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An N modular redundancy method, system, and computer program product include a computer-implemented N modular redundancy method for neural networks, the method including selectively replicating the neural network by employing one of checker neural networks and selective N modular redundancy (N-MR) applied only to critical computations.
To date, the estimated radiation-absorbed dose to organs and tissues in patients undergoing diagnostic examinations in nuclear medicine is derived via calculations based on models of the human body and the biokinetic behaviour of the radiopharmaceutical. An internal dosimetry computer program, IDAC-Dose2.1, was developed based on the International Commission on Radiological Protection (ICRP)-specific absorbed fractions and computational framework of internal dose assessment given for reference adults in ICRP Publication 133. The program uses the radionuclide decay database of ICRP Publication 107 and considers 83 different source regions irradiating 47 target tissues, defining the effective dose as presented in ICRP Publications 60 and 103. The computer program was validated against another ICRP dosimetry program, Dose and Risk Calculation (DCAL), that employs the same computational framework in evaluation of occupational and environmental intakes of radionuclides. IDAC-Dose2.1 has a sub-module for absorbed dose calculations in spherical structures of different volumes and composition; this sub-module is intended for absorbed dose estimates in radiopharmaceutical therapy. For nine specific alpha emitters, the absorbed dose contribution from their decay products is also included in the committed absorbed dose calculations. The absorbed doses and effective dose of 131 I-iodide determined by IDAC-Dose2.1 were validated against the dosimetry program DCAL, showing identical results. IDAC-Dose2.1 was used to calculate absorbed doses for intravenously administered 18 F-FDG and orally administered 99m Tc-pertechnetate and 131 I-iodide, three frequently used radiopharmaceuticals. Using the tissue weighting factors from ICRP Publication 103, the effective dose per administered activity was estimated to be 0.016 mSv/MBq for 18 F-FDG, 0.014 mSv/MBq for 99m Tc-pertechnetate, and 16 mSv/MBq for 131 I-iodide. The internal dosimetry program IDAC-Dose2.1 was developed and applied to three radiopharmaceuticals for validation against DCAL and to generate improved absorbed dose estimations for diagnostic nuclear medicine using specific absorbed fraction values of the ICRP computational voxel phantoms. The sub-module for absorbed dose calculations in spherical structures 1 mm to 9 cm in diameter and different tissue composition was included to broaden the clinical usefulness of the program. The IDAC-Dose2.1 program is free software for research and available for download at http://www.idac-dose.org.
Here, this article offers perspective on quantum computing programming languages, as well as their emerging runtimes and algorithmic modalities. With the scientific high-performance computing (HPC) community as a target audience, we describe the current state of the art in the field, and outline programming paradigms for scientific workflows. One take-home message is that there is significant work required to first refine the notion of the quantum processing unit in order to integrate in the HPC environments. Programming for today’s quantum computers is making significant strides toward modern HPC-compatible workflows, but key challenges still face the field.
The SKINATH point kinetics program, whose name comes from: A Computer Program for Solving the Reactor Point Kinetics Equations with Simple Thermal Hydraulic-Feedback, had its origins at ORNL. The authors were interested in investigating low-level criticality events such as might occur in a waste repository of 55 gallon drums. We assume a relatively realistic thermal feedback for fissionable material in a container (called a reactor here), either critical or subcritical, with the potential to undergo a further excursion. The system is a homogeneous fissile fluid (mostly water), increasing in temperature as it absorbs all heat from the excursion. An ideal gas eternally cools the reactor at constant temperature T{sub c}. The SKINATH numerical concept in 1984 was to use an off-the-shelf Livermore ODE solver LSODE to solve the kinetic equations, much as one does today with MATLAB{sup TM}. Here, we develop a novel solver that uses the simplest of numerical methods including convergence acceleration. This work represents the initiation of a Multiphysics benchmark effort at INL. (authors)
In parallel with Sandia National Laboratories having two major locations (NM and CA), along with a number of smaller facilities across the nation, so too is the distribution of scientific, engineering and computing resources. As a part of Sandia’s Institutional Computing Program, CA site-based Sandia computer scientists and engineers have been providing mission and research staff with local CA resident expertise on computing options while also focusing on two growing high performance computing research problems. The first is how to increase system resilience to failure, as machines grow larger, more complex and heterogeneous. The second is how to ensure that computer hardware and configurations are optimized for specialized data analytical mission needs within the overall Sandia computing environment, including the HPC subenvironment. All of these activities support the larger Sandia effort in accelerating development and integration of high performance computing into national security missions. Sandia continues to both promote national R&D objectives, including the recent Presidential Executive Order establishing the National Strategic Computing Initiative and work to ensure that the full range of computing services and capabilities are available for all mission responsibilities, from national security to energy to homeland defense.
