Merge pull request LLNL#308 from LLNL/november-news

November news

_posts/2019-11-01-esgfvideos.md

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+---
+title: "ESGF User Tutorial Videos"
+tags: multimedia
+---
+
+The [Earth System Grid Federation (ESGF)](https://github.com/esgf)—a robust, distributed data and computation platform enabling worldwide access to huge amounts of scientific data—has launched a [YouTube channel](https://www.youtube.com/channel/UCRTfkCkF-W8TSXO4-hrVFXQ) for user support. Current videos include tutorials for data downloads. Subscribe to the channel to be notified when new videos are posted.

_posts/2019-11-04-ccloud-0.12.md

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+---
+title: "Charliecloud 0.12 Released"
+tags: new-release
+---
+
+LANL led with LLNL contributors, Charliecloud provides user-defined software stacks for HPC centers. It uses Linux user namespaces to run containers with no privileged operations or daemons and minimal configuration changes on center resources. This simple approach avoids most security risks while maintaining access to the performance and functionality already on offer.
+
+This release contains two new test suite features:
+- Added a script `ch-test` that manages the tests
+- Removed the option to use an embedded Bats, eliminating the need for a Git submodule and simplifying packaging
+
+Learn more:
+- [Release notes](https://github.com/hpc/charliecloud/releases/tag/v0.12)
+- [GitHub repo](https://github.com/hpc/charliecloud)
+- [Documentation](https://hpc.github.io/charliecloud)

_posts/2019-11-07-cct-1.0.7.md

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+---
+title: "CCT 1.0.7 Released"
+tags: new-release
+---
+
+The Coda Calibration Tool (CCT) calculates reliable moment magnitudes for small- to moderate-sized seismic events. This release contains several new features, including:
+- Added a constraint set configuration panel in Parameter for the velocity model and the model space bounds on Shape (V/B/G) models for advanced users
+- Updated the input/output formats to include the new configurable fields
+- Updated notebook to use new REST JSON format for measurements
+- Added ability in Shape and Site to grow/shrink the data on the Y and X axis respectively via a button toggle
+
+Learn more:
+- [Release notes](https://github.com/LLNL/coda-calibration-tool/releases/tag/1.0.7)
+- [GitHub repo](https://github.com/LLNL/coda-calibration-tool), which includes a demo of CCT in action
+- *Science & Technology Review* article: [Stronger Structures through Scientific Collaboration](https://str.llnl.gov/2018-10/gok)

_posts/2019-11-07-spacktutorial-new.md

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+---
+title: "New Repo: Spack Tutorial"
+tags: new-repo
+---
+
+As part of Spack's [v0.13.0 release](https://github.com/spack/spack/releases/tag/v0.13.0), the tutorial has been broken out into [its own repo](https://github.com/spack/spack-tutorial) for easier archiving of versions from past events. The tutorial is available in [its own Read the Docs instance](https://spack-tutorial.readthedocs.io/en/latest/) while remaining navigable from Spack's [full RtD documentation](https://spack.readthedocs.io/en/latest/).

_posts/2019-11-08-esgfuk.md

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+---
+title: "ESGF Architecture Workshop"
+tags: trip-report
+---
+
+Members of the [Earth System Grid Federation (ESGF)](https://github.com/esgf) gathered in Abingdon, England, on November 5-7 to kick off the redesign process for the Federation's computing architecture. Since the original system was designed a decade ago, the number of ESGF's supported projects and disciplines has grown and diversified. Furthermore, operational requirements are clearer for the ESGF to support an international federated archive of this size. Many of the ESGF nodes now have other functions beyond CMIP (the Coupled Model Intercomparison Project), and the landscape of data repository and science needs has changed.
+
+Led by ESGF's Executive Committee, the workshop team discussed improvements to the user experience, data repository and management, data compute requirements, and platform and system administration. This workshop concluded with a high-level roadmap for future architecture directions, which will be presented at the larger ESGF conference in March. LLNL's delegates to the workshop were Ghaleb Abdulla (principal investigator and co-chair of the Executive Committee), Sasha Ames (member of multiple ESGF Working Teams) and Jason Boutte (Compute Working Team member).

