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Updated publications and presentations #133

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Updated publications and presentations #133

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efe3a92
Update Open XDMoD overview
jtpalmer May 8, 2017
1bcd62c
Merge pull request #130 from jtpalmer/update-docs
jtpalmer May 8, 2017
97c879e
Updated publications and presentations
smgallo May 8, 2017
4bf3cd8
Fix capitalization
smgallo May 8, 2017
ef06c9c
Additional capitalization changes
smgallo May 8, 2017
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62 changes: 32 additions & 30 deletions docs/index.md
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title: Open XDMoD
---

XDMoD (XD Metrics on Demand) is an NSF-funded open source tool designed
to audit and facilitate the utilization of the XSEDE cyberinfrastructure
by providing a wide range of metrics on XSEDE resources, including
resource utilization, resource performance, and impact on scholarship
and research. The [XDMoD](https://xdmod.ccr.buffalo.edu/) framework is
designed to meet the following objectives: (1) provide the user
community with a tool to manage their allocations and optimize their
resource utilization, (2) provide operational staff with the ability to
monitor and tune resource performance, (3) provide management with a
tool to monitor utilization, user base, and performance of resources,
and (4) provide metrics to help measure scientific impact. While
initially focused on the XSEDE program, Open XDMoD has been created to
be adaptable to any HPC environment.

The framework includes a computationally lightweight application kernel
auditing system that utilizes performance kernels chosen from both
low-level benchmarks and actual scientific and engineering applications
to measure overall system performance from the user’s perspective. This
allows continuous resource monitoring to measure all aspects of system
performance including file-system, processor, and memory performance,
and network latency and bandwidth. Current and past utilization
metrics, coupled with application kernel-based performance analysis, can
be used to help guide future cyberinfrastructure investment decisions,
plan system upgrades, tune machine performance, improve user job
throughput, and facilitate routine system operation and maintenance.
Open XDMoD is an open source tool to facilitate the management of high
performance computing resources. It is widely deployed at academic,
industrial and governmental HPC centers. Open XDMoD's management
capabilities include monitoring standard metrics such as utilization,
providing quality of service metrics designed to proactively identify
underperforming system hardware and software, and reporting job level
performance data for every job running on the HPC system without the
need to recompile applications. Open XDMoD is designed to meet the
following objectives: (1) provide the user community with a tool to more
effectively and efficiently use their allocations and optimize their use
of HPC resources, (2) provide operational staff with the ability to
monitor, diagnose, and tune system performance as well as measure the
performance of all applications running on their system, (3) provide
software developers with the ability to easily obtain detailed analysis
of application performance to aid in optimizing code performance, (4)
provide stakeholders with a diagnostic tool to facilitate HPC planning
and analysis, and (5) provide metrics to help measure scientific impact.
In addition, analyses of the operational characteristics of the HPC
environment can be carried out at different levels of granularity,
including job, user, or on a system-wide basis.

The Open XDMoD portal provides a rich set of features accessible through
an intuitive graphical interface, which is tailored to the role of the
user. Metrics provided include: number of jobs, CPUs consumed, wait
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I don't like the phrase "CPUs consumed"

Suggest either "job size" or "CPU hours consumed" depending on what the original phrase was supposed to mean.

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Oops, looks like this pulled in Jeff's modification to the 6.6 branch as well after I git a git pull. That's the text that Tom wanted updated...

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I've emailed Tom to get his opinion.

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I've created #135 to address this issue. You can rebase this branch against xdmod6.7 and remove those commits.

time, and wall time, with minimum, maximum and the average of these
metrics, in addition to many others. Metrics are organized by a
customizable hierarchy appropriate for your organization.

A version of Open XDMoD, namely [XDMoD](https://xdmod.ccr.buffalo.edu/),
was developed to monitor the NSF supported portfolio of supercomputers
that fall under the [XSEDE](https://www.xsede.org/) program.

This work was sponsored by NSF under grant numbers
[ACI 1025159][nsf-1025159] and [ACI 1445806][nsf-1445806] for the
development of technology audit service for XSEDE.
[ACI 1025159][nsf-1025159] and [ACI 1445806][nsf-1445806].