We summarize the status of Deep Underground Neutrino Experiment (DUNE) Offline Software and Computing program. We describe plans for the computing infrastructure needed to acquire, catalog, reconstruct, simulate and analyze the data from the DUNE experiment and its prototypes in pursuit of the experiment's physics goals of precision measurements of neutrino oscillation parameters, detection of astrophysical neutrinos, measurement of neutrino interaction properties and searches for physics beyond the Standard Model. In contrast to traditional HEP computational problems, DUNE's Liquid Argon Time Projection Chamber data consist of simple but very large (many GB) data objects which share many characteristics with astrophysical images. We have successfully reconstructed and simulated data from 4% prototype detector runs at CERN. The data volume from the full DUNE detector, when it starts commissioning late in this decade will present memory management challenges in conventional processing but significant opportunities to use advances in machine learning and pattern recognition as a frontier user of High Performance Computing facilities capable of massively parallel processing. Our goal is to develop infrastructure resources that are flexible and accessible enough to support creative software solutions as HEP computing evolves.
The purpose of this CRADA project was to evaluate the seismic stability of block retaining wall systems. Retaining wall systems are used extensively in private and commercial developments. This study was designed to develop and demonstrate a computer modeling technology to be used to predict the seismic stability of any block wall system design. The nonlinear finite element computer programs developed at LLNL and employed in the Computational Earthquake Initiative were utilized in this small business CRADA to analyze the seismic stability of the block retaining walls. The unique capability of the LLNL programs to rigorously model frictional contact in a dynamic analysis problem were used in a computer simulation of the dynamic interaction the block waiVsoil systems under seismic excitation.
Ash and ion exchange resin wastes to be vitrified were considered among various radioactive wastes in the Japanese nuclear industry. The appropriate glass composition for the waste is calculated using the computer program. The glass composition is systematically studied using a ternary diagram, considering viscosity, electrical conductivity, and durability. The optimized glass composition based on calculated parameters of vitrification process and the convenience of mixing wastes is selected for crucible experiment. Since differences between calculated values and measured values may occur upon evaluation of glass formulations using glass formulation computer simulation program, the calculated glass formulations should be verified through experiments on a laboratory scale for more meticulous development of glass formulations. For the follow-up development of glass formulations, several glass formulations are planned to be developed. The candidate glasses for treatment of ash and ion exchange resin were melted and fabricated using reagents, respectively. The chemicals were weighed out to produce the desired batch compositions and mixed thoroughly and then put into clay crucibles for melting. Next, the crucibles were introduced into an electric furnace at 1,150 deg. C in the ambient atmosphere and pressure with occasional stirring by a quartz rod. A hold time of 1 hour was introduced to promote homogenization. Finally, the melted material was poured on a graphite plate to be rapidly cooled. The viscosities of all fabricated glasses were in the desired range. After rapid cooling, the micro-structure of the glasses was analyzed using the SEM. They exhibited amorphous structure with good homogeneity. (authors)
Genetic Programming (GP) is an evolutionary algorithm that generates computer programs, or mathematical expressions, to solve complex problems. In this Guide, we demonstrate how to use GP to develop surrogate models to mitigate the computational costs of modeling atomic nuclei with ever increasing complexity. The computational burden escalates when uncertainty quantification is pursued, or when observables must be globally computed for thousands of nuclei. By studying three models in which the mean field depends on the total particle density self-consistently, we show that by constructing reduced order models supported by GP one can speed up many-body computations by several orders of magnitude with a negligible loss in accuracy.
We describe a Python-based computer program, DEFT, for manipulating operators in effective field theories (EFTs). In its current incarnation, DEFT can be applied to 4-dimensional, Poincaré invariant theories with gauge group SU(3)×SU(2)×U(1), such as the Standard Model (SM), but a variety of extensions (e.g. to lower dimensions or to an arbitrary product of unitary gauge groups) are conceptually straightforward. Amongst other features, the program is able to: (i) check whether an input list of Lagrangian operators (of a given dimension in the EFT expansion) is a basis for the space of operators contributing to S-matrix elements, once redundancies (such as Fierz-Pauli identities, integration by parts, and equations of motion) are taken into account; (ii) generate such a basis (where possible) from an input algorithm; (iii) carry out a change of basis. We describe applications to the SM (where we carry out a number of non-trivial cross-checks) and extensions thereof, and outline how the program may be of use in precision tests of the SM and in the ongoing search for new physics at the LHC and elsewhere. The code and instructions can be downloaded from http://web.physics.ucsb.edu/~dwsuth/DEFT/.
