skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Addressing Unknown Constants and Metabolic Network Behaviors Through Petascale Computing: Understanding H2 Production in Green Algae

Abstract

The Genomics Revolution has resulted in a massive and growing quantity of whole-genome DNA sequences, which encode the metabolic catalysts necessary for life. However, gene annotations can rarely be complete, and measurement of the kinetic constants associated with the encoded enzymes can not possibly keep pace, necessitating the use of careful modeling to explore plausible network behaviors. Key challenges are (1) quantitatively formulating kinetic laws governing each transformation in a fixed model network; (2) characterizing the stable solution (if any) of the associated ordinary differential equations (ODEs); (3) fitting the latter to metabolomics data as it becomes available; and, (4) optimizing a model output against the possible space of kinetic parameters, with respect to properties such as robustness of network response, or maximum consumption/production. This SciDAC-2 project addresses this large-scale uncertainty in the genome-scale metabolic network of the water-splitting, H{sub 2}-producing green alga Chlamydomonas reinhardtii. Each metabolic transformation is formulated as an irreversible steady-state process, such that the vast literature on known enzyme mechanisms may be incorporated directly. To start, glycolysis, the tricarboxylic acid cycle, and basic fermentation pathways have been encoded in Systems Biology Markup Language (SBML) with careful annotation and consistency with the KEGG database, yielding a modelmore » with 3 compartments, 95 species, 38 reactions, and 109 kinetic constants. To study and optimize such models with a view toward larger models, we have developed a system which takes as input an SBML model, and automatically produces C code that when compiled and executed optimizes the model's kinetic parameters according to test criteria. We describe the system and present numerical results. Further development, including overlaying of a parallel multistart algorithm, will allow optimization of thousands of parameters on high-performance systems ranging from distributed grids to unified petascale architectures.« less

Authors:
; ; ;
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
982280
DOE Contract Number:
AC36-08GO28308
Resource Type:
Conference
Resource Relation:
Conference: Proceedings of SciDAC 2007; Journal of Physics: Conference Series 78; Related Information: Article No. 012011
Country of Publication:
United States
Language:
English
Subject:
08 HYDROGEN; 59 BASIC BIOLOGICAL SCIENCES; 97 MATHEMATICS AND COMPUTING; ALGAE; BASIC; BIOLOGY; C CODES; CATALYSTS; CHLAMYDOMONAS; COMPARTMENTS; DIFFERENTIAL EQUATIONS; DNA; ENZYMES; FERMENTATION; GENES; GLYCOLYSIS; GRIDS; KINETICS; OPTIMIZATION; PHYSICS; SOLUTIONS; SPACE; TRANSFORMATIONS; Basic Sciences

Citation Formats

Chang, C., Alber, D., Graf, P., and Seibert, M. Addressing Unknown Constants and Metabolic Network Behaviors Through Petascale Computing: Understanding H2 Production in Green Algae. United States: N. p., 2007. Web. doi:10.1088/1742-6596/78/1/012011.
Chang, C., Alber, D., Graf, P., & Seibert, M. Addressing Unknown Constants and Metabolic Network Behaviors Through Petascale Computing: Understanding H2 Production in Green Algae. United States. doi:10.1088/1742-6596/78/1/012011.
Chang, C., Alber, D., Graf, P., and Seibert, M. Mon . "Addressing Unknown Constants and Metabolic Network Behaviors Through Petascale Computing: Understanding H2 Production in Green Algae". United States. doi:10.1088/1742-6596/78/1/012011.
@article{osti_982280,
title = {Addressing Unknown Constants and Metabolic Network Behaviors Through Petascale Computing: Understanding H2 Production in Green Algae},
author = {Chang, C. and Alber, D. and Graf, P. and Seibert, M.},
abstractNote = {The Genomics Revolution has resulted in a massive and growing quantity of whole-genome DNA sequences, which encode the metabolic catalysts necessary for life. However, gene annotations can rarely be complete, and measurement of the kinetic constants associated with the encoded enzymes can not possibly keep pace, necessitating the use of careful modeling to explore plausible network behaviors. Key challenges are (1) quantitatively formulating kinetic laws governing each transformation in a fixed model network; (2) characterizing the stable solution (if any) of the associated ordinary differential equations (ODEs); (3) fitting the latter to metabolomics data as it becomes available; and, (4) optimizing a model output against the possible space of kinetic parameters, with respect to properties such as robustness of network response, or maximum consumption/production. This SciDAC-2 project addresses this large-scale uncertainty in the genome-scale metabolic network of the water-splitting, H{sub 2}-producing green alga Chlamydomonas reinhardtii. Each metabolic transformation is formulated as an irreversible steady-state process, such that the vast literature on known enzyme mechanisms may be incorporated directly. To start, glycolysis, the tricarboxylic acid cycle, and basic fermentation pathways have been encoded in Systems Biology Markup Language (SBML) with careful annotation and consistency with the KEGG database, yielding a model with 3 compartments, 95 species, 38 reactions, and 109 kinetic constants. To study and optimize such models with a view toward larger models, we have developed a system which takes as input an SBML model, and automatically produces C code that when compiled and executed optimizes the model's kinetic parameters according to test criteria. We describe the system and present numerical results. Further development, including overlaying of a parallel multistart algorithm, will allow optimization of thousands of parameters on high-performance systems ranging from distributed grids to unified petascale architectures.},
doi = {10.1088/1742-6596/78/1/012011},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Mon Jan 01 00:00:00 EST 2007},
month = {Mon Jan 01 00:00:00 EST 2007}
}

