Search NASA⌕ Search

SEARCH · Search NASA

Results for “John von Neumann”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

18 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

ASCR@40: Highlights and Impacts of ASCR’s Programs

A report compiled by the ASCAC Subcommittee on the 40-year history of ASCR for the U.S. Department of Energy’s Office of Advanced Scientific Computing Research. The Office of Advanced Scientific Computing Research (ASCR) sits within the Office of Science in the Department of Energy (DOE). Per their web pages, “the mission of the ASCR program is to discover, develop, and deploy computational and networking capabilities to analyze, model, simulate, and predict complex phenomena important to the DOE.” This succinct statement encompasses a wide range of responsibilities for computing and networking facilities; for procuring, deploying, and operating high performance computing, networking, and storage resources; for basic research in mathematics and computer science; for developing and sustaining a large body of software; and for partnering with organizations across the Office of Science and beyond. While its mission statement may seem very contemporary, the roots of ASCR are quite deep—long predating the creation of DOE. Applied mathematics and advanced computing were both elements of the Theoretical Division of the Manhattan Project. In the early 1950s, the Manhattan Project scientist and mathematician John von Neumann, then a commissioner for the AEC (Atomic Energy Commission), advocated for the creation of a Mathematics program to support the continued development and applications of digital computing. Los Alamos National Laboratory (LANL) scientist John Pasta created such a program to fund researchers at universities and AEC laboratories. Under several organizational name changes, this program has persisted ever since, and would eventually grow to become ASCR.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Bethe, Oppenheimer, Teller and the Fermi Award: Norris Bradbury Speaks

In 1956 the Enrico Fermi Presidential Award was established to recognize scientists, engineers, and science policymakers who gave unstintingly over their careers to advance energy science and technology. The first recipient was John von Neumann. .1 Among those scientists who were thought eligible for the award were Hans Bethe, J. Robert Oppenheimer, and Edward Teller. In 1959 Norris Bradbury was asked to comment on the relative merits of each these three men, whom he knew well from their affiliation with Los Alamos. Below is a reproduction of the letter Bradbury sent to Dr. Warren C. Johnson of the AEC’s General Advisory Committee(GAC) containing his evaluation of each man. The letter might surprise those not accustomed to Bradbury’s modus operandi of providing very detailed and forthright answers to the AEC. The letter, itself, was found in cache of old microfilm. Whether because of the age of the microfilm or the quality of the filming process, portions of the letter are not legible. Where empty brackets appear, the word or words could not be read or deduced. Words appearing in brackets are guesses that appear, from the image, to be what was written. These guesses, of course, are just that – guesses.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2019

On the Development of Godunov Methods and Their Application to Gasdynamics

We are interested in developing the most accurate numeral models to simulate Gadynamics of explosions. But we must first recognize that there is no unique way to discretize the partial differential equations (PDEs) of gas dynamics, and also, there is no unique method to integrate the discretized forms of these equations. This has spawned a variety of numerical methods (religions*) that attempt to solve this conundrum, for example: Artificial Viscosity method created by the American mathematician John von Neumann, Flux-Corrected-Transport (FCT) method invented by Dr. Jay Boris, founder of the Laboratory for Computational Physics (LCP) at NRL, WENO method developed by Professor Stan Osher of UCLA and Professor Bjorn Enquist of U. Texas, and Godunov method by Academician Sergei Konstantinovich Godunov, Professor of the Sobolev Institute of Mathematics, RAS, in Novosibirsk to name just a few.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Who Invented the Christy Gadget

The Christy Gadget, named after its principal inventor, is the informal name for the device tested at Trinity on July 16th, 1945. In late 1944, Robert Christy proposed a novel invention that altered the design of the plutonium pit in Fat Man. While scientists originally intended to use a hollow sphere of plutonium, there was a substantial risk given a number of asymmetries that resulted from implosion. Christy proposed changing the design of the plutonium core to a solid sphere of plutonium with a modulated neutron source. The new model was adopted and used in the early implosion bombs. While there is little debate about the important role that Christy played in demonstrating its feasibility as a safe design, there is a debate as to who initially proposed the idea of the Christy Device. My project this summer outlines and resolves this dispute. While Christ does deserve the majority of the credit for the invention and design, I also acknowledge the important role Rudolf Peierls and John von Neumann played in its development.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

The History of Monte Carlo and MCNP at Los Alamos [Slides]

