high performance computing on graphics processing units: hgpu.org

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 […]

Global Illumination aims to generate high quality images. But due to its high requirements, it is usually quite slow. Research documented in this thesis was intended to offer a hardware and software combined acceleration solution to global illumination. The GPU (using CUDA) was the hardware part of the whole method that applied parallelism to increase […]

Given a collection of documents residing on a disk, we develop a new strategy for processing these documents and building the inverted files extremely fast. Our approach is tailored for a heterogeneous platform consisting of a multicore CPU and a highly multithreaded GPU. Our algorithm is based on a number of novel techniques including: (i) […]

In this paper, we present an approach for efficiently monitoring multiple data streams using graphic processor units (GPUs). Given reference patterns, similar subsequences in streams are matched under the dynamic time warping (DTW) distance and reported continuously. DTW distance is adopted since it offers scaling and shifting exibility in the time axis. However, it suffers […]