with numerous ligands or bioactive factors that influence the growth of cells in culture: these include hormones, growth factors, lipids, amino acids, metal ions, reactive oxygen and nitrogen species to name a few. The interaction of albumin with the cell in relation to these co-factors has a potential impact on metabolic and biosynthetic activity, cell proliferation and survival. Application of this knowledge to improve the performance in manufacturing biotechnology and in the emerging uses of cell culture for tissue engineering and stem cell derived therapies is an important prospect

Optics in Data Center: Improving Scalability and Energy Efficiency

Interconnection networks within modern data centers suffer from bandwidth and scalability limitations, and important power consumption. Optical switching solutions can help to overcome such issues when properly designed and optimized. This paper discusses three areas of improvement beyond state of the art: i) the use of more energy-efficient optical devices to realize high-capacity and energy-efficient optical space switches; ii) the enhancement of their scalability by combining space switching with time switching into a space-time interconnection network architecture (STIA); iii) the planning of an energy-efficient STIA-based network meeting data center bisection bandwidth requirements. Performance assessment shows that i) by combining different switching devices in the same space switch, up to 90% of the power can be saved with respect to conventional SOA-based space switches; ii) STIA allows scalability to increase by a factor of 8, thanks to the combined use of space and time switching domains, while limiting the energy per bit; iii) STIA allows the realization of data center topologies, such as folded Clos and flattened butterfly, whose optimized design can lead to power saving up to 50% with respect to an energy unaware design