The Monte Carlo method for radiation particle transport has its origins at LANL dating back to the 1940’s. The creators of these methods were Drs. Stanislaw Ulam, John von Neumann, Robert Richtmyer, and Nicholas Metropolis. Monte Carlo methods for particle transport have been driving computational developments since the beginning of modern computers; this continues today. In the 1950’s and 1960’s, these new methods were organized into a series of special-purpose Monte Carlo codes, including MCS, MCN, MCP, and MCG. These codes were able to transport neutrons and photons for specialized LANL applications. In 1977, these separate codes were combined to create the LANL Monte Carlo N-Particle (MCNP) radiation particle transport code. In 1983, MCNP3 was released for public distribution to the Radiation Safety Information Computational Center (RSICC). MCNP6.3 will be released late in 2021. Each year, LANL has ~100 MCNP new users and RSICC ~1250 new licenses distributed. This talk will review the Los Alamos history of the development of the modern Monte Carlo method and MCNP.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Learning Operators for Structure-Informed Surrogate Models

This report summarizes the work performed under the author's two-year John von Neumann LDRD project, which involves the non-intrusive surrogate modeling of dynamical systems with remarkable structural properties. After a brief introduction to the topic, technical accomplishments and project metrics are reviewed including peer-reviewed publications, software releases, external presentations and colloquia, as well as organized conference sessions and minisymposia. The report concludes with a summary of ongoing projects and collaborations which utilize the results of this work.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1983

Population Control of Self-Replicating Systems: Option C

From the conception and development of the theory of self-replicating automata by John von Neumann, others have expanded on his theories. In 1980, Georg von Tiesenhausen and Wesley A. Darbro developed a report which is a "first' in presenting the theories in a conceptualized engineering setting. In that report several options involving self-replicating systems are presented. One of the options allows each primary to generate n replicas, one in each sequential time frame after its own generation. Each replica is limited to a maximum of m ancestors. This study involves determining the state vector of the replicas in an efficient manner. The problem is cast in matrix notation, where F = fij is a non-diagonalizable matrix. Any element fij represents the number of elements of type j = (c,d) in time frame k+1 generated from type i = (a,b) in time frame k. It is then shown that the state vector is: bar F(k)=bar F (non-zero) X F sub K = bar F (non-zero) xmx J sub kx m sub-1 where J is a matrix in Jordan form having the same eigenvalues as F. M is a matrix composed of the eigenvectors and the generalized eigenvectors of F.

Mccord, R. L.↗
NASA NTRS1991

Development of ISO connection-oriented/correctionless gateways

The project had two goals, establishment of a gateway between French and U.S. academic networks and studies of issues related to the development of ISO connection-oriented/connectionless (CO/CL) gateways. The first component involved installation of a 56K bps line between Princeton Univ. and INRIA in France. The end-points of these lines were connected by Vitalink link level bridges. The Princeton end was then connected to the NSFNET via the John Von Neumann Supercomputer Center. The French end was connected to Transpac, the French X.25 public data network and to the French IP research internet. U.S. users may communicate with users of the French internet by e-mail and may access computational and data resources in France by use of remote login and file transfer. The connection to Transpac enables U.S. users to access the SIMBAD astronomical database outside of Paris. Access to this database from the U.S. can be via TCP/IP or DECNET (via a DECNET to TCP/IP gateway) protocols utilizing a TCP/IP to X.25 gateway developed and operated by INRIA. The second component of the project involved experiments aimed at understanding the issues involved is ISO CO/CL gateways. An experimental gateway was developed at Wisconsin and a preliminary report was prepared. Because of the need to devote most resources to the first component of the project, work in this area did not go beyond development of a prototype gateway.

Landweber, Lawrence H.↗
DOE OSTI2017

Computer Architecture's Changing Role in Rebooting Computing

In this paper, Windows 95 started the Wintel era, in which Microsoft Windows running on Intel x86 microprocessors dominated the computer industry and changed the world. Retaining the x86 instruction set across many generations let users buy new and more capable microprocessors without having to buy software to work with new architectures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Organismic materials for beyond von Neumann machines

