In this paper, we describe the design of Neurogrid, a neuromorphic system for simulating large-scale neural models in real time. Neuromorphic systems realize the function of biological neural systems by emulating their structure. Designers of such systems face three major design choices: 1) whether to emulate the four neural elements-axonal arbor, synapse, dendritic tree, and soma-with dedicated or shared electronic circuits; 2) whether to implement these electronic circuits in an analog or digital manner; and 3) whether to interconnect arrays of these silicon neurons with a mesh or a tree network. The choices we made were: 1) we emulated all neural elements except the soma with shared electronic circuits; this choice maximized the number of synaptic connections; 2) we realized all electronic circuits except those for axonal arbors in an analog manner; this choice maximized energy efficiency; and 3) we interconnected neural arrays in a tree network; this choice maximized throughput. These three choices made it possible to simulate a million neurons with billions of synaptic connections in real time-for the first time-using 16 Neurocores integrated on a board that consumes three watts.

/pdf/neurogrid-a-mixed-analog-digital-multichip-system-for-large-494ipl0j1g.pdf

Neurogrid: A Mixed-Analog-Digital Multichip System for Large-Scale Neural Simulations

This book introduces a new approach to the design and implementation of software systems which will help users of large scale parallel systems coordinate many concurrent activities toward a single goal It assesses the strengths an weaknesses of this approach with existing alternativesCole's system proposes a selection of independent algorithmic skeletons, each of which describes the structure of a particular style of algorithm The user must describe a solution to a problem as an instance of the appropriate skeleton The implementation task is simplified by the fact that each skeleton may be considered independently, in contrast to the monolithic programming interfaces of existing systems at a similar level of abstractionThe book describes four skeletons based on the notions of fixed degree divide and conquer, task queues, iterative combination, and clustering Each is introduced in terms of the abstraction it presents to the user Implementation on a square grid of autonomous processor memory pairs is considered and examples of problems which could be solved in terms of the skeleton are presentedMurray I Cole is a Lecturer in the Computing Science Department of the University of Glasgow "Algorithmic Skeletons" is included in the series Research Monographs in Parallel and Distributed Computing, Copublished with Pitman Publishing,

/pdf/algorithmic-skeletons-structured-management-of-parallel-2u29jsqtry.pdf

Algorithmic skeletons : structured management of parallel computation

In this paper, we describe the design of Neurogrid, a neuromorphic system for simulating large-scale neural models in real time. Neuromorphic systems realize the function of biological neural systems by emulating their structure. Designers of such systems face three major design choices: 1) whether to emulate the four neural elementsVaxonal arbor, synapse, dendritic tree, and somaVwith dedicated or shared electronic circuits; 2) whether to implement these electronic circuits in an analog or digital manner; and 3) whether to interconnect arrays of these silicon neurons with a mesh or a tree network. The choices we made were: 1) we emulated all neural elements except the soma with shared electronic circuits; this choice maximized the number of synaptic connections; 2) we realizedallelectroniccircuitsexcept those foraxonal arbors in an analog manner; this choice maximized energy efficiency; and

/pdf/neurogrid-a-mixed-analog-digital-multichip-system-for-large-lloj7iozmh.pdf

Neurogrid: A Mixed-Analog-Digital Multichip System for Large-Scale Neural Simulations This paper describes the design of the first hardware system to provide computational neuroscientists with the capability of performing biological real-time simulations of a million neurons and their synaptic connections.

Polylactide (PLA), a biodegradable aliphatic polyester, has been studied extensively for its wide applications in various fields from food packaging to interior materials for automobiles. One of PLA's advantages is that the raw material, lactic acid can be derived from renewable resources, which makes PLA very attractive for the packaging and considered as green packaging. Although, the cost of PLA is relatively higher compared to petroleum based packaging materials and it is predicted that the price will go down after commercial success of the process. This paper presents a review on polylactide with focus on its chemistry, synthesis, properties, and applications. Plasticization effect on PLA, sorption isotherm and mechanical properties of PLA based packaging materials have been discussed. PLA/layered organo nanocomposites exhibit significant improvement in mechanical, thermal, optical, and physicochemical properties over pure PLA. This review includes brief overview of PLA based nanocomposite, their mec...

/pdf/polylactides-chemistry-properties-and-green-packaging-23wnjezmvg.pdf

Polylactides—Chemistry, Properties and Green Packaging Technology: A Review

Decision trees and diagrams (also known as sequential evaluation procedures) have widespread applications in databases, dec~smn table programming, concrete complexity theory, switching theory, pattern recognmon, and taxonomy--in short, wherever discrete functions must be evaluated sequentially. In this tutorial survey a common framework of defimtmns and notation is established, the contributions from the main fields of apphcatmn are reviewed, recent results and extensions are presented, and areas of ongoing and future research are discussed.

Decision Trees and Diagrams

The binary tree is a natural way to organize complex computations by a computer. For problems that can be naturally divided into a tree structure, a great deal of parallelism may be employed. In this paper we examine several aspects of the binary tree structure as it relates to both multiprocessor systems and to VISI circuit design. First, we present an algorithm for mapping an arbitrary binary tree onto the plane. An analysis shows the density of this mapping. Second, we consider the problem of routing messages within a binary tree under the assumption that certain nodes may be faulty. Finally, we analyze the binary tree's capacity to transfer information between nodes and we compare it to the capacity of the linear array and the grid.

The Binary Tree as an Interconnection Network: Applications to Multiprocessor Systems and VLSI

The well known divide-and-conquer paradigm has proved to be useful for deriving efficient algorithms for many problems. Several researchers have pointed out its usefulness for parallel processing; however, the problem of analyzing such parallel algorithms in a realistic setting has been largely overlooked. In this paper a realistic model for divide-and-conquer based algorithms is postulated; the efficiency of some algorithms is then analyzed, taking into account all relevant parameters of the model (time, data movement and number of processors.)

Divide-and-Conquer for Parallel Processing

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The Binary Tree as an Interconnection Network: Applications to Multiprocessor Systems and VLSI

Divide-and-Conquer for Parallel Processing