Abstract We report initial experience with gas dynamics simulation on the Los Alamos Roadrunner machine. In this initial work, we have restricted our attention to flows in which the flow Mach number is less than 2. This permits us to use a simplified version of the PPM gas dynamics algorithm that has been described in detail by Woodward (2006). We follow a multifluid volume fraction using the PPB moment‐conserving advection scheme, enforcing both pressure and temperature equilibrium between two monatomic ideal gases within each grid cell. The resulting gas dynamics code has been extensively restructured for efficient multicore processing and implemented for scalable parallel execution on the Roadrunner system. The code restructuring and parallel implementation are described and performance results are discussed. For a modest grid size, sustained performance of 3.89 Gflops−1 CPU‐core−1 is delivered by this code on 36 Cell processors in 9 triblade nodes of a single rack of Roadrunner hardware. Copyright © 2009 John Wiley & Sons, Ltd.

According to today's best projections, petaFLOP/s computing platforms will combine deep memory hierarchies in both latency and bandwidth with a need for many-thousand-fold parallelism. Unless effective parallel programs are prepared in advance, much of the promise of the first year or two of operation for these systems may be lost. We introduce a candidate for a portable petaFLOP/s programming model that can enable these important early application programs to be developed while, at the same time, permitting these same applications to run efficiently on the most capable computing systems now available. An MPI-based model is portable, but its programming paradigm ignores the potential benefits of hardware support for shared memory within each network node. A threads-based model cannot directly cope with the distributed nature of the memory over the network. Therefore, a new, portable programming model is needed. The shared memory programming model dramatically simplifies the expression of dynamic load balancing strategies for irregular algorithms. The main strategy is a transparent self-scheduled task list performed in parallel so long as specified data-dependent conditions are met. The model used is a cluster of multiprocessor distributed shared memory machines with network-attached disks. Our experimental run-time system allows the programmer to view this computing platform as a single machine with a four-stage memory hierarchy, consisting of coherent processor cache, non-coherent local shared memory, global shared memory, plus a global disk file system.

Understanding turbulence and mix in compressible flows is of fundamental importance to real-world applications such as chemical combustion and supernova evolution.The ability to run in three dimensions and at very high resolution is required for the simulation to accurately represent the interaction of the various length scales, and consequently, the reactivity of the intermixing species.Toward this end, we have carried out a very high resolution (over 8 billion zones) 3-D simulation of the Richtmyer-Meshkov instability and turbulent mixing on the IBM Sustained Stewardship TeraOp (SST) system, developed under the auspices of the Department of Energy (DOE) Accelerated Strategic Computing Initiative (ASCI) and located at Lawrence Livermore National Laboratory.We have also undertaken an even higher resolution proofof-principle calculation (over 24 billion zones) on 5832 processors of the IBM system, which executed for over an hour at a sustained rate of 1.05 Tflop/s, as well as a short calculation with a modified algorithm that achieved a sustained rate of 1.18 Tflop/s.The full production scientific simulation, using a further modified algorithm, ran for 27,000 timesteps in slightly over a week of wall time using 3840 processors of the IBM system, clocking a sustained throughput of roughly 0.6 teraflop per second (32-bit arithmetic).Nearly 300,000 graphics files comprising over three terabytes of data were produced and post-processed.The capability of running in 3-D at high resolution enabled us to get a more accurate and detailed picture of the fluidflow structure -in particular, to simulate the development of fine scale structures from the interactions of long-and short-wavelength phenomena, to elucidate differences between twodimensional and three-dimensional turbulence, to explore a conjecture regarding the transition from unstable flow to fully developed turbulence with increasing Reynolds number, and to ascertain convergence of the computed solution with respect to mesh resolution.