SIGGRAPH 2016

SIGGRAPH 2016 papers:

 

TOG presentations at SIGGRAPH 2016:

Ebb: A DSL for Physical Simulation on CPUs and GPUs

Gilbert Bernstein, Chinmayee Shah, Crystal Lemire, Zachery DeVito, Matthew Fisher, Philip Levis, Pat Hanrahan

Designing programming environments for physical simulation is challenging because simulations rely on diverse algorithms and geometric domains. These challenges are compounded when we try to run efficiently on heterogeneous parallel architectures. We present Ebb, a domain-specific language (DSL) for simulation, that runs efficiently on both CPUs and GPUs. Unlike previous DSLs, Ebb uses a three-layer architecture to separate (1) simulation code, (2) definition of data structures for geometric domains, and (3) runtimes supporting parallel architectures. Different geometric domains are implemented as libraries that use a common, unified, relational data model. By structuring the simulation framework in this way, programmers implementing simulations can focus on the physics and algorithms for each simulation without worrying about their implementation on parallel computers. Because the geometric domain libraries are all implemented using a common runtime based on relations, new geometric domains can be added as needed, without specifying the details of memory management, mapping to different parallel architectures, or having to expand the runtime’s interface. We evaluate Ebb by comparing it to several widely used simulations, demonstrating comparable performance to hand-written GPU code where available, and surpassing existing CPU performance optimizations by up to 9x when no GPU code exists.

Ebb: A DSL for Physical Simulation on CPUs and GPUs

Boundary detection in particle-based fluids

Marcos Sandim, Douglas Cedrim, Luis Gustavo Nonato, Paulo Pagliosa, and Afonso Paiva

This paper presents a novel method to detect free-surfaces on particle-based volume representation. In contrast to most particle-based free-surface detection methods, which perform the surface identification based on physical and geometrical properties derived from the underlying fluid flow simulation, the proposed approach only demands the spatial location of the particles to properly recognize surface particles, avoiding even the use of kernels. Boundary particles are identified through a Hidden Point Removal (HPR) operator used for visibility test. Our method is very simple, fast, easy to implement and robust to changes in the distribution of particles, even when facing large deformation of the free-surface. A set of comparisons against state-of-the-art boundary detection methods show the effectiveness of our approach. The good performance of our method is also attested in the context of fluid flow simulation involving free-surface, mainly when using level-sets for rendering purposes.

Boundary detection in particle-based fluids