[nsf-1025159]: http://nsf.gov/awardsearch/showAward?AWD_ID=1025159
[nsf-1445806]: http://nsf.gov/awardsearch/showAward?AWD_ID=1445806

**NOTE**: Not all of the XDMoD features mentioned above are currently
available in Open XDMoD.

For more information, questions, or feedback send email to
`ccr-xdmod-help` at `buffalo.edu`.

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10 changes: 10 additions & 0 deletions html/about/presentations.html
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<p><b><font size="5">Presentations</font></b></p>
<br>

<div><b>SC16: Salt Lake City, UT</b></div>
<ul>
<li> <a target="_blank" href="https://drive.google.com/open?id=0Bw-3_B_73Ep1dlo2Ykxma05yYzA">Data Analytics Support for HPC System Management</a> </li>
</ul>

<div><b>XSEDE16: Miami, FL</b></div>
<ul>
<li> <a target="_blank" href="https://drive.google.com/open?id=0Bw-3_B_73Ep1MTFpaS1XRTluUEk">XDMoD Job Viewer Overview</a> and <a target="_blank" href="https://drive.google.com/open?id=0Bw-3_B_73Ep1TklwR2xWcXllWEE">XDMoD Job Viewer Hands On Tutorial</a></li>
</ul>

<div><b>HPCMASPA 2015: Chicago, IL</b></div>
<ul>
<li> <a target="_blank" href="https://drive.google.com/open?id=0Bw-3_B_73Ep1WlA5UDVidDNoMlU">Analysis of XDMoD/SUPReMM Data Using Machine Learning Techniques</a></li>
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<a href="http://dx.doi.org/10.1109/MCSE.2015.68" target="_blank">10.1109/MCSE.2015.68</a></b>
</p>

<div><b>2017:</b></div>
<ol>
<li> Joseph White, Martins Innus, Matthew Jones, Robert DeLeon, Nikolay A. Simakov, Jeffery Palmer, Steven Gallo, Thomas Furlani, Michael Showerman, Robert Brunner, Andriy Kot, Gregory Bauer, Brett Bode, Jeremy Enos and William Kramer, "Challenges of workload analysis on large HPC systems; a case study on NCSA Blue Waters". Accepted for PEARC 17. </li>
<br>
<li> Ben Fulton, Steven Gallo, Matt Link, Robert Henschel, Tom Yearke, Katy Borner, Robert L. DeLeon, Thomas Furlani and Craig A. Stewart, "Value Analytics: A Financial Module for the Open XDMoD Project". Accepted for PEARC 17. </li>
</ol>

<div><b>2016:</b></div>
<ol>
<li>Nikolay Simakov, Robert L. DeLeon, Joseph P. White, Thomas R. Furlani, Martins Innus, Steven M. Gallo, Matthew D. Jones, Abani Patra, Benjamin D. Plessinger, Jeanette M. Sperhac, Thomas Yearke, Ryan Rathsam, Jeffrey T. Palmer "A quantitative Analysis of node Sharing on HPC Clusters Using XDMoD Application Kernels" , XSEDE16: Proceedings of the XSEDE16 Conference on Diversity, Big Data, and Science at Scale (Article No. 32 ). Miami, FL. <a href="http://dx.doi.org/10.1145/2949550.2949553" target="_blank">10.1145/2949550.2949553</a></li>
<li>Nikolay Simakov, Robert L. DeLeon, Joseph P. White, Thomas R. Furlani, Martins Innus, Steven M. Gallo, Matthew D. Jones, Abani Patra, Benjamin D. Plessinger, Jeanette M. Sperhac, Thomas Yearke, Ryan Rathsam, Jeffrey T. Palmer "A Quantitative Analysis of Node Sharing on HPC Clusters Using XDMoD Application Kernels" , XSEDE16: Proceedings of the XSEDE16 Conference on Diversity, Big Data, and Science at Scale (Article No. 32 ). Miami, FL. <a href="http://dx.doi.org/10.1145/2949550.2949553" target="_blank">10.1145/2949550.2949553</a></li>
</ol>

<div><b>2015:</b></div>
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