Conference:
Other availability
Please see Document Availability for additional information on obtaining the full-text document. Library patrons may search WorldCat to identify libraries that hold this conference proceeding.

Save / Share:
  • Abstract not provided.
  • ne-sided communication is important to enable asynchronous communication and data movement for Global Address Space (GAS) programming models. Such communication is typically realized through direct messages between initiator and target processes. For petascale systems with 10,000s of nodes and 100,000s of cores, these direct messages require dedicated communication buffers and/or channels, which can lead to significant scalability challenges for GAS programming models. In this paper, we describe a network-friendly communication model, multinode cooperation, to enable indirect one-sided communication. Compute nodes work together to handle one-sided requests through (1) request forwarding in which one node can intercept a request and forwardmore » it to a target node, and (2) request aggregation in which one node can aggregate many requests to a target node. We have implemented multinode cooperation for a popular GAS runtime library, Aggregate Remote Memory Copy Interface (ARMCI). Our experimental results on a large-scale Cray XT5 system demonstrate that, multinode cooperation is able to greatly increase the memory scalability by reducing the number of communication buffers. In addition, multinode cooperation improves the resiliency of GAS runtime system to network contention. Furthermore, multinode cooperation can benefit the performance of scientific applications. In one case, it reduces the total execution time of an NWChem application by 52%.« less
  • ne-sided communication is important to enable asynchronous communication and data movement for Global Address Space (GAS) programming models. Such communication is typically realized through direct messages between initiator and target processes. For petascale systems with 10,000s of nodes and 100,000s of cores, these direct messages require dedicated communication buffers and/or channels, which can lead to significant scalability challenges for GAS programming models. In this paper, we describe a network-friendly communication model, multinode cooperation, to enable indirect one-sided communication. Compute nodes work together to handle one-sided requests through (1) request forwarding in which one node can intercept a request and forwardmore » it to a target node, and (2) request aggregation in which one node can aggregate many requests to a target node. We have implemented multinode cooperation for a popular GAS runtime library, Aggregate Remote Memory Copy Interface (ARMCI). Our experimental results on a large-scale Cray XT5 system demonstrate that, multinode cooperation is able to greatly increase the memory scalability by reducing the number of communication buffers. In addition, multinode cooperation improves the resiliency of GAS runtime system to network contention. Furthermore, multinode cooperation can benefit the performance of scientific applications. In one case, it reduces the total execution time of an NWChem application by 52%.« less
  • Safeguards demands have brought about the use of new, advanced equipment. These new systems are typically more complex than previous systems sometimes making use of dense circuitry and complex controls that can bring out previously unseen susceptibilities to various environmental conditions. In addition to possibly being susceptible to ambient conditions such as temperature and humidity, there may be a misunderstanding regarding the operational limitations of the equipment. Will a radiation detector respond to a moving source? Will other types of radiation overwhelm the response of the detector to the radiation of interest? Will the electronics survive or become incapacitated aftermore » exposure to radiation? These questions and others need to be addressed through the use of a systematic testing program. The program should not be used as a tool for criticism, but as a method of improving the reliability of equipment in the field and as a technique for improving the operation of the equipment. This document presents some of the information that was obtained at Oak Ridge National Laboratory where a series of tests were performed on various types of equipment with differing functions. Equipment tested included data transmission devices and radiation sensors. Tests performed included ionizing radiation to test for effects from interfering radiation and as a characterization tool for such things as response to moving sources. Other tests involved the use of non-ionizing radiation to determine whether interference could occur when equipment is exposed to radio frequency or magnetic field environments. The remaining tests were performed to establish whether susceptibilities exist when equipment is exposed to various temperature and humidity environments. Although more testing may be needed, the test methodologies used could provide a direction to future qualification plans.« less