Posts
Dec, 15
A GPU-based Approximate SVD Algorithm
Approximation of matrices using the Singular Value Decomposition (SVD) plays a central role in many science and engineering applications. However, the computation cost of an exact SVD is prohibitively high for very large matrices. In this paper, we describe a GPU-based approximate SVD algorithm for large matrices. Our method is based on the QUIC-SVD introduced […]
Dec, 15
GPU Algorithms for the Estimation of Environmental Models Based on Large Datasets
Statistical environmental models are computationally intensive due to the high dimension of the data, both in space and time, and due to the inferential techniques required for parameter estimation and spatial prediction. In particular, the complexity of these procedures is related to matrix operations (inversion, solution of linear systems, factorization) involving large matrices. Recently, much […]
Dec, 15
GPU Collision Detection in Conformal Geometric Space
We derive a conformal algebra treatment unifying all types of collisions among points, vectors, areas (defined by bivectors and trivectors) and 3D solid objects (defined by trivectors and quadvectors), based in a reformulation of collision queries from R^3 to conformal R^4,1 space. The algebraic formulation in this 5D space is then implemented in GPU to […]
Dec, 15
Performance in GPU Architectures: Potentials and Distances
GPUs can execute up to one TFLOPs at their peak performance. This peak performance, however, is rarely reached as a result of resource underutilization. Three parameters contribute to this inefficiency: branch divergence, memory access delays and limited workload parallelism. To this end we suggest machine models to estimate performance gain potentials obtainable by eliminating each […]
Dec, 15
Minimising Testing in Genetic Programming
The cost of optimisation can be reduced by evaluating candidate designs on only a fraction of all possible use cases. We show how genetic programming (GP) can avoid overfitting and evolve general solutions from fitness test suites as small as just one dynamic training case. Search effort can be greatly reduced.
Dec, 15
Free surface flow simulations on GPGPUs using the LBM
In this paper, we present the implementation of a volume-of-fluid-(VOF)-based algorithm for the simulation of free-surface flow problems on general purpose graphical processing units (GPGPUs). For the solution of the flow field and the additional advection equation for the VOF fill level, the lattice Boltzmann method on the basis of an MRT collision operator is […]
Dec, 15
Speed sign detection and recognition by convolutional neural networks
From the desire to update the maximum road speed data for navigation devices, a speed sign recognition and detection system is proposed. This system should prevent accidental speeding at roads where the map data is incorrect for example due to construction work. Multiple examples of road sign classification systems already exist but none uses a […]
Dec, 15
On the numerical solution of chaotic dynamical systems using extend precision floating point arithmetic and very high order numerical methods
Multiple results in the literature exist that indicate that all computed solutions to chaotic dynamical systems are time-step dependent. That is, solutions with small but different time steps will decouple from each other after a certain (small) finite amount of simulation time. When using double precision floating point arithmetic time step independent solutions have been […]
Dec, 14
Graph Generation on GPUs using Dynamic Memory Allocation
Complex networks are often studied using statistical measurements over many independently generated samples. Irregular data structures such as graphs that involve dynamical memory management and "pointer chasing" are an important class of application and have attracted recent interest in the form of the Graph500 benchmark formulation. The generation of simulated sample network graphs and measurement […]
Dec, 14
A Novel Multi-GPU Neural Simulator
Between the biophysical and behavioral studies of the brain lies computational neuroscience. The goal of which, among other things, is to help bridge the gap in our knowledge and provide alternative or complimentary theories to other neurological studies. As more information is provided and more complex theories are developed, the size and computational cost of […]
Dec, 14
Fast thermal simulation of 2D/3D integrated circuits exploiting neural networks and GPUs
Heat removal is one of the major challenges faced in developing the new generation of high density integrated circuits. Future design technologies strongly depend on the availability of efficient means for thermal modeling and analysis. These thermal models must be also accurate and provide the most efficient level of abstraction enabling fast execution. We propose […]
Dec, 14
Power consumption of mixed precision in the iterative solution of sparse linear systems
This paper presents a detailed analysis of a mixed precision iterative refinement solver applied to a linear system obtained from the 2D discretization of a fluid flow problem. The total execution time and energy need of different soft- and hardware implementations are measured and compared with those of a plain GMRES-based solver in double precision. […]
