high performance computing on graphics processing units: hgpu.org

Intraoperative cardiac monitoring, accurate preoperative diagnosis, and surgical planning are important components of minimally-invasive cardiac therapy. Retrospective, electrocardiographically (ECG) gated, multidetector computed tomographical (MDCT), four-dimensional (3D + time), real-time, cardiac image visualization is an important tool for the surgeon in such procedure, particularly if the dynamic volumetric image can be registered to, and fused with […]

Graphics Processing Units (GPUs), originally developed for computer games, now provide computational power for scientific applications. In this paper, we develop a general purpose Lattice Boltzmann code that runs entirely on a single GPU. The results show that: (1) simple precision floating point arithmetic is sufficient for LBM computation in comparison to double precision; (2) […]

We demonstrate the use of highly parallel graphics processing units (GPUs) to accelerate the superposition/convolution (S/C) algorithm to interactive rates while reducing the number of approximations. S/C first transports the incident fluence to compute the total energy released per unit mass (TERMA) grid. Dose is then calculated by superimposing the dose deposition kernel at each […]

Ultrasound imaging is widely used in medical areas. By transmitting ultrasound signals into the human body, their echoed signals can be rendered to represent the shape of internal organs. Although its image quality is inferior to that of CT or MR, ultrasound is widely used for its speed and reasonable cost. Volume rendering techniques provide […]

We present a variational approach to jointly estimate a displacement map and a superresolution texture for a 3D model from multiple calibrated views. The superresolution image formation model leads to an energy functional defined in terms of an integral over the object surface. This functional can be minimized by alternately solving a deblurring PDE and […]

We can make smaller transistors, but we have a hard time making them run faster. Yet, the demand for computing power is growing. This challenge has led to a renewed interest in novel computing architectures that can take advantage of shrinking transistor size and deliver the necessary application performance improvements.

This paper proposed a multi-cue based face tracking algorithm with the help of parallel multi-core processing. Due to illumination and occlusion problems, face tracking usually does not work stably based on a single cue. Three different visual cues, color histogram, edge orientation histogram and wavelet feature, are integrated under the framework of particle filter to […]

We present a particle-based method for viscoelastic fluids simulation. In the method, based on the traditional Navier-Stokes equation, an additional elastic stress term is introduced to achieve viscoelastic flow behaviors, which have both fluid and solid features. Benefiting from the Lagrangian nature of Smoothed Particle Hydrodynamics, large flow deformation can be handled more easily and […]

The availability of high performance compute capability in NVIDIA GPUs has expanded their use in CAD environments. We will describe the basic compute models including host/device programming models, device multi-thread programming models, as well optimization and performance tuning techniques.

We present the implementation of a full electronic structure calculation code on a hybrid parallel architecture with graphic processing units (GPUs). This implementation is performed on a free software code based on Daubechies wavelets. Such code shows very good performances, systematic convergence properties, and an excellent efficiency on parallel computers. Our GPU-based acceleration fully preserves […]

While many models of biological object recognition share a common set of “broad-stroke” properties, the performance of any one model depends strongly on the choice of parameters in a particular instantiation of that model–e.g., the number of units per layer, the size of pooling kernels, exponents in normalization operations, etc. Since the number of such […]

Graphics Processor Units are used for many general purpose processing due to high compute power available on them. Regular, data-parallel algorithms map well to the SIMD architecture of current GPU. Irregular algorithms on discrete structures like graphs are harder to map to them. Efficient data-mapping primitives can play crucial role in mapping such algorithms onto […]