This paper presents and characterizes the Princeton Application Repository for Shared-Memory Computers (PARSEC), a benchmark suite for studies of Chip-Multiprocessors (CMPs). Previous available benchmarks for multiprocessors have focused on high-performance computing applications and used a limited number of synchronization methods. PARSEC includes emerging applications in recognition, mining and synthesis (RMS) as well as systems applications which mimic large-scale multithreaded commercial programs. Our characterization shows that the benchmark suite covers a wide spectrum of working sets, locality, data sharing, synchronization and off-chip traffic. The benchmark suite has been made available to the public.

We built an anatomically accurate model of facial musculature, passive tissue and underlying skeletal structure using volumetric data acquired from a living male subject. The tissues are endowed with a highly nonlinear constitutive model including controllable anisotropic muscle activations based on fiber directions. Detailed models of this sort can be difficult to animate requiring complex coordinated stimulation of the underlying musculature. We propose a solution to this problem automatically determining muscle activations that track a sparse set of surface landmarks, e.g. acquired from motion capture marker data. Since the resulting animation is obtained via a three dimensional nonlinear finite element method, we obtain visually plausible and anatomically correct deformations with spatial and temporal coherence that provides robustness against outliers in the motion capture data. Moreover, the obtained muscle activations can be used in a robust simulation framework including contact and collision of the face with external objects.

Enveloping, or the mapping of skeletal controls to the deformations of a surface, is key to driving realistic animated characters. Despite its widespread use, enveloping still relies on slow or inaccurate deformation methods. We propose a method that is both fast, accurate and example-based. Our technique introduces a rotational regression model that captures common skinning deformations such as muscle bulging, twisting, and challenging areas such as the shoulders. Our improved treatment of rotational quantities is made practical by model reduction that ensures real-time solution of leastsquares problems, independent of the mesh size. Our method is significantly more accurate than linear blend skinning and almost as fast, suggesting its use as a replacement for linear blend skinning when examples are available.

We present a physically based system for creating animations of novel words and phrases from text and audio input based on the analysis of motion captured speech examples. Leading image based techniques exhibit photo-real quality, yet lack versatility especially with regard to interactions with the environment. Data driven approaches that use motion capture to deform a three dimensional surface often lack any anatomical or physically based structure, limiting their accuracy and realism. In contrast, muscle driven physics-based facial animation systems can trivially integrate external interacting objects and have the potential to produce very realistic animations as long as the underlying model and simulation framework are faithful to the anatomy of the face and the physics of facial tissue deformation. We start with a high resolution, anatomically accurate flesh and muscle model built for a specific subject. Then we translate a motion captured training set of speech examples into muscle activation signals, and subsequently segment those into intervals corresponding to individual phonemes. Finally, these samples are used to synthesize novel words and phrases. The versatility of our approach is illustrated by combining this novel speech content with various facial expressions, as well as interactions with external objects.

We present an efficient algorithm for simulating contacts between deformable bodies with high-resolution surface geometry using dynamic deformation textures, which reformulate the 3D elastoplastic deformation and collision handling on a 2D parametric atlas to reduce the extremely high number of degrees of freedom in such a computationally demanding simulation. We perform proximity queries for deformable bodies using a two-stage algorithm directly on dynamic deformation textures, resulting in output-sensitive collision detection that is independent of the combinatorial complexity of the deforming meshes. We present a robust, parallelizable formulation for computing constraint forces using implicit methods that exploits the structure of the motion equations to achieve highly stable simulation, while taking large time steps with inhomogeneous materials. The dynamic deformation textures can also be used directly for real-time shading and can easily be implemented using SIMD architecture on commodity hardware. We show that our approach, complementing existing pioneering work, offers significant computational advantages on challenging contact scenarios in dynamic simulation of deformable bodies. 1.

We explore the emerging application area of physics-based simulation for computer animation and visual special effects. In particular, we examine its parallelization potential and characterize its behavior on a chip multiprocessor (CMP). Applications in this domain model and simulate natural phenomena, and often direct visual components of motion pictures. We study a set of three workloads that exemplify the span and complexity of physical simulation applications used in a production environment: fluid dynamics, facial animation, and cloth simulation. They are computationally demanding, requiring from a few seconds to several minutes to simulate a single frame; therefore, they can benefit greatly from the acceleration possible with large scale CMPs. Starting with serial versions of these applications, we parallelize code accounting for at least 96 % of the serial execution time, targeting a large number of threads. We then study the most expensive modules using a simulated 64-core CMP. For the code in key modules, we achieve parallel scaling of 45x, 50x, and 30x for fluid, face, and cloth simulations, respectively. The modules have a spectrum of task granularity and locking behavior, and all but one are dominated by loop-level parallelism. Many modules operate on streams of data. In some cases, modules iterate over their data, leading to significant temporal locality. This streaming behavior leads to very high on-die and main memory bandwidth requirements. Finally, most modules have little inter-thread communication since they are data-parallel, but a few require heavy communication between data-parallel operations.

