Efficient Simulation of Biological Neural Networks on Massively Parallel Supercomputers with Hypercube Architecture

We present a neural network simulation which we implemented on the massively parallel Connection Machine 2. In contrast to previous work, this simulator is based on biologically realistic neurons with nontrivial single-cell dynamics, high connectivity with a structure modelled in agreement with biological data, and preservation of the temporal dynamics of spike interactions. We simulate neural networks of 16,384 neurons coupled by about 1000 synapses per neuron, and estimate the performance for much larger systems. Communication between neurons is identified as the computationally most demanding task and we present a novel method to overcome this bottleneck. The simulator has already been used to study the primary visual system of the cat

Research summary, January 1989 - June 1990

The Research Institute for Advanced Computer Science (RIACS) was established at NASA ARC in June of 1983. RIACS is privately operated by the Universities Space Research Association (USRA), a consortium of 62 universities with graduate programs in the aerospace sciences, under a Cooperative Agreement with NASA. RIACS serves as the representative of the USRA universities at ARC. This document reports our activities and accomplishments for the period 1 Jan. 1989 - 30 Jun. 1990. The following topics are covered: learning systems, networked systems, and parallel systems

Report from the MPP Working Group to the NASA Associate Administrator for Space Science and Applications

NASA's Office of Space Science and Applications (OSSA) gave a select group of scientists the opportunity to test and implement their computational algorithms on the Massively Parallel Processor (MPP) located at Goddard Space Flight Center, beginning in late 1985. One year later, the Working Group presented its report, which addressed the following: algorithms, programming languages, architecture, programming environments, the way theory relates, and performance measured. The findings point to a number of demonstrated computational techniques for which the MPP architecture is ideally suited. For example, besides executing much faster on the MPP than on conventional computers, systolic VLSI simulation (where distances are short), lattice simulation, neural network simulation, and image problems were found to be easier to program on the MPP's architecture than on a CYBER 205 or even a VAX. The report also makes technical recommendations covering all aspects of MPP use, and recommendations concerning the future of the MPP and machines based on similar architectures, expansion of the Working Group, and study of the role of future parallel processors for space station, EOS, and the Great Observatories era

Parallel Processing for Supercomputing Speeds .

The various approaches to improving the speeds of computers by exploiting parallelism is briefly described. The architecture of PACE which is a loosely coupled, message-passing MIMD machine developed by ANURAG is described. PACE is an open architecture which is independent of the specific hardware used for the computing nodes. Several versions of PACE have been configured and the performance figures for some applications are presented

Center for Space Microelectronics Technology 1988-1989 technical report

The 1988 to 1989 Technical Report of the JPL Center for Space Microelectronics Technology summarizes the technical accomplishments, publications, presentations, and patents of the center. Listed are 321 publications, 282 presentations, and 140 new technology reports and patents

Center for Space Microelectronics Technology

The 1990 technical report of the Jet Propulsion Laboratory Center for Space Microelectronics Technology summarizes the technical accomplishments, publications, presentations, and patents of the center during 1990. The report lists 130 publications, 226 presentations, and 87 new technology reports and patents

Center for Space Microelectronics Technology. 1993 Technical Report

The 1993 Technical Report of the Jet Propulsion Laboratory Center for Space Microelectronics Technology summarizes the technical accomplishments, publications, presentations, and patents of the Center during the past year. The report lists 170 publications, 193 presentations, and 84 New Technology Reports and patents. The 1993 Technical Report of the Jet Propulsion Laboratory Center for Space Microelectronics Technology summarizes the technical accomplishments, publications, presentations, and patents of the Center during the past year. The report lists 170 publications, 193 presentations, and 84 New Technology Reports and patents

Technology Directions for the 21st Century, volume 1

For several decades, semiconductor device density and performance have been doubling about every 18 months (Moore's Law). With present photolithography techniques, this rate can continue for only about another 10 years. Continued improvement will need to rely on newer technologies. Transition from the current micron range for transistor size to the nanometer range will permit Moore's Law to operate well beyond 10 years. The technologies that will enable this extension include: single-electron transistors; quantum well devices; spin transistors; and nanotechnology and molecular engineering. Continuation of Moore's Law will rely on huge capital investments for manufacture as well as on new technologies. Much will depend on the fortunes of Intel, the premier chip manufacturer, which, in turn, depend on the development of mass-market applications and volume sales for chips of higher and higher density. The technology drivers are seen by different forecasters to include video/multimedia applications, digital signal processing, and business automation. Moore's Law will affect NASA in the areas of communications and space technology by reducing size and power requirements for data processing and data fusion functions to be performed onboard spacecraft. In addition, NASA will have the opportunity to be a pioneering contributor to nanotechnology research without incurring huge expenses

Predictive Scale-Bridging Simulations through Active Learning

Throughout computational science, there is a growing need to utilize the continual improvements in raw computational horsepower to achieve greater physical fidelity through scale-bridging over brute-force increases in the number of mesh elements. For instance, quantitative predictions of transport in nanoporous media, critical to hydrocarbon extraction from tight shale formations, are impossible without accounting for molecular-level interactions. Similarly, inertial confinement fusion simulations rely on numerical diffusion to simulate molecular effects such as non-local transport and mixing without truly accounting for molecular interactions. With these two disparate applications in mind, we develop a novel capability which uses an active learning approach to optimize the use of local fine-scale simulations for informing coarse-scale hydrodynamics. Our approach addresses three challenges: forecasting continuum coarse-scale trajectory to speculatively execute new fine-scale molecular dynamics calculations, dynamically updating coarse-scale from fine-scale calculations, and quantifying uncertainty in neural network models