high performance computing on graphics processing units: hgpu.org

Multi-scale manipulations are central to image editing but they are also prone to halos. Achieving artifact-free results requires sophisticated edgeaware techniques and careful parameter tuning. These shortcomings were recently addressed by the local Laplacian filters, which can achieve a broad range of effects using standard Laplacian pyramids. However, these filters are slow to evaluate and […]

We realized a real-time dual-mode standard/complex Fourier-domain optical coherence tomography (FD-OCT) system using graphics processing unit (GPU) accelerated 4D (3D+time) signal processing and visualization. For both standard and complex FD-OCT modes, the signal processing tasks were implemented on a dual-GPUs architecture that included lambda-to-k spectral re-sampling, fast Fourier transform (FFT), modified Hilbert transform, logarithmic-scaling, and […]

The GPU is an efficient accelerator for regular data-parallel workloads, but GPU acceleration is more difficult for graph algorithms and other applications with irregular memory access patterns and large memory footprints. The Minimum Spanning Tree (MST) problem arises in a variety of applications and its solution exemplifies the difficulties of mapping irregular algorithms to the […]

The growing need for power efficient extreme-scale highperformance computing (HPC) coupled with plateauing clock-speeds is driving the emergence of massively parallel compute architectures. Tens to many hundreds of cores are increasingly made available as compute units, either as the integral part of the main processor or as coprocessors designed for handling massively parallel workloads. In […]

Parallel computing is now an essential paradigm for high performance scientific computing. Most existing hardware and software solutions are expensive or difficult to use. We developed Playdoh, a Python library for distributing computations across the free computing units available in a small network of multicore computers. Playdoh supports independent and loosely coupled parallel problems such […]

In interactive volume rendering, the cost for rendering a certain block of the volume strongly varies with dynamically changing parameters (most notably the camera position and orientation). In distributed environments – wherein each compute device renders one block – this potentially causes severe load-imbalance. Balancing the load usually induces costly data transfers causing critical rendering […]

Development of multimedia systems on heterogeneous platforms is a challenging task with existing design tools due to a lack of rigorous integration between high level abstract modeling, and low level synthesis and analysis. In this paper, we present a new dataflow-based design tool, called the targeted dataflow interchange format (TDIF), for design, analysis, and implementation […]

GPGPU architectures (applications) have several different characteristics compared to traditional CPU architectures (applications): highly multithreaded architectures and SIMD-execution behavior are the two important characteristics of GPGPU computing. In this paper, we propose a potential function that models the DRAM behavior in GPGPU architectures and a DRAM scheduling policy, Alpha-SJF policy to minimize the potential function. […]

This work presents the application of parallel computing techniques using Graphic Processing Units to improve the efficiency of scheduling heuristics for heterogeneous computing systems. The experimental evaluation of the proposed methods demonstrates that a significant reduction on the computing times can be attained, allowing to tackle large scheduling scenarios in reasonable execution times.

The Finite-Difference Time-Domain (FDTD) solution of Maxwell’s equations, a grid-based differential time-domain numerical modeling method, is an approach for the direct modelling of the penetration of structures by continuous plane waves. Although FDTD techniques are considered to be relatively easy to understand and to implement in software, such modelling methods require a high level of […]

In this work, we explore heterogeneous computing hardware, including CPUs, GPUs and FPGAs, for scientific computing. We study system metrics such as throughput, energy efficiency and temperature, and formulate the problem of workload allocation among computing hardware in mathematical models with regards to the three metrics. The workload allocation approach is evaluated using Linpack on […]

Application demands and grand challenges in numerical simulation require for both highly capable computing platforms and efficient numerical solution schemes. Power constraints and further miniaturization of modern and future hardware give way for multi- and manycore processors with increasing fine-grained parallelism and deeply nested hierarchical memory systems — as already exemplified by recent graphics processing […]