The elementary basis of intelligence in organisms with a central nervous system includes neurons and synapses and their complex interconnections forming neural circuits. In non-neural organisms such as slime mold with gel-like media, viscosity modulation enables adaptation to changing environments. At a larger scale, collective intelligence emerges via social interactions and feedback in animal colonies. Learning and memory are therefore multi-scale features that evolve as a result of constant interactions with the environment. There is growing interest in emulating such features of intelligence in computing machines and autonomous systems. Materials that can respond to their environment in a manner similar to organisms (referred to as "organismic materials") therefore may be of interest as hardware components in artificial intelligence machines. In this brief review, we present a class of semiconductors called correlated oxides as candidates for learning machines. The term "correlated" refers to the fact that electrons in such lattices strongly interact and the ground state is not what is predicted by classical band theory. Such materials can undergo insulator-metal transitions at near ambient conditions under external stimuli such as thermal or electrical fields, strain, and chemical doping. Depending on the mechanism driving the transition, intermediate states can be metastable with different volatilities, and the time scales of phase change can be controlled over many orders of magnitude. The change in electronic properties can be sharp or gradual, leading to digital or analog behavior. These properties enable the realization of artificial neurons and synapses and emulate the associative and non-associative learning characteristics found in various organisms. We examine microscopic properties concerning electronic and structural transitions leading to collective behavior and theoretical treatments of the ground state and dynamical response, showcasing VO 2 as a model system. Next, we briefly review algorithms designed from the plasticity demonstrated by phase changing systems. Finally, we conclude the brief review with suggestions for future research toward realizing non-von Neumann machines.

42 ENGINEERING↗
DOE OSTI2024

Enhanced Estimation of Quantum Properties with Common Randomized Measurements

We present a technique for enhancing the estimation of quantum state properties by incorporating approximate prior knowledge about the quantum state. This consists in performing randomized measurements on a quantum processor and comparing the results with those obtained from a classical computer that stores an approximation of the quantum state. We provide unbiased estimators for expectation values of multicopy observables and present performance guarantees in terms of variance bounds that depend on the prior knowledge accuracy. We demonstrate the effectiveness of our approach through experimental and numerical examples detecting mixed-state entanglement, and estimating polynomial approximations of the von Neumann entropy and state fidelities. Published by the American Physical Society 2024

Physics↗
DOE OSTI2017

Neuromorphic data microscope

In 2016, Lewis Rhodes Labs, (LRL), shipped the first commercially viable Neuromorphic Processing Unit, (NPU), branded as a Neuromorphic Data Microscope (NDM). This product leverages architectural mechanisms derived from the sensory cortex of the human brain to efficiently implement pattern matching. LRL and Sandia National Labs have optimized this product for streaming analytics, and demonstrated a 1,000x power per operation reduction in an FPGA format. When reduced to an ASIC, the efficiency will improve to 1,000,000x. Additionally, the neuromorphic nature of the device gives it powerful computational attributes that are counterintuitive to those schooled in traditional von Neumann architectures. The Neuromorphic Data Microscope is the first of a broad class of brain-inspired, time domain processors that will profoundly alter the functionality and economics of data processing.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Applying Quantum Tomography to Hadronic Interactions

A proper description of inclusive reactions is expressed with density matrices. Quantum tomography reconstructs density matrices from experimental observables. We review recent work that applies quantum tomography to practical experimental data analysis. Almost all field-theoretic formalism and modeling used in a traditional approach is circumvented with great efficiency. Tomographically-determined density matrices can express information about quantum systems which cannot in principle be expressed with distributions defined by classical probability. Topics such as entanglement and von Neumann entropy can be accessed using the same natural language where they are defined. A deep relation exists between separability, as defined in quantum information science, and factorization, as defined in high energy physics. Factorization acquires a non-perturbative definition when expressed in terms of a conditional form of separability. An example illustrates how to go from data for momentum 4-vectors to a density matrix while bypassing almost all the formalism of the Standard Model.