_posts/2019-11-11-safire-new.md

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+---
+title: "New Repo: SAFIRE"
+tags: new-repo
+---
+
+[SAFIRE](https://github.com/LLNL/SAFIRE) (Scalable and Accurate Fault Injection for Parallel Multi-threaded Applications) is a fault injection framework, descending from REFINE, that supports injecting bit-flip faults in both serial and multi-threaded programs. SAFIRE includes a modified LLVM compiler backend for x86 to instrument and inject bit-flip faults on machine instructions. The backend implements several optimizations for fast instrumentation and injection that make SAFIRE the fastest and most accurate tool for fault injection so far.

_posts/2019-11-12-sweng101talk.md

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+---
+title: "Software Engineering 101: I have some code! Now what?"
+tags: trip-report, story, this-website
+---
+
+As part of LLNL’s _Computing 101_ speaker series, Ian Lee gave a talk to employees on November 12 titled “Software Engineering 101: I have some code! Now what?” The presentation reviewed the Lab’s resources for supporting software engineering and open source development.
+
+Lee, who manages this website and leads many initiatives in the Lab’s open source community, aimed his remarks at relative newcomers to the software development landscape. He also updated the audience on the state of open source development at the Lab.
+
+The Lab provides a wide range of support and solutions for just about any task a developer does: programing languages, package managers, computing platforms, code editors, version control systems, project communication, project tracking, documentation, and much more. Lee provided an overview of these options, offered advice about how to navigate the Lab’s software resources, and encouraged developers to take advantage of colleagues’ knowledge and experience.
+
+Lee summarized the Lab’s recent open source activity, which echoes a trend toward developing “out in the open,”—i.e., not waiting for code to mature before releasing it for community feedback and contributions. (As this website [shows](https://software.llnl.gov/explore/), the [Lab](https://github.com/llnl) and affiliated GitHub organizations have almost 600 repos.) Accordingly, the Lab has updated its open source release policies to support modern code development practices.
+
+Among open source projects Lee highlighted in his talk were 2019 R&D 100 Award winners [Spack](https://spack.io/) and [SCR (Scalable Checkpoint/Restart)](https://github.com/LLNL/scr) and the software stack underpinning the [Exascale Computing Project](https://www.exascaleproject.org/focus_area/software/).
+
+Lee also demoed this website’s category-driven design changes, LLNL’s open source logo (and stickers), the [@LLNL_OpenSource](https://twitter.com/LLNL_OpenSource) Twitter account, and [Slack channels](https://llnl.slack.com). He noted that LLNL may have a booth at [PyCon 2020](https://us.pycon.org/2020/), which will be held April 15-23 in Pittsburgh. (Conferences such as PyCon provide LLNL’s open source software community with opportunities for networking, collaboration, and technical skills development. Lab employees interested in attending similar events may contact Ian Lee for funding.)

_posts/2019-11-12-variorum-new.md

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+---
+title: "New Repo: Variorum"
+tags: new-repo
+---
+
+[Variorum](https://github.com/LLNL/variorum) is a platform-agnostic library exposing monitor and control interfaces for several features in hardware architectures. It provides general interfaces to provide privileged functionality for monitoring and controlling various hardware-level features of multiple hardware architectures. Variorum provides vendor-neutral APIs such that the user can query or control hardware knobs without needing to know the underlying vendor’s implementation. These APIs enable HPC application developers to gain a better understanding of performance through various metrics for the devices contained within the node. See the documentation for a [Quick Start Guide](https://variorum.readthedocs.io/en/latest/).

_posts/2019-11-13-caliper-2.2.0.md

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+---
+title: "Caliper 2.12.0 Released"
+tags: new-release
+---
+
+Caliper is a program instrumentation and performance measurement framework. It is designed as a performance analysis toolbox in a library, allowing one to bake performance analysis capabilities directly into applications and activate them at runtime. The latest release includes several improvements and new features, such as:
+- Many improvements to the ConfigManager API and syntax
+- Support for metadata collection with the [Adiak](https://github.com/LLNL/Adiak) library
+- Record memory high-water mark
+
+Learn more:
+- [Release notes](https://github.com/LLNL/Caliper/releases/tag/v2.2.0)
+- [GitHub repo](https://github.com/LLNL/Caliper)
+- [Documentation](https://llnl.github.io/Caliper/)
+- [Caliper: Application Introspection System](https://computing.llnl.gov/projects/caliper)

