Hello, A yearly allocation for the LCRC cluster has been requested with the following updated information: Submitter/PI: Michael Borland Project Name: ApsRenewalLattice Division: ASD Project title: Lattice Development and Beam Dynamics for APS Upgrade Associated funding: Department of Energy,Office of Science, Office of Basic Energy Sciences Other Systems: ASD "weed" cluster, operated by ASD/AOP group. weed has 56 Nehelem processors with a lustre filesystem and infiniband network. I typically have access to about 50% of the cluster full time. Science: As part of the APS Upgrade, the accelerator lattice (the location and powering of the magnets) may be completed replaced with a multi-bend achromat (MBA) configuration. This configuration promises dramatically lower emittance and dramatically higher x-ray brightness. If successful, it would make APS the brightest storage ring hard x-ray source in the world. The goal of this project is to design and validate an MBA lattice suitable for incorporation into the APS Upgrade. Project description: APS has developed a method of using multi-objective genetic algorithms (MOGA) for optimization of accelerator lattices. In past years, this method has been applied successfully using blues, fusion, intrepid, and a small APS cluster to development and evaluation of lattices for the APS Upgrade. In the coming year, we will contniue working on a multi-bend achromat (MBA) lattice design that promises to push APS x-ray brightness to world-leading levels. Significant progress has already been made and the results are used in on-going discussions of the project with DOE. Our approach is to create a series of lattices that gradually push performance up while simultaneously incorporating on-going constraints derived from on-going interactions with magnet and vacuum system designers. As such, the process is naturally iterative, and we have completed a series of iterations to date to conform to engineering limits. Further iterations are on-going, with interest in reducing cost also being relevant. In addition to MOGA, we will perform ensemble evaluation to assess the robustness of solutions and evaluate effects of insertion devices on the newly-developed solutions. A major review is anticipated in the second quarter of FY15. The codes being used for MOGA and ensemble evaluation have all been used in past years on fusion. These include Pelegant, a parallel accelerator simulation code used primarily for particle tracking and acceptance determination, as well as a Tcl script used for genetic optimization. The simulations are close to embarrassingly parallel and thus scale very well. In late FY14, we began a new effort to model the effects of the higher harmonic cavity (HHC), which plays a vital role in increasing the beam lifetime and reducing emittance blow-up. The simulations involve tracking beams consisting of 48 or more bunches of 100,000 or more particles each, and computing the collective electromagnetic interaction of these particles with the vacuum chamber and rf cavities. The code was optimized to improve efficiency, with 70% efficiency obtained on 256 cores for a "small" problem consisting of 48 bunches with 100,000 particles each. Efficiency increases for larger problems as computation increasingly dominates inter-process communication. These efforts will continue into FY15 and require significant disk space. Industry partnership: Project URL: Current FY Hours Used: undetermined amount New FY Requested allocation: 10000000 Q1: 3000000 Q2: 3000000 Q3: 2000000 Q4: 2000000 Justification: The code is already running efficiently on Blues. Scaling is very good for MOGA and ensemble evaluation because the code is close to embarrassingly parallel. The MOGA script runs many simultaneous, unconnected jobs, each using 2 nodes. Because each job uses only 32 cores, scaling is not relevant. Jobs are sized to take advantage of the number of cores provided, e.g., by tracking n*32 particles so that each core has an approximately equal workload. Efficiency for collective effect tracking was found to be good (>70%) for up to 256 cores for a small problem, and increases with problem size. Storage requirements: 3 TB, needed for storage of large data files generated by collective effects simulation. Thank You, The LCRC Accounts System