Martens, J. C.↗
DOE OSTI2022

Reimagining Codesign for Advanced Scientific Computing: Report for the ASCR Workshop on Reimagining Codesign

In March 2021, the U.S. Department of Energy’s Advanced Scientific Computing Research program convened the Workshop on Reimagining Codesign. The workshop, also known as ReCoDe, was organized around discussions on eight topic areas: (1) codesign for traditional high-performance computing workloads; (2) codesign of memory/storage systems; (3) codesign of machine learning, neuromorphic, quantum, and other non-von Neumann accelerators; (4) codesign for edge computing and processing at experimental instruments; (5) codesign for security and privacy; (6) hardware design tools and open-source hardware for high-productivity codesign; (7) tools, software stack, and programming languages for high-productivity codesign; and (8) quantitative tools and data collection for modeling and simulation for codesign. The panels identified four Priority Research Directions from these deliberations: (1) breakthrough computing capabilities with targeted heterogeneity and rapid design; (2) software and applications that embrace radical architecture diversity; (3) engineered security and integrity, from transistors to applications; and (4) design with data-rich processes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Transients following the loss of detonation confinement

We present a theory for the evolution of a one-dimensional, steady-state detonation reaction zone to a two-dimensional reaction zone, when the explosive experiences a sudden loss of side-on confinement as a boundary of the explosive is impulsively withdrawn. Our focus is on condensed-phase explosives, which we describe as having a constant adiabatic gamma equation of state and an irreversible, state-independent reaction rate. We consider two detonation models: (i) the instantaneous reaction heat release Chapman–Jouguet (CJ)-limit and (ii) the spatially resolved reaction heat-release Zel’dovich–von Neumann–Döring (ZND) model, in the limit where only a small fraction of the energy release is resolved (the SRHR-limit). Two competing rarefaction waves are generated by this loss of confinement: (i) a smooth wave coming off the full length of the withdrawn boundary and (ii) a singular fan spreading out from the point where the detonation shock and the withdrawn boundary meet. For the CJ-limit, in all cases the singular rarefaction fan eventually dominates the competition to control the steady-state behaviour. For the SRHR-limit, the spatially resolved heat release moderates this competition. When the withdrawal speed is fast, the rarefaction fan dominates; when the withdrawal speed is slower, the smooth rarefaction eventually dominates, although the flow features a fan at early times. By examining the mathematical properties of the steady two-dimensional fan-based solution, we set down a mechanism for this transition in behaviours.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

(Bi 0.2 Sb 0.8 ) 2 Te 3 based dynamic synapses with programmable spatio-temporal dynamics

Neuromorphic computing has recently emerged as a promising paradigm to overcome the von-Neumann bottleneck and enable orders of magnitude improvement in bandwidth and energy efficiency. However, existing complementary metal-oxide-semiconductor (CMOS) digital devices, the building block of our computing system, are fundamentally different from the analog synapses, the building block of the biological neural network—rendering the hardware implementation of the artificial neural networks (ANNs) not scalable in terms of area and power, with existing CMOS devices. In addition, the spatiotemporal dynamic, a crucial component for cognitive functions in the neural network, has been difficult to replicate with CMOS devices. Here, we present the first topological insulator (TI) based electrochemical synapse with programmable spatiotemporal dynamics, where long-term and short-term plasticity in the TI synapse are achieved through the charge transfer doping and ionic gating effects, respectively. We also demonstrate basic neuronal functions such as potentiation/depression and paired-pulse facilitation with high precision (>500 states per device), as well as a linear and symmetric weight update. We envision that the dynamic TI synapse, which shows promising scaling potential in terms of energy and speed, can lead to the hardware acceleration of truly neurorealistic ANNs with superior cognitive capabilities and excellent energy efficiency.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Artificial Intelligence-Enhanced, Multi-Level, Modular System Design

As Moore’s Law and Dennard Scaling come to an end, it is becoming increasingly important to develop non-von Neumann computing architectures that can perform low-power computing in the domains of scientific computing, artificial intelligence, embedded systems, and edge computing. Next-generation computing technologies, such as neuromorphic computing and quantum computing, have the potential to revolutionize computing. However, in order to make progress in these fields, it is necessary to fundamentally change the current computing paradigm by codesigning systems across all system level, from materials to software. Because skilled labor is limited in the field of next-generation computing, we are developing artificial intelligence-enhanced tools to automate the codesign and co-discovery of next-generation computers. Here, we develop a method called Modular and Multi-level MAchine Learning (MAMMAL) which is able to perform analog codesign and co-discovery across multiple system levels, spanning devices to circuits. We prototype MAMMAL by using it to design simple passive analog low-pass filters. We also explore methods to incorporate uncertainty quantification into MAMMAL and to accelerate MAMMAL by using emerging technologies, such as crossbar arrays. Ultimately, we believe that MAMMAL will enable rapid progress in developing next-generation computers by automating the codesign and co-discovery of electronic systems.

97 MATHEMATICS AND COMPUTING↗