high performance computing on graphics processing units: hgpu.org

Particle-in-cell (PIC) is a simulation technique for plasma physics. The large number of particles in highresolution plasma simulation increases the volume computation required, making it vital to increase computation speed. In this study, we attempt to accelerate computation speed on graphics processing units (GPUs) using KEMPO, a PIC simulation code package [H. Matsumoto and Y. […]

We fundamentally reconsider implementation of the Fast Multipole Method (FMM) on a computing node with a heterogeneous CPU-GPU architecture with multicore CPU(s) and one or more GPU accelerators, as well as on an interconnected cluster of such nodes. The FMM is a divide-and-conquer algorithm that performs a fast N-body sum using a spatial decomposition and […]

Magnetic Resonance Imaging (MRI) is a non-invasive and highly exible medical imaging modality that does not expose patients ionizing radiation. MR Image acquisitions can be designed by varying a large number of contrast-generation parameters, and many clinical diagnostic applications exist. However, imaging speed is a fundamental limitation to many potential applications. Traditionally, MRI data have […]

This paper discusses the experimental results of our visualization model for data extracted from sensors. The objective of this paper is to find a computationally efficient method to produce a real time rendering visualization for a large amount of data. We develop visualization method to monitor temperature variance of a data center. Sensors are placed […]

This paper introduces the ADVANCE approach to engineering concurrent systems using a new component-based approach. A cost-directed tool-chain maps concurrent programs onto emerging hardware architectures, where costs are expressed in terms of programmer annotations for the throughput, latency and jitter of components. These are then synthesized using advanced statistical analysis techniques to give overall cost […]

This document proposes an alternative method for the comparison of molecular electrostatic potential (MEP), based on parallel computing algorithms on graphics cards using NVIDIA CUDA platform and kernel methods for pattern recognition. The proposed solution optimizes the construction process of a particular representation of MEP, presents options for improving this representation, and offers 11 kernel […]

Global remote sensing and large-scale environmental modeling have generated huge amounts of raster geospatial data. While the inherent data parallelism of large-scale raster geospatial data allows straightforward coarse-grained parallelization at the chunk level on CPUs, it is largely unclear how to effectively exploit such data parallelism on massively parallel General Purpose Graphics Processing Units (GPGPUs) […]

We describe the use of Graphics Processing Units (GPUs) for speeding up the code NBODY 6 which is widely used for direct N-body simulations. Over the years, the N^2 nature of the direct force calculation has proved a barrier for extending the particle number. Following an early introduction of force polynomials and individual time-steps, the […]

Recent advances in deep learning have made the use of large, deep neural networks with tens of millions of parameters suitable for a number of applications that require real-time processing. The sheer size of these networks can represent a challenging computational burden, even for modern CPUs. For this reason, GPUs are routinely used instead to […]

This paper analyzed the efficient architecture features of massive terrain LOD visualization, and found that CPU can hardly select tiles from mass terrain effectively. This restricted the expansion of terrain’s size. Yacine Amara presented Tile Load Map(TLM). This paper presented Multilevel Tile Load Map (MTLM) algorithm for tile selection to extend TLM. MTLM uses 2d […]

In this paper, we introduce a GPU-based framework for simulating particle trajectories under both static and dynamic force fields. By exploiting the highly parallel nature of the problem and making efficient use of the available hardware, our simulator exhibits a significant speedup over its CPU-based analog. We apply our framework to a specific experimental simulation: […]

We used the Binomial Options Pricing Model (BOPM) implemented on a Graphics Processing Unit (GPU) to calculate the value of European and American options, of both put and call type. The advantage of using a GPU over a CPU is that a GPU has many more processing-cores than a CPU and can perform more calculations […]