Project Final Report: HPC-Colony II

This report recounts the HPC Colony II Project which was a computer science effort funded by DOE's Advanced Scientific Computing Research office. The project included researchers from ORNL, IBM, and the University of Illinois at Urbana-Champaign. The topic of the effort was adaptive system software for extreme scale parallel machines. A description of findings is included

GLB: Lifeline-based Global Load Balancing library in X10

We present GLB, a programming model and an associated implementation that can handle a wide range of irregular paral- lel programming problems running over large-scale distributed systems. GLB is applicable both to problems that are easily load-balanced via static scheduling and to problems that are hard to statically load balance. GLB hides the intricate syn- chronizations (e.g., inter-node communication, initialization and startup, load balancing, termination and result collection) from the users. GLB internally uses a version of the lifeline graph based work-stealing algorithm proposed by Saraswat et al. Users of GLB are simply required to write several pieces of sequential code that comply with the GLB interface. GLB then schedules and orchestrates the parallel execution of the code correctly and efficiently at scale. We have applied GLB to two representative benchmarks: Betweenness Centrality (BC) and Unbalanced Tree Search (UTS). Among them, BC can be statically load-balanced whereas UTS cannot. In either case, GLB scales well-- achieving nearly linear speedup on different computer architectures (Power, Blue Gene/Q, and K) -- up to 16K cores

Data decomposition of Monte Carlo particle transport simulations via tally servers

An algorithm for decomposing large tally data in Monte Carlo particle transport simulations is developed, analyzed, and implemented in a continuous-energy Monte Carlo code, OpenMC. The algorithm is based on a non-overlapping decomposition of compute nodes into tracking processors and tally servers. The former are used to simulate the movement of particles through the domain while the latter continuously receive and update tally data. A performance model for this approach is developed, suggesting that, for a range of parameters relevant to LWR analysis, the tally server algorithm should perform with minimal overhead on contemporary supercomputers. An implementation of the algorithm in OpenMC is then tested on the Intrepid and Titan supercomputers, supporting the key predictions of the model over a wide range of parameters. We thus conclude that the tally server algorithm is a successful approach to circumventing classical on-node memory constraints en route to unprecedentedly detailed Monte Carlo reactor simulations.United States. Dept. of Energy. Naval Reactors Division. Rickover Fellowship Program in Nuclear EngineeringUnited States. Dept. of Energy. Office of Advanced Scientific Computing Research (Contract DE-AC02-06CH11357)United States. Dept. of Energy (Consortium for Advanced Simulation of Light Water Reactors. Contract DE-AC05-00OR22725

Multi-core performance studies of a Monte Carlo neutron transport code

Performance results are presented for a multi-threaded version of the OpenMC Monte Carlo neutronics code using OpenMP in the context of nuclear reactor criticality calculations. Our main interest is production computing, and thus we limit our approach to threading strategies that both require reasonable levels of development effort and preserve the code features necessary for robust application to real-world reactor problems. Several approaches are developed and the results compared on several multi-core platforms using a popular reactor physics benchmark. A broad range of performance studies are distilled into a simple, consistent picture of the empirical performance characteristics of reactor Monte Carlo algorithms on current multi-core architectures.United States. Dept. of Energy. Office of Advanced Scientific Computing Research (Contract DEAC02-06CH11357