We present that x-ray standing-wave photoemission experiments involving multilayered samples are emerging as unique probes of the buried interfaces that are ubiquitous in current device and materials research. Such data require for their analysis a structure optimization process comparing experiment to theory that is not straightforward. In this work, we present a new computer program for optimizing the analysis of standing-wave data, called SWOPT, that automates this trial-and-error optimization process. The program includes an algorithm that has been developed for computationally expensive problems: so-called black-box simulation optimizations. It also includes a more efficient version of the Yang X-ray Optics Program (YXRO) [Yang, S.-H., Gray, A.X., Kaiser, A.M., Mun, B.S., Sell, B.C., Kortright, J.B., Fadley, C.S., J. Appl. Phys. 113, 1 (2013)] which is about an order of magnitude faster than the original version. Human interaction is not required during optimization. We tested our optimization algorithm on real and hypothetical problems and show that it finds better solutions significantly faster than a random search approach. The total optimization time ranges, depending on the sample structure, from minutes to a few hours on a modern laptop computer, and can be up to 100x faster than a corresponding manual optimization. Finally, these speeds make the SWOPT program a valuable tool for realtime analyses of data during synchrotron experiments.
As quantum computers become available to the general public, the need has arisen to train a cohort of quantum programmers, many of whom have been developing classical computer programs for most of their careers. While currently available quantum computers have less than 100 qubits, quantum computing hardware is widely expected to grow in terms of qubit count, quality, and connectivity. This review aims at explaining the principles of quantum programming, which are quite different from classical programming, with straightforward algebra that makes understanding of the underlying fascinating quantum mechanical principles optional. We give an introduction to quantum computing algorithms and their implementation on real quantum hardware. We survey 20 different quantum algorithms, attempting to describe each in a succinct and self-contained fashion. We show how these algorithms can be implemented on IBM’s quantum computer, and in each case, we discuss the results of the implementation with respect to differences between the simulator and the actual hardware runs. This article introduces computer scientists, physicists, and engineers to quantum algorithms and provides a blueprint for their implementations.
Embodiments relate to program structure-based blocking. An aspect includes receiving source code corresponding to a computer program by a compiler of a computer system. Another aspect includes determining a prefetching section in the source code by a marking module of the compiler. Yet another aspect includes performing, by a blocking module of the compiler, blocking of instructions located in the prefetching section into instruction blocks, such that the instruction blocks of the prefetching section only contain instructions that are located in the prefetching section.
Embodiments relate to program structure-based blocking. An aspect includes receiving source code corresponding to a computer program by a compiler of a computer system. Another aspect includes determining a prefetching section in the source code by a marking module of the compiler. Yet another aspect includes performing, by a blocking module of the compiler, blocking of instructions located in the prefetching section into instruction blocks, such that the instruction blocks of the prefetching section only contain instructions that are located in the prefetching section.
This study was motivated by the efforts on evaluation of radiation risk for leukemia incidence in the Techa River Cohort, where the main bone marrow dose contributors were 89,90Sr (bone-seeking beta emitters). Energy deposition in bone marrow targets was evaluated by simulating radiation particle transport using computational phantoms. The present paper describes the computer program “Trabecula” implementing an algorithm for parametric generation of computational phantoms, which serve as the basis for calculating bone marrow doses. “Trabecula” is a user-friendly tool that automatically converts analytical models into voxelized representations that are directly compatible as input to MCNP.
In my undergraduate studies at the Massachusetts Institute of Technology (MIT), the short-lived chemical physics major allowed me to evade a number of courses required for chemistry majors. Thus, it was possible to take many physics courses and most of the advanced PhD-level courses in physical chemistry. I also took the introductory electrical engineering course in computer programming. The latter allowed me to write lots of computer code as a part of my (passing, but largely unsuccessful) senior thesis directed graciously by Professor Walter Thorson. As recommended by MIT Professor John C. Slater, I moved to Stanford University with Professor Frank Harris as my PhD supervisor. Frank was the perfect advisor for me, providing very close direction during the first year, and then allowing me to develop more and more independently. Within a few days of my twenty-fifth birthday, I became an assistant professor of chemistry at the University of California, Berkeley. Eighteen years later, I moved to the University of Georgia as director of a new research institute.
A method, system and computer program product are disclosed for routing data packet in a computing system comprising a multidimensional torus compute node network including a multitude of compute nodes, and an I/O node network including a plurality of I/O nodes. In one embodiment, the method comprises assigning to each of the data packets a destination address identifying one of the compute nodes; providing each of the data packets with a toio value; routing the data packets through the compute node network to the destination addresses of the data packets; and when each of the data packets reaches the destination address assigned to said each data packet, routing said each data packet to one of the I/O nodes if the toio value of said each data packet is a specified value. In one embodiment, each of the data packets is also provided with an ioreturn value used to route the data packets through the compute node network.
A method, system and computer program product are disclosed for routing data packet in a computing system comprising a multidimensional torus compute node network including a multitude of compute nodes, and an I/O node network including a plurality of I/O nodes. In one embodiment, the method comprises assigning to each of the data packets a destination address identifying one of the compute nodes; providing each of the data packets with a toio value; routing the data packets through the compute node network to the destination addresses of the data packets; and when each of the data packets reaches the destination address assigned to said each data packet, routing said each data packet to one of the I/O nodes if the toio value of said each data packet is a specified value. In one embodiment, each of the data packets is also provided with an ioreturn value used to route the data packets through the compute node network.