admission. This proportion could already be greater in some parts of the country and may increase if referrals of cases of self-poisoning increase faster than the facilities for their assessment and management. The provision of social work and psychiatric expertise in casualty departments may be one means of preventing unnecessary medical admissions without risk to the patients. Dr Blake's and Dr Bramble's figures do not demonstrate, however, that any advantage would attach to medical teams taking over assessment from psychiatrists except that, by implication, assessments would be completed sooner by staff working on the ward full time. What the figures actually suggest is that if assessment of overdoses were left to house doctors there would be an increase in admissions to psychiatric units (by 19°U), outpatients (by 5O°'), and referrals to social services (by 140o). So for house doctors to assess overdoses would provide no economy for the psychiatric or social services. The study does not tell us what the consequences would have been for the six patients who the psychiatrists would have admitted but to whom the house doctors would have offered outpatient appointments. E J SALTER

Vitamin D deficiency.

International Technology Roadmap for Semiconductors 2003の要求清浄度について － シリコンウエハ表面と雰囲気環境に要求される清浄度, 分析方法の現状について －

生活習慣病とgenome-wide association study

Network-on-Chips (NoCs) are becoming integral parts of modern microprocessors as the number of cores and modules integrated on a single chip continues to increase. Research and development of future NoC technology relies on accurate modeling and simulations to evaluate the performance impact and analyze the cost of novel NoC architectures. In this work, we present BookSim, a cycle-accurate simulator for NoCs. The simulator is designed for simulation flexibility and accurate modeling of network components. It features a modular design and offers a large set of configurable network parameters in terms of topology, routing algorithm, flow control, and router microarchitecture, including buffer management and allocation schemes. BookSim furthermore emphasizes detailed implementations of network components that accurately model the behavior of actual hardware. We have validated the accuracy of the simulator against RTL implementations of NoC routers.

https://crd.lbl.gov/assets/booksimispass.pdf

A detailed and flexible cycle-accurate Network-on-Chip simulator

Neuromorphic computing has come to refer to a variety of brain-inspired computers, devices, and models that contrast the pervasive von Neumann computer architecture This biologically inspired approach has created highly connected synthetic neurons and synapses that can be used to model neuroscience theories as well as solve challenging machine learning problems The promise of the technology is to create a brain-like ability to learn and adapt, but the technical challenges are significant, starting with an accurate neuroscience model of how the brain works, to finding materials and engineering breakthroughs to build devices to support these models, to creating a programming framework so the systems can learn, to creating applications with brain-like capabilities In this work, we provide a comprehensive survey of the research and motivations for neuromorphic computing over its history We begin with a 35-year review of the motivations and drivers of neuromorphic computing, then look at the major research areas of the field, which we define as neuro-inspired models, algorithms and learning approaches, hardware and devices, supporting systems, and finally applications We conclude with a broad discussion on the major research topics that need to be addressed in the coming years to see the promise of neuromorphic computing fulfilled The goals of this work are to provide an exhaustive review of the research conducted in neuromorphic computing since the inception of the term, and to motivate further work by illuminating gaps in the field where new research is needed

A Survey of Neuromorphic Computing and Neural Networks in Hardware.

Future many-core processors will require high-performance yet energy-efficient on-chip networks to provide a communication substrate for the increasing number of cores. Recent advances in silicon nanophotonics create new opportunities for on-chip networks. To efficiently exploit the benefits of nanophotonics, we propose Firefly - a hybrid, hierarchical network architecture. Firefly consists of clusters of nodes that are connected using conventional, electrical signaling while the inter-cluster communication is done using nanophotonics - exploiting the benefits of electrical signaling for short, local communication while nanophotonics is used only for global communication to realize an efficient on-chip network. Crossbar architecture is used for inter-cluster communication. However, to avoid global arbitration, the crossbar is partitioned into multiple, logical crossbars and their arbitration is localized. Our evaluations show that Firefly improves the performance by up to 57% compared to an all-electrical concentrated mesh (CMESH) topology on adversarial traffic patterns and up to 54% compared to an all-optical crossbar (OP XBAR) on traffic patterns with locality. If the energy-delay-product is compared, Firefly improves the efficiency of the on-chip network by up to 51% and 38% compared to CMESH and OP XBAR, respectively.

