DATA MANAGEMENT ENVIRONMENT FOR MULTI SCALE BIOLOGICAL MODELING

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This project is developing efficient and stable implementations of the AMBER molecular modeling package on parallel machines for use at SDSC. There are two general aspects to the proposed research: a fine-grained implementation of the molecular dynamics and minimization algorithms, followed by a more coarse-grained parallelization of free energy calculations. A new direction in the past year is the parallelization of the particle-mesh Ewald code, along with further improvements in other areas. A major test case involving a 60,000 atom system is in progress. We use the Message Passing Interface (MPI) programming model developed at Argonne Labs for our basic MD implementation. Most vendors, including Intel, IBM, and Cray/SGI now support MPI. We now have (nearly) identical parallel code on clusters of workstations and on MPP machines like the Cray T3E, IBM's SP1 and SP2 machines, and the Convex Exemplar SPP. The MPI implementation is now a standard part of version 5.0 of AMBER, making it available to workers throughout the world. The code development has been a collaborative effort, involving primarily John Vincent and Ken Merz (PSU), Tom Cheatham and Peter Kollman (UCSF), David Case (TSRI), and Jerry Greenberg and Jack Rogers (SDSC). The release of Amber 5.1 is now being prepared and is expected in fall, 1998. This release will be coordinated by D.A. Case. Key parallel improvements that are now in final testing include: * Greatly improved parallel implementation of particle-mesh Ewald code; * Fully parallel implementation of free energy perturbation codes * Parallel implementation of "locally-enhanced sampling", a multiple-copies approach to dynamics * Parallel implementation of NMR restraints for structure refinement Goals for the coming year include: (1) tuning of the communication steps to achieve performance more like that expected on theoretical grounds; (2) additional production calculations (of DNA + salt + water) to test and illustrate the use of the new codes; (3) adapting coarse-grained parallel algorithms for free energy calculations.