Case Study Worksheet

Project Information - The Joint Bioenergy Institute (JBEI)

Project Summary (Scientific Objectives)

Please give a brief description of your project and its scientific objectives for the next 3-5 years.

Transportation fuels are the largest end use of energy by sector in the U.S. A full two-thirds of the 
world's petroleum resources are used for transportation, and 60% of that is used for ground 
transportation. Despite increasing demand, petroleum production is expected to peak within 10-30 
years, after which time worldwide production will decline until resources are exhausted, resulting in 
dramatically higher fuel costs and potentially disastrous geopolitical conflicts for resources. In addition, 
each gallon of gasoline and diesel produces 20 pounds of carbon dioxide (7 tons per vehicle per year), 
heavily contributing to global warming and far-reaching climate changes. 
 
The Joint BioEnergy Institute (JBEI) is designed to address these roadblocks in biofuels production. JBEI 
draws on the expertise and capabilities of three national laboratories (Lawrence Berkeley National 
Laboratory (LBNL), Sandia National Laboratories (SNL), and Lawrence Livermore National Laboratory 
(LLNL) and three leading US academic institutions (University of California campuses at Berkeley (UCB) 
and Davis (UCD); and the Carnegie Institution of Washington) to create the transformational discoveries 
needed to convert the energy stored in lignocellulose into renewable biofuels. 
 
We propose to develop a computational model that will enable the predictive tailoring of pretreatments 
to specific biomass types using multi-scale, multi-physics computational approaches. The initial 
development of this model will focus on biomass under pretreatment conditions. The macroscopic 
processes of transport, mechanical deformation, and tissue degradation arise from microscopic 
processes at the cellular and molecular length scales. These modeling approaches will utilize the 
Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS). We will simulate the deformation 
of, and fluid flow and solute transport through, a micromechanical model of biomass to investigate the 
effects of microstructure on the material response and transport parameters such as the fluid 
permeability and pretreatment solute mobilities. At the continuum scale, we will employ a mixture 
theory approach for modeling the coupled processes of mechanical deformation, transport, and 
chemical conversion involved in lignocellulose degradation. The chemical process of material 
degradation will be incorporated into the mixture theory through mass sources/sinks terms which will 
be modeled based on the measured reaction kinetics. This model will be validated with the 
experimental results obtained from pretreatment processing of biomass.

Current HPC Usage and Methods

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

Gaussian03 
GROMACS 
LAMMPS 
fftw

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)

GROMACS 
Molecular dynamics simulations 
 
Gaussian03 
Quantum Mechanical Calculations 
 
LAMMPS 
Multi-scale molecular dynamics simulations. 
Simulation of Newton's equations of motion for a system of interacting particles 
N-body calculations, integration of the equations of motion using finite difference methods. 
 

Please list the known limitations/obstacles/bottleneck of resources currently available HPC systems, and in particular, those at NERSC.

HPC Usage and Methods for the Next 3-5 Years

Anticipated changes to codes, mathematical methods and/or algorithms needed to achieve this project's scientific objectives.

Known or Anticipated architectural requirements (e.g., 2 GB memory/core).

Please list any additional required or important software, services, or infrastructure beyond those listed in the previous section.

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. 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.

What Do You Need from NERSC?

Please tell us what you need from NERSC to meet your project's computing needs over the next 3-5 years. Also please feel free to make any general comments.