nuclear plants currently under construction including 10 in China, 8 in India, and 4 in Russia. In the United States, there have been notifications to the Nuclear Regulatory Commission of intentions to apply for combined construction and operating licenses for 27 new units over the next decade. The projected growth in nuclear power has focused increasing attention on issues related to the permanent disposal of nuclear waste, the proliferation of nuclear weapons technologies and materials, and the sustainability of a once-through nuclear fuel cycle. In addition, the effective utilization of nuclear power will require continued improvements in nuclear technology, particularly related to safety and efficiency. In all of these areas, the performance of materials and chemical processes under extreme conditions is a limiting factor. The related basic research challenges represent some of the most demanding tests of our fundamental understanding of materials science and chemistry, and they provide significant opportunities for advancing basic science with broad impacts for nuclear reactor materials, fuels, waste forms, and separations techniques. Of particular importance is the role that new nanoscale characterization and computational tools can play in addressing these challenges. These tools, which include DOE synchrotron X-ray sources, neutron sources, nanoscale science research centers, and supercomputers, offer the opportunity to transform and accelerate the fundamental materials and chemical sciences that underpin technology development for advanced nuclear energy systems. The fundamental challenge is to understand and control chemical and physical phenomena in multi-component systems from femto-seconds to millennia, at temperatures to 1000?C, and for radiation doses to hundreds of displacements per atom (dpa). This is a scientific challenge of enormous proportions, with broad implications in the materials science and chemistry of complex systems. New understanding is required for microstructural evolution and phase stability under relevant chemical and physical conditions, chemistry and structural evolution at interfaces, chemical behavior of actinide and fission-product solutions, and nuclear and thermomechanical phenomena in fuels and waste forms. First-principles approaches are needed to describe f-electron systems, design molecules for separations, and explain materials failure mechanisms. Nanoscale synthesis and characterization methods are needed to understand and design materials and interfaces with radiation, temperature, and corrosion resistance. Dynamical measurements are required to understand fundamental physical and chemical phenomena. New multiscale approaches are needed to integrate this knowledge into accurate models of relevant phenomena and complex systems across multiple length and time scales.

NNSA to support stockpile requirements. The ultimate goal of the SSP, and thus of the Advanced Simulation and Computing (ASC) Program, is to ensure that the U.S. maintains a safe, secure, and effective strategic deterrent.

Productivity from day one on supercomputers that leverage new technologies requires significant preparation. An institution that procures a novel system architecture often lacks sufficient institutional knowledge and skills to prepare for it. Thus, the "Center of Excellence" (CoE) concept has emerged to prepare for systems such as Summit and Sierra, currently the top two systems in the Top 500. This paper documents CoE experiences that prepared a workload of diverse applications and math libraries for a heterogeneous system. We describe our approach to this preparation, including our management and execution strategies, and detail our experiences with and reasons for using different programming approaches. Our early science and performance results show that the project enabled significant early seismic science with up to a l4X throughput increase over Cori. In addition to our successes, we discuss our challenges and failures so others may benefit from our experience.

This work plan encompasses a slice of effort going on within the ASC program, and for projects which are actively utilizing (or wish to utilize) COE vendor resources. It may describe work that will be performed by both LLNL staff and COE vendor staff collaboratively.

The Sidney Fernbach Postdoctoral Fellowship in the Computing Sciences was established in 2012 to attract top new researchers into the Computation Directorate. Similar to LLNL’s Lawrence Fellowship, it offers outstanding new scientists the opportunity to establish their own research directions with a great deal of autonomy. The Lawrence Fellowship is open to all technical disciplines at the Laboratory and is awarded to several candidates each year. The Fernbach, on the other hand, focuses specifically on disciplines in the computing sciences: applied mathematics, computer science, computational science, and data science. It usually supports one fellow at a time for a two-year term.

Proposing a Center of Excellence under the CORAL-2 NRE is a mandatory requirement. The current Sierra COE (CORAL-1) is largely focused on helping LLNL applications make the disruptive transition to a heterogeneous GPU-based system by 2018. We expect a continuation of COE activities around optimizing our broad and diverse application base (of so-called “traditional” simulation codes) optimized for the El Capitan architecture, as well as supporting the underlying software stack (compilers, tools, programming models, etc.) – but do not expect this to require as much effort in the El Capitan COE (assuming a heterogeneous node architecture). What follows are some thoughts on 3 potential topics of interest for an El Capitan COE at LLNL – largely focused around AI and machine learning and the concept of advancing our goal of intelligent simulation or cognitive computing in the timeframe of deployment and production use of El Capitan (2023-2038). We believe vendor engagement through a COE in this area will provide a natural point-of-interest between LLNL and our vendor partner for common advancement of machine learning capabilities focused on scientific data – potentially greatly broadening the ecosystem around HPC architectures and the supporting software stack for scientific simulation-based AI.