/pdf/firefly-illuminating-future-network-on-chip-with-34qvzibkvg.pdf

Firefly: illuminating future network-on-chip with nanophotonics

On-chip network is becoming critical to the scalability of future many-core architectures. Recently, nanophotonics has been proposed for on-chip networks because of its low latency and high bandwidth. However, nanophotonics has relatively high static power consumption, which can lead to inefficient architectures. In this work, we propose FlexiShare — a nanopho-tonic crossbar architecture that minimizes static power consumption by fully sharing a reduced number of channels across the network. To enable efficient global sharing, we decouple the allocation of the channels and the buffers, and introduce novel photonic token-stream mechanism for channel arbitration and credit distribution The flexibility of FlexiShare introduces additional router complexity and electrical power consumption. However, with the reduced number of optical channels, the overall power consumption is reduced without loss in performance. Our evaluation shows that the proposed token-stream arbitration applied to a conventional crossbar design improves network throughput by 5.5× under permutation traffic. In addition, FlexiShare achieves similar performance as a token-stream arbitrated conventional crossbar using only half the amount of channels under balanced, distributed traffic. With the extracted trace traffic from MineBench and SPLASH-2, FlexiShare can further reduce the amount of channels by up to 87.5%, while still providing better performance — resulting in up to 72% reduction in power consumption compared to the best alternative.

/pdf/flexishare-channel-sharing-for-an-energy-efficient-3qtc5feyth.pdf

FlexiShare: Channel sharing for an energy-efficient nanophotonic crossbar

Inspired by the double helix structure of DNA, a simple enantioselective system based on chitosan (CS) was employed for electrochemical enantiorecognition of tryptophan (Trp) isomers The recognition mechanism was proposed from the supramolecular point of view, which was further verified by the recognition of Trp isomers with sulfonated CS (SCS) The SCS-based chiral system presented the ability of indicating the percentage of d-Trp in racemic mixture, extending future applications of the electrochemical chiral system based on natural polysaccharides

DNA-Inspired Electrochemical Recognition of Tryptophan Isomers by Electrodeposited Chitosan and Sulfonated Chitosan

Highly fluorescent and morphology-controllable graphene quantum dots-chitosan hybrid xerogels for in vivo imaging and pH-sensitive drug carrier.

Sharing on-chip network resources efficiently is critical in the design of a cost-efficient network on-chip (NoC). Concentration has been proposed for on-chip networks but the trade-off in concentration implementation and performance has not been well understood. In this paper, we describe cost-efficient implementations of concentration and show how external concentration provides a significant reduction in complexity (47% and 36% reduction in area and energy, respectively) compared to previous assumed integrated (high-radix) concentration while degrading overall performance by only 10%. Hybrid implementations of concentration is also presented which provide additional tradeoff between complexity and performance. To further reduce the cost of NoC, we describe how channel slicing can be used together with concentration. We propose virtual concentration which further reduces the complexity - saving area and energy by 69% and 32% compared to baseline mesh and 88% and 35% over baseline concentrated mesh.

/pdf/exploring-concentration-and-channel-slicing-in-on-chip-1ex2bxt6f4.pdf

Yan Pan

Papers

Firefly: illuminating future network-on-chip with nanophotonics

FlexiShare: Channel sharing for an energy-efficient nanophotonic crossbar

DNA-Inspired Electrochemical Recognition of Tryptophan Isomers by Electrodeposited Chitosan and Sulfonated Chitosan

Highly fluorescent and morphology-controllable graphene quantum dots-chitosan hybrid xerogels for in vivo imaging and pH-sensitive drug carrier.

Exploring concentration and channel slicing in on-chip network router