We propose a novel approach to fracturing (and denting) brittle materials. To avoid the computational burden imposed by the stringent time step restrictions of explicit methods or with solving nonlinear systems of equations for implicit methods, we treat the material as a fully rigid body in the limit of infinite stiffness. In addition to a triangulated surface mesh and level set volume for collisions, each rigid body is outfitted with a tetrahedral mesh upon which finite element analysis can be carried out to provide a stress map for fracture criteria. We demonstrate that the commonly used stress criteria can lead to arbitrary fracture (especially for stiff materials) and instead propose the notion of a time averaged stress directly into the FEM analysis. When objects fracture, the virtual node algorithm provides new triangle and tetrahedral meshes in a straightforward and robust fashion. Although each new rigid body can be rasterized to obtain a new level set, small shards can be difficult to accurately resolve. Therefore, we propose a novel collision handling technique for treating both rigid bodies and rigid body thin shells represented by only a triangle mesh.

Abstract—Real-time evaluation of distributed contact forces between rigid or deformable 3D objects is a key ingredient of 6-DoF force-feedback rendering. Unfortunately, at very high temporal rates, there is often insufficient time to resolve contact between geometrically complex objects. We propose a spatially and temporally adaptive approach to approximate distributed contact forces under hard real-time constraints. Our method is CPU-based and supports contact between rigid or reduced deformable models with complex geometry. We propose a contact model that uses a point-based representation for one object and a signed-distance field for the other. This model is related to the Voxmap-PointShell (VPS) method, but gives continuous contact forces and torques, enabling stable rendering of stiff penalty-based distributed contacts. We demonstrate that stable haptic interactions can be achieved by point-sampling offset surfaces to input “polygon soup ” geometry using particle repulsion. We introduce a multiresolution nested pointshell construction that permits level-of-detail contact forces and enables graceful degradation of contact in close-proximity scenarios. Parametrically deformed distance fields are proposed for contact between reduced deformable objects. We present several examples of 6-DoF haptic rendering of geometrically complex rigid and deformable objects in distributed contact at real-time kilohertz rates.

Finite element simulations of nonlinear deformable models are computationally costly, routinely taking hours or days to compute the motion of detailed meshes. Dimensional model reduction can make simulations orders of magnitude faster, but is unsuitable for general deformable body simulations because it requires expensive precomputations, and it can suppress motion that lies outside the span of a pre-specified low-rank basis. We present an online model reduction method that does not have these limitations. In lieu of precomputation, we analyze the motion of the full model as the simulation progresses, incrementally building a reduced-order nonlinear model, and detecting when our reduced model is capable of performing the next timestep. For these subspace steps, full-model computation is “skipped ” and replaced with a very fast (on the order of milliseconds) reduced order step. We present algorithms for both dynamic and quasistatic simulations, and a “throttle ” parameter that allows a user to trade off between faster, approximate previews and slower, more conservative results. For detailed meshes undergoing low-rank motion, we have observed speedups of over an order of magnitude with our method.

Figure 1: The biomechanical model in action. A motion controller drives the musculoskeletal system toward a sequence of target poses. We introduce a comprehensive biomechanical model of the human upper body. Our model confronts the combined challenge of modeling and controlling more or less all of the relevant articular bones and muscles, as well as simulating the physics-based deformations of the soft tissues. Its dynamic skeleton comprises 68 bones with 147 jointed degrees of freedom, including those of each vertebra and most of the ribs. To be properly actuated and controlled, the skeletal submodel requires comparable attention to detail with respect to muscle modeling. We incorporate 814 muscles, each of which is modeled as a piecewise uniaxial Hill-type force actuator. To simulate biomechanically realistic flesh deformations, we also develop a coupled finite element model with the appropriate constitutive behavior, in which are embedded the detailed 3D anatomical geometries of the hard and soft tissues. Finally, we develop an associated physics-based animation controller that computes the muscle activation signals necessary to drive the elaborate musculoskeletal system in accordance with a sequence of target poses specified by an animator.