MCELL SIMULATIONS OF NEURAL MODELS USING APST

Carnegie-Mellon University, Pittsburgh PA

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Abstract

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. In order to analyze the microscopic structure of brain tissue, researchers are using Monte Carlo simulations. One of the most successful is MCell, a general Monte Carlo simulator of cellular microphysiology developed by Tom Bartol and Joel Stiles when they were at Cornell University (with Ed Salpeter, and the late Miriam Salpeter). Bartol and Stiles are now at the Salk Institute and the Pittsburgh Supercomputing Center, respectively. MCell produces highly realistic 3-D simulations of subcellular architecture and physiology, allowing unexplored aspects of neural signaling to be quantitatively modeled. Together with partners at UC San Diego (UCSD) and the University of Tennessee, participants in this alpha project have made significant progress toward providing a grid-enabled version of MCell that can handle much larger, more realistic data sets than previously possible. MCell researchers have been limited by the lack of adequate computational infrastructure and the ability to use it to accommodate large-scale simulations as well as to navigate and map large parameter spaces. Key limiting factors include the ability to efficiently access remote computational, storage, and federated database resources, the ability to schedule the application so as to exploit fluctuating deliverable resource performance, and the ability to manage distributed and heterogeneous resources within a unified, service-oriented framework. MCell is representative of a large class of NPACI metasystem applications which, through NPACKage, can now leverage NPACI and other Grid resources for large runs -- a feat which previously could only be accomplished with considerable difficulty. There are three typical scenarios for use of MCell: Small scale usage on typical workstations or small clusters of workstations. Large-scale parameter sweep usage in a metacomputing environment. This is accomplished using MCell with APST. Single large-scale simulations on massively parallel supercomputers such as BlueHorizon. This is accomplished using MCell with KeLP, called MCell-K. APST is a Grid application execution environment that performs automatic scheduling and deployment of "parameter sweep" applications, that is applications consisting of large sets of independent computational tasks with potentially large datasets. MCell belongs to this class of applications. APST interfaces to several middleware infrastructures to launch and monitor computation on a wide variety of Grid resources, to move data among Grid storage resources, and to gather information about the status of the Grid platform. APST uses sophisticated scheduling algorithms that take into account the cost of data movements when scheduling computation. APST provides MCell users with transparent access to local and NPACI resources, shielding the user, to a large degree, from the vast array of authentication, storage, and queuing systems to be encountered.