high performance computing on graphics processing units: hgpu.org

This paper introduces an Enhanced Multi Objective Genetic Algorithm (E-MOGA) running on Compute Unified Device Architecture (CUDA) hardware, as a general purpose tool that can solve conflict optimization problems. The tool demonstrates significant speed gains using affordable, scalable and commercially available hardware. The objectives of this research are: to enhance the general purpose Multi Objective […]

The challenges and benefits of using the GPU to compute solutions to Lambert’s Problem are discussed. Three algorithms (Universal Variables, Gooding’s algorithm, and Izzo’s algorithm) were adapted for GPU computation directly within MATLAB. The robustness of each algorithm was considered, along with the speed at which it could be computed on each of three computers. […]

Modern GPU architectures closely resemble supercomputers. Commodity GPUs that have already been equipped with personal and cluster computers can be used to boost the performance of spatial databases and GIS. In this study, we report our preliminary work on designing and implementing a spatial join algorithm on GPUs by using generic parallel primitives that have […]

Efficient lookups in huge, possibly multi-dimensional datasets are crucial for the performance of numerous use cases that generate multiple search operations at the same time, like point queries in ray tracing or spatial joins in collision detection of interactive 3D applications. These applications greatly benefit from index structures that quickly filter relevant candidates for further […]

In the last few years, Graphics Processing Units (GPUs) have become a great tool for massively parallel computing. GPUs are specifically designed for throughput and face several design challenges, specially what is known as the Power and Memory Walls. In these devices, available resources should be used to enhance performance and throughput, as the performance […]

SystemC is a widespread language for HW/SW system simulation and design exploration, and thus a key development platform in embedded system design. However, the growing complexity of SoC designs is having an impact on simulation performance, leading to limited SoC exploration potential, which in turns affects development and verification schedules and time-to-market for new designs. […]

Conjugate gradient is an important iterative method used for solving least squares problems. It is compute-bound and generally involves only simple matrix computations. One would expect that we could fully parallelize such computation on the GPU architecture with multiple Stream Multiprocessors (SMs), each consisting of many SIMD processing units. While implementing a conjugate gradient method […]

We present an investigation of the use of GPGPU techniques to parallelize the execution of a satisfiability solver, based on the traditional DPLL procedure – which, in spite of its simplicity, still represents the core of the most competitive solvers. The investigation tackles some interesting problems, including the use of a predominantly data-parallel architecture, like […]

High level productivity languages such as Python or Matlab enable the use of computational resources by nonexpert programmers. However, these languages often sacrifice program speed for ease of use. This paper proposes Parakeet, a library which provides a just-in-time (JIT) parallel accelerator for Python. Parakeet bridges the gap between the usability of Python and the […]

The NVIDIA graphics processing units (GPUs) are playing an important role as general purpose programming devices. The implementation of parallel codes to exploit the GPU hardware architecture is a task for experienced programmers. The threadblock size and shape choice is one of the most important user decisions when a parallel problem is coded. The threadblock […]

To date, the GPGPU approach has been mainly utilized for academic and scientific computing, for example, for genetic algorithms, image analysis, cryptography, or password cracking. Though video cards supporting GPGPU have become pervasive, there do not appear to be any applications utilizing GPGPU for a household user. In this paper, one consumer application for GPGPU […]

HPC systems now exploit GPUs within their compute nodes to accelerate program performance. As a result, high-end application development has become extremely complex at the node level. In addition to restructuring the node code to exploit the cores and specialized devices, the programmer may need to choose a programming model such as OpenMP or CPU […]