Associative massively parallel computers

Article Abstract:

Massively Parallel Computers (MPCs) are being used extensively to supply powerful computing environments for a number of computationally intensive applications that need up to Tera (1E12) operations per second (TOPS) performance levels. Associative Processing (AP) architectures are being used in second-generation MPCs because APs provide considerable flexibility for applications and maintain high efficiency. Associative String Processor (ASP), a form of AP, is particularly suitable for second-generation MPCs because it was developed as a Silicon-efficient parallel architecture.

Technological forecasting, Industrial research, Architecture, Research and Development, Future of Computing, Computer Design, Associative Memory, Massive Parallelism

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Backpropagation through time: what it does and how to do it

Article Abstract:

Backpropagation is a method for calculating a single quantity's derivatives with respect to a set of input values. Backpropagation through time finds derivatives for dynamic systems. Basic backpropagation is used to teach neural networks by adjusting weights to produce smaller output errors. Backpropagation through time allows networks to account for results from previous determinations. Backpropagation through time can be used in areas such as pattern recognition and systems identification.

Pattern recognition (Computers), Neural networks, Algorithms, Algorithm, Network architectures, Network Architecture, Pattern Recognition, Scientific Research, Methods, Neural Network, Equation Analysis, Partial Differential Equations, Pseudocode

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