Learn More
Sparse matrix-vector multiplication (SpMV) is of singular importance in sparse linear algebra. In contrast to the uniform regularity of dense linear algebra, sparse operations encounter a broad spectrum of matrices ranging from the regular to the highly irregular. Harnessing the tremendous potential of throughput-oriented processors for sparse operations(More)
Algebraic multigrid methods for large, sparse linear systems are a necessity in many computational simulations, yet parallel algorithms for such solvers are generally decomposed into coarse-grained tasks suitable for distributed computers with traditional processing cores. However, accelerating multigrid methods on massively parallel throughput-oriented(More)
Granular materials, such as sand and grains, are ubiquitous. Simulating the 3D dynamic motion of such materials represents a challenging problem in graphics because of their unique physical properties. In this paper we present a simple and effective method for granular material simulation. By incorporating techniques from physical models, our approach(More)
In this paper, we present a multigrid technique for efficiently deforming large surface and volume meshes. We show that a previous least-squares formulation for distortion minimization reduces to a Laplacian system on a general graph structure for which we derive an analytic expression. We then describe an efficient multigrid algorithm for solving the(More)
Sparse matrix--matrix multiplication (SpGEMM) is a key operation in numerous areas from information to the physical sciences. Implementing SpGEMM efficiently on throughput-oriented processors, such as the graphics processing unit (GPU), requires the programmer to expose substantial fine-grained parallelism while conserving the limited off-chip memory(More)
Gestalt imagery-the ability to create imaged wholes-is a critical factor in oral and written language comprehension. Despite good decoding, good vocabulary, and adequate background experiences, many individuals experience weak gestalt imagery, thus processing "parts" rather than "wholes," from verbal stimuli, spoken or written. This contributes to a(More)
This article describes the algorithms, features, and implementation of PyDEC, a Python library for computations related to the discretization of exterior calculus. PyDEC facilitates inquiry into both physical problems on manifolds as well as purely topological problems on abstract complexes. We describe efficient algorithms for constructing the operators(More)
In this paper we describe an aggregation-based algebraic multigrid method for the solution of discrete k-form Laplacians. Our work generalizes Reitzinger and Schöberl’s algorithm to higher-dimensional discrete forms. We provide conditions on the tentative prolongators under which the commutativity of the coarse and fine de Rham complexes is maintained.(More)
Awareness of the internal phonological structure of words is a causal factor in success with the alphabetic principle in word recognition. However, findings with the Lindamood Auditory Conceptualization (LAC) Test reveal 25-30% of the population show deficiency in a subtle component of phonological awareness termed comparator function. We argue that this(More)