This ASC Co-design Strategy lays out the full continuum and components of the co-design process, based on what we have experienced thus far and what we wish to do more in the future to meet the program’s mission of providing high performance computing (HPC) and simulation capabilities for NNSA to carry out its stockpile stewardship responsibility.

In 2015, the three Department of Energy (DOE) National Laboratories that make up the Advanced Sci- enti c Computing (ASC) Program (Sandia, Lawrence Livermore, and Los Alamos) collaboratively explored performance portability programming environments in the context of several ASC co-design proxy applica- tions as part of a tri-lab L2 milestone executed by the co-design teams at each laboratory. The programming environments that were studied included Kokkos (developed at Sandia), RAJA (LLNL), and Legion (Stan- ford University). The proxy apps studied included: miniAero, LULESH, CoMD, Kripke, and SNAP. These programming models and proxy-apps are described herein. Each lab focused on a particular combination of abstractions and proxy apps, with the goal of assessing performance portability using those. Performance portability was determined by: a) the ability to run a single application source code on multiple advanced architectures, b) comparing runtime performance between \native" and \portable" implementations, and c) the degree to which these abstractions can improve programmer productivity by allowing non-portable implementation details to be hidden from the application developer. This report captures the work that was completed for this milestone, and outlines future co-design work to be performed by application developers, programming environment developers, compiler writers, and hardware vendors.

On July 31-August 2 of 2012, the U.S. Department of Energy (DOE) held a workshop entitled Grand Challenges of Advanced Computing for Energy Innovation. This workshop built on three earlier workshops that clearly identified the potential for the Department and its national laboratories to enable energy innovation. The specific goal of the workshop was to identify the key challenges that the nation must overcome to apply the full benefit of taxpayer-funded advanced computing technologies to U.S. energy innovation in the ways that the country produces, moves, stores, and uses energy. Perhaps more importantly, the workshop also developed a set of recommendations to help the Department overcome those challenges. These recommendations provide an action plan for what the Department can do in the coming years to improve the nation’s energy future.

how these major facilities are organized by program elements. Section II gives a more detailed breakdown of the over 200 research and technology facilities being used at the Laboratories to support the Defense Programs mission.

DOI: 10.1049/ic:20040412 ISBN: 0 86341 418 4 Location: Edinburgh, UK Conference date: 24 May 2004 Format: PDF We discuss several software engineering practices that have proven useful in a large multidisciplinary physics code development project at Lawrence Livermore National Laboratory. In the project discussed, as with many large-scale efforts in HPC scientific computing, we have had to balance the competing demands of being a stable "production" code that our user base can rely on with being a platform for research into new physics, models, and software architectures. The ideas presented here are not meant to necessarily transfer to other environments with different needs. It is our belief that projects need to be given large latitude in defining their own software engineering process versus a prescribed a solution. However, the ideas presented are hopefully high level and general enough that we hope other projects might find some inspiration and adopt similar methods if it is to their benefit, much as we have done through the years. Inspec keywords: software quality; program testing; software development management; configuration management; software metrics Subjects: Software engineering techniques; Software management; Diagnostic, testing, debugging and evaluating systems

A parallel application benefits from scheduling policies that include a global perspective of the application's process working set. As the interactions among cooperating processes increase, mechanisms to ameliorate waiting within one or more of the processes become more important. In particular, collective operations such as barriers and reductions are extremely sensitive to even usually harmless events such as context switches among members of the process working set. For the last 18 months, we have been researching the impact of random short-lived interruptions such as timer-decrement processing and periodic daemon activity, and developing strategies to minimize their impact on large processor-count SPMD bulk-synchronous programming styles. We present a novel co-scheduling scheme for improving performance of fine-grain collective activities such as barriers and reductions, describe an implementation consisting of operating system kernel modifications and run-time system, and present a set of empirical results comparing the technique with traditional operating system scheduling. Our results indicate a speedup of over 300% on synchronizing collectives.

We have continued to improve our ability to model the response of energetic materials to thermal stimuli and the processes involved in the energetic response. Several new algorithms have been developed to increase the accuracy and fidelity of the modeling process. These include a level set driven multi-material deflagration model, a multi-temperature mixed material treatment, self-consistent thermal-hydro coupling, full implicit quasi-static hydrodynamics, ale slide surfaces and ale slide deletion. These capabilities have allowed us to improve our ability to model the cookoff process from the initial application of heat to the final metal expansion.