NERSCPowering Scientific Discovery Since 1974

Charlson Kim

FES Requirements Worksheet

1.1. Project Information - Plasma Science and Innovation Center

Document Prepared By

Charlson Kim

Project Title

Plasma Science and Innovation Center

Principal Investigator

Charlson Kim

Participating Organizations

U. Washington, U. Wisconsin-Madison, Utah State, NRL

Funding Agencies

 DOE SC  DOE NSA  NSF  NOAA  NIH  Other:

2. Project Summary & Scientific Objectives for the Next 5 Years

Please give a brief description of your project - highlighting its computational aspect - and outline its scientific objectives for the next 3-5 years. Please list one or two specific goals you hope to reach in 5 years.

The goal is to develop practical and accurate methods to capture the physics needed for predictability in user-friendly codes that take full advantage of state of the art computers that have thousands or more processors. The new methods are being incorporated into the 3D codes and results are compared with data from all participating experiments. The methods will be further refined as needed until predictive capability is achieved for all experiments. A long term goal is the development of design tools that will lead the rapid and cost effective advancement of fusion experiments and of basic plasma science in general.

3. Current HPC Usage and Methods

3a. Please list your current primary codes and their main mathematical methods and/or algorithms. Include quantities that characterize the size or scale of your simulations or numerical experiments; e.g., size of grid, number of particles, basis sets, etc. Also indicate how parallelism is expressed (e.g., MPI, OpenMP, MPI/OpenMP hybrid)

NIMROD - 3D extended MHD initial value, finite elements and spectral spatial representation, implicit time advance, with PIC and continuum method in development. The largest fluid computations involve millions of spatial grid points evolved over tens of thousands of timesteps, evolving on the order of a dozen independent variables. The hybrid kinetic-MHD delta-f PIC module typically runs millions of particles for linear simulations although 100's millions of particle simulations have been successfully demonstrated. The parallelism is accomplished through MPI. 
 
HIFI/SEL - 3D extended MHD initial value, modal finite elements for all 3 dimensions, similar fluid capabilities as NIMROD. Parallelism also through MPI (primarily through PETSC packpage) 
 
PSITET - 3D equilibrium solver using tetrahedral elements uses hybrid OpenMP/MPI. 

3b. Please list known limitations, obstacles, and/or bottlenecks that currently limit your ability to perform simulations you would like to run. Is there anything specific to NERSC?

limited by scaling capabilities of sparse linear solvers 

3c. Please fill out the following table to the best of your ability. This table provides baseline data to help extrapolate to requirements for future years. If you are uncertain about any item, please use your best estimate to use as a starting point for discussions.

Facilities Used or Using

 NERSC  OLCF  ACLF  NSF Centers  Other:  

Architectures Used

 Cray XT  IBM Power  BlueGene  Linux Cluster  Other:  SGI Altix

Total Computational Hours Used per Year

 600000 Core-Hours

NERSC Hours Used in 2009

 300000 Core-Hours

Number of Cores Used in Typical Production Run

 100-300

Wallclock Hours of Single Typical Production Run

 10-30

Total Memory Used per Run

 100s? GB

Minimum Memory Required per Core

 1-4 GB

Total Data Read & Written per Run

 10s GB

Size of Checkpoint File(s)

 ? GB

Amount of Data Moved In/Out of NERSC

 ? GB per  

On-Line File Storage Required (For I/O from a Running Job)

 ? TB and  Files

Off-Line Archival Storage Required

? TB and  Files

Please list any required or important software, services, or infrastructure (beyond supercomputing and standard storage infrastructure) provided by HPC centers or system vendors.

SuperLU and supporting software, VISIT 

4. HPC Requirements in 5 Years

4a. We are formulating the requirements for NERSC that will enable you to meet the goals you outlined in Section 2 above. Please fill out the following table to the best of your ability. If you are uncertain about any item, please use your best estimate to use as a starting point for discussions at the workshop.

Computational Hours Required per Year

 500000

Anticipated Number of Cores to be Used in a Typical Production Run

 100s

Anticipated Wallclock to be Used in a Typical Production Run Using the Number of Cores Given Above

 20

Anticipated Total Memory Used per Run

 100s? GB

Anticipated Minimum Memory Required per Core

 2 GB

Anticipated total data read & written per run

 10s? GB

Anticipated size of checkpoint file(s)

 ? GB

Anticipated Amount of Data Moved In/Out of NERSC

 ? GB per  

Anticipated On-Line File Storage Required (For I/O from a Running Job)

 ? TB and  Files

Anticipated Off-Line Archival Storage Required

? TB and  Files

4b. What changes to codes, mathematical methods and/or algorithms do you anticipate will be needed to achieve this project's scientific objectives over the next 5 years.

improved solvers 
 
improved PIC algorithms

4c. Please list any known or anticipated architectural requirements (e.g., 2 GB memory/core, interconnect latency < 1 μs).

low latency always helps

4d. Please list any new software, services, or infrastructure support you will need over the next 5 years.

improved workflow services - easy way of setting up/queuing batches of runs with on the fly postprocessing and posting of data to accessible website. 
 
web-based, checkbox driven way of specifying files and directories for backup services 
 
continued dedicated graphics machine with VISIT server 
 
module support of NIMROD executables (and other flagship codes) 
 
direct support for massive undertaking of the anticipated paradigm shift in parallel computing forshadowed in the next question 

4e. It is believed that the dominant HPC architecture in the next 3-5 years will incorporate processing elements composed of 10s-1,000s of individual cores, perhaps GPUs or other accelerators. It is unlikely that a programming model based solely on MPI will be effective, or even supported, on these machines. Do you have a strategy for computing in such an environment? If so, please briefly describe it.

aside from hiring a graduate student and hoping for the best, i have no strategy yet devised for the unspecified machine of unspecified architecture using an unspecified API 

New Science With New Resources

To help us get a better understanding of the quantitative requirements we've asked for above, please tell us: What significant scientific progress could you achieve over the next 5 years with access to 50X the HPC resources you currently have access to at NERSC? What would be the benefits to your research field if you were given access to these kinds of resources?

Please explain what aspects of "expanded HPC resources" are important for your project (e.g., more CPU hours, more memory, more storage, more throughput for small jobs, ability to handle very large jobs).

a raw hardware power increase would most likely bring any significant physics research to a grinding halt as the codes are retooled to "take advantage" of "the increased performance" of the new machine.  
 
the smaller scale experiments run comparably smaller simulations compared to large tokamak simulations. 
more throughput with longer runtimes for modest sized jobs would be the most beneficial