Topics

Data collection, transport, and storage

• Design of systems and frameworks for HPC monitoring which address HPC requirements such as:

  • Extreme scalability

  • Run time data collection and transport

  • Analysis on actionable timescales

  • Feedback on actionable timescales

  • Minimal application impact

• Extraction and evaluation of resource utilization and state information from current and next generation components (e.g., GPU, MICS)

• Monitoring methodologies and results for all HPC system components and support infrastructure (e.g., compute, network, storage, power)

• How not to do it, with explanations, benchmarks, or analysis of code to save the rest of us from trying it again

Analysis of monitored data and system information

• Extraction of meaningful information from raw data, such as system and resource health, contention, or bottlenecks

• Methodologies and applications of analysis algorithms on large scale HPC system data

• Visualization techniques for large scale HPC data (addressing size, timescales, presentation within a meaningful context)

• Evaluation of correlative relationships between system state and application performance via use of monitored system data

Response to and utilization of processed data and system information

• Mechanisms for feedback and response to applications and system software (e.g., informing schedulers, down-clocking CPUs)

• HPC application design and implementation that take advantage of monitored system data (e.g., dynamic task placement or rank-to-core mapping)

• System-level and Job-level feedback and responses to monitored system data

• Job Scheduling and Allocation based on monitored system information (e.g. contention for storage or network resources)

• Use of monitored system data for evaluation of future systems specifications and requirements

• Use of monitored system data for validation of systems simulations

Important dates

• May 31 AOE - Abstract due

• June 7 AOE - Papers due (contingent upon abstract submission by 5/31)

  • June 30 - Acceptance notification

  • July 21 - Camera ready papers due

  • Sept 26 - Workshop

Format

HPCMASPA 2014 welcomes submissions for the following:

Technical Papers (30 minute presentation):

These submissions consist of work not previously published nor under review by another conference or journal. Accepted papers will be included in the workshop proceedings published by IEEE.

Mini-talks (15 minute presentation):

These submissions can consist of previously published work and can address work-in-progress, highlight gap areas, motivate research areas, etc. Accepted mini-talks will not be published in the proceedings.

Submission Guidelines:

• • Submissions (either type) must be compliant with the IEEE Xplore format for publication. LaTeX (preferred) and Word Templates are available here. Additional instructions can be found on the IEEE Cluster site.

  • Maximum 8 pages for Technical Papers

  • Maximum 4 pages descriptive text and figures for Mini-talks

  • Web-based submission through EasyChair. PDF's only.

  • Submissions must be in English.

  • Submission implies the willingness of at least one of the authors to register and present the work associated with submission.

  • Submissions will be evaluated on their originality, technical soundness, significance, presentation, and interest to the workshop attendees.

Organization

Organizing Committee

• Benjamin Allan, Sandia National Laboratories

• Jim Brandt, Sandia National Laboratories

• Ann Gentile, Sandia National Laboratories

• Cory Lueninghoener, Los Alamos National Laboratory

• Nichamon Naksinehaboon, Open Grid Computing

• Boyana Norris, University of Oregon

• Narate Taerat, Open Grid Computing

Program Committee

• Jon Cook, New Mexico State University

• Narayan Desai, Argonne National Laboratory

• Richard Gerber, NERSC

• Forest Godfrey, Cray

• Yun (Helen) He, Lawrence Berkeley National Laboratory

• Karen Karavanic, Portland State University

• Zhiling Lan, Illinois Institute of Technology

• Box Leangsuksun, Louisiana Tech University

• Mike Mason, Los Alamos National Laboratory

• Henry Neeman, Oklahoma University Supercomputing Center for Education & Research

• Martin Schulz, Lawrence Livermore National Laboratory

• Mike Showerman, NCSA

• David Thompson, Kitware

• Ziming Zheng, HP Vertica