Leonardo Ram'irez-Guzm'an

From mesh generation to scientific visualization: an end-to-end approach to parallel supercomputing

Parallel supercomputing has traditionally focused on the inner kernel of scientific simulations: the solver. The front and back ends of the simulation pipeline - problem description and interpretation of the output - have taken a back seat to the solver when it comes to attention paid to scalability and performance, and are often relegated to offline, sequential computation. As the largest simulations move beyond the realm of the terascale and into the petascale, this decomposition in tasks and platforms becomes increasingly untenable. We propose an end-to-end approach in which all simulation components - meshing, partitioning, solver, and visualization - are tightly coupled and execute in parallel with shared data structures and no intermediate I/O. We present our implementation of this new approach in the context of octree-based finite element simulation of earthquake ground motion. Performance evaluation on up to 2048 processors demonstrates the ability of the end-to-end approach to overcome the scalability bottlenecks of the traditional approach

Model for Basin Effects on Long-Period Response Spectra in Southern California

We propose a model for the effect of sedimentary basin depth on long-period response spectra. The model is based on the analysis of 3-D numerical simulations (finite element and finite difference) of long-period (2–10 s) ground motions for a suite of sixty scenario earthquakes (Mw 6.3 to Mw 7.1) within the Los Angeles basin region. We find depth to the 1.5 km/s S-wave velocity isosurface to be a suitable predictor variable, and also present alternative versions of the model based on depths to the 1.0 and 2.5 km/s isosurfaces. The resulting mean basin-depth effect is period dependent, and both smoother (as a function of period and depth) and higher in amplitude than predictions from local 1-D models. The main requirement for the use of the results in construction of attenuation relationships is determining the extent to which the basin effect, as defined and quantified in this study, is already accounted for implicitly in existing attenuation relationships, through (1) departures of the average “rock” site from our idealized reference model, and (2) correlation of basin depth with other predictor variables (such as Vs30).

Remote runtime steering of integrated terascale simulation and visualization

We have developed a novel analytic capability for scientists and engineers to obtain insight from ongoing large-scale parallel unstructured mesh simulations running on thousands of processors. The breakthrough is made possible by a new approach that visualizes partial differential equation (PDE) solution data simultaneously while a parallel PDE solver executes. The solution field is pipelined directly to volume rendering, which is computed in parallel using the same processors that solve the PDE equations. Because our approach avoids the bottlenecks associated with transferring and storing large volumes of output data, it offers a promising approach to overcoming the challenges of visualization of petascale simulations. The submitted video demonstrates real-time on-the-fly monitoring, interpreting, and steering from a remote laptop computer of a 1024-processor simulation of the 1994 Northridge earthquake in Southern California.

BEMC: a searchable, compressed representation for large seismic wavefields

State-of-the-art numerical solvers in Earth Sciences produce multi terabyte datasets per execution. Operating on increasingly larger datasets becomes challenging due to insufficient data bandwidth. Queries result in difficult to handle I/O access patterns. BEMC is a new mechanism that allows querying and processing wavefields in the compressed representation. This approach combines well-known spatial-indexing techniques with novel compressed representations, thus reducing I/O bandwidth requirements. A new compression approach based on boundary integral representations exploits properties of the simulated domain. Frequency domain representation further compresses the data by eliminating temporal redundancy found in wave propagation data. This representation enables the transformation of a large I/O workload into a massively-parallel CPU-intensive computation. Queries to this representation result in largely sequential I/O accesses. Although, decompression places heavy demands on the CPU, it exhibits parallelism well-suited for many-core processors. We evaluate our approach in the context of data analysis for the Earth Sciences datasets.