_posts/2019-11-18-hatchet-new.md

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+---
+title: "New Repo: Hatchet"
+tags: new-repo
+---
+
+[Hatchet](https://github.com/LLNL/hatchet) is a Python-based library that allows Pandas dataframes to be indexed by structured tree and graph data. It is intended for analyzing performance data that has a hierarchy (for example, serial or parallel profiles that represent calling context trees, call graphs, nested regions’ timers, etc.). Hatchet implements various operations to analyze a single hierarchical data set or compare multiple data sets, and its API facilitates analyzing such data programmatically. See the [documentation](https://hatchet.readthedocs.io/en/latest/) for more information including installation steps.

_posts/2019-11-19-merlin-new.md

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+---
+title: "LLNL-Led Team Wins SC19 Best Paper Award"
+tags: story, trip-report
+---
+
+On November 22, a panel of judges at the International Conference for High Performance Computing, Networking, Storage and Analysis (SC19) awarded a multi-institutional team led by LLNL computer scientists with the conference’s Best Paper award. The [paper](http://www.sci.utah.edu/~hbhatia/pubs/2019_SC_MUMMI.pdf), entitled “Massively Parallel Infrastructure for Adaptive Multiscale Simulations: Modeling RAS Initiation Pathway for Cancer,” describes the workflow driving a first-of-its-kind multiscale simulation on predictively modeling the dynamics of RAS proteins—a family of proteins whose mutations are linked to more than 30 percent of all human cancers—and their interactions with lipids, the organic compounds that help make up cell membranes.
+
+The team’s software, called MuMMI (Multiscale Machine-Learned Modeling Infrastructure), will soon be released as open source. Read more about the award on [LLNL news](https://www.llnl.gov/news/llnl-led-team-awarded-best-paper-sc19-modeling-cancer-causing-protein-interactions).

_posts/2019-11-22-sc19bestpaper.md

@@ -0,0 +1,8 @@
+---
+title: "LLNL-Led Team Wins SC19 Best Paper Award"
+tags: story, trip-report
+---
+
+On November 22, a panel of judges at the International Conference for High Performance Computing, Networking, Storage and Analysis (SC19) awarded a multi-institutional team led by LLNL computer scientists with the conference’s Best Paper award. The [paper](http://www.sci.utah.edu/~hbhatia/pubs/2019_SC_MUMMI.pdf), entitled “Massively Parallel Infrastructure for Adaptive Multiscale Simulations: Modeling RAS Initiation Pathway for Cancer,” describes the workflow driving a first-of-its-kind multiscale simulation on predictively modeling the dynamics of RAS proteins—a family of proteins whose mutations are linked to more than 30 percent of all human cancers—and their interactions with lipids, the organic compounds that help make up cell membranes.
+
+The team’s software, called MuMMI (Multiscale Machine-Learned Modeling Infrastructure), will soon be released as open source. Read more about the award on [LLNL news](https://www.llnl.gov/news/llnl-led-team-awarded-best-paper-sc19-modeling-cancer-causing-protein-interactions).

_posts/2019-11-26-quantkriging-new.md

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+---
+title: "New Repo: Quantkriging"
+tags: new-repo
+---
+
+[Quantkriging](https://github.com/LLNL/quantkriging) is a method to model the uncertainty of a stochastic simulation by modelling both the overall simulation response and the output distribution at each sample point. The output distribution is characterized by dividing it into quantiles, where the division of each quantile is determined by kriging.

_posts/2019-11-26-simplexdesign-new.md

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+---
+title: "New Repo: Simplexdesign"
+tags: new-repo
+---
+
+[Simplexdesign](https://github.com/LLNL/simplexdesign) is a collection of tools for the design of statistical experiments on Agent Based Models. It includes a coordinate exchange algorithm for homogeneous agents and, more generally, any simplex. The repo also includes an optimization algorithm for the case with multiple classes of homogeneous agents.