ASC Computational Environment (ACE) requirements version 8.0 final report.

A decision was made early in the Tri-Lab Usage Model process, that the collection of the user requirements be separated from the document describing capabilities of the user environment. The purpose in developing the requirements as a separate document was to allow the requirements to take on a higher-level view of user requirements for ASC platforms in general. In other words, a separate ASC user requirement document could capture requirements in a way that was not focused on ''how'' the requirements would be fulfilled. The intent of doing this was to create a set of user requirements that were not linked to any particular computational platform. The idea was that user requirements would endure from one ASC platform user environment to another. The hope was that capturing the requirements in this way would assist in creating stable user environments even though the particular platforms would be evolving and changing. In order to clearly make the separation, the Tri-lab S&CS program decided to create a new title for the requirements. The user requirements became known as the ASC Computational Environment (ACE) Requirements

Sandia National Laboratories Advanced Simulation and Computing (ASC) Software Quality Plan. Part 2, Mappings for the ASC software quality engineering practices. Version 1.0.

The purpose of the Sandia National Laboratories Advanced Simulation and Computing (ASC) Software Quality Plan is to clearly identify the practices that are the basis for continually improving the quality of ASC software products. The plan defines the ASC program software quality practices and provides mappings of these practices to Sandia Corporate Requirements CPR 1.3.2 and 1.3.6 and to a Department of Energy document, 'ASCI Software Quality Engineering: Goals, Principles, and Guidelines'. This document also identifies ASC management and software project teams responsibilities in implementing the software quality practices and in assessing progress towards achieving their software quality goals

Sandia National Laboratories Advanced Simulation and Computing (ASC) software quality plan. Part 1: ASC software quality engineering practices, Version 2.0.

The purpose of the Sandia National Laboratories Advanced Simulation and Computing (ASC) Software Quality Plan is to clearly identify the practices that are the basis for continually improving the quality of ASC software products. The plan defines the ASC program software quality practices and provides mappings of these practices to Sandia Corporate Requirements CPR 1.3.2 and 1.3.6 and to a Department of Energy document, ASCI Software Quality Engineering: Goals, Principles, and Guidelines. This document also identifies ASC management and software project teams responsibilities in implementing the software quality practices and in assessing progress towards achieving their software quality goals

Supercomputer and cluster performance modeling and analysis efforts:2004-2006.

This report describes efforts by the Performance Modeling and Analysis Team to investigate performance characteristics of Sandia's engineering and scientific applications on the ASC capability and advanced architecture supercomputers, and Sandia's capacity Linux clusters. Efforts to model various aspects of these computers are also discussed. The goals of these efforts are to quantify and compare Sandia's supercomputer and cluster performance characteristics; to reveal strengths and weaknesses in such systems; and to predict performance characteristics of, and provide guidelines for, future acquisitions and follow-on systems. Described herein are the results obtained from running benchmarks and applications to extract performance characteristics and comparisons, as well as modeling efforts, obtained during the time period 2004-2006. The format of the report, with hypertext links to numerous additional documents, purposefully minimizes the document size needed to disseminate the extensive results from our research

Red Storm usage model :Version 1.12.

Red Storm is an Advanced Simulation and Computing (ASC) funded massively parallel supercomputer located at Sandia National Laboratories (SNL). The Red Storm Usage Model (RSUM) documents the capabilities and the environment provided for the FY05 Tri-Lab Level II Limited Availability Red Storm User Environment Milestone and the FY05 SNL Level II Limited Availability Red Storm Platform Milestone. This document describes specific capabilities, tools, and procedures to support both local and remote users. The model is focused on the needs of the ASC user working in the secure computing environments at Los Alamos National Laboratory (LANL), Lawrence Livermore National Laboratory (LLNL), and SNL. Additionally, the Red Storm Usage Model maps the provided capabilities to the Tri-Lab ASC Computing Environment (ACE) requirements. The ACE requirements reflect the high performance computing requirements for the ASC community and have been updated in FY05 to reflect the community's needs. For each section of the RSUM, Appendix I maps the ACE requirements to the Limited Availability User Environment capabilities and includes a description of ACE requirements met and those requirements that are not met in that particular section. The Red Storm Usage Model, along with the ACE mappings, has been issued and vetted throughout the Tri-Lab community

PDS/PIO: Lightweight libraries for collective parallel I/O

PDS/PIO is a lightweight, parallel interface designed to support efficient transfers of massive, grid-based, simulation data among memory, disk, and tape subsystems. The higher-level PDS (Parallel Data Set) interface manages data with tensor and unstructured grid abstractions, while the lower-level PIO (Parallel Input/Output) interface accesses data arrays with arbitrary permutation, and provides communication and collective I/O operations. Higher-level data abstraction for finite element applications is provided by PXI (Parallel Exodus Interface), which supports, in parallel, functionality of Exodus II, a finite element data model developed at Sandia National Laboratories. The entire interface is implemented in C with Fortran-callable PDS and PXI wrappers