high performance computing on graphics processing units: hgpu.org

One of the major challenges faced by the HPC community today is user-friendly and accurate heterogeneous performance modeling. Although performance prediction models exist to fine-tune applications, they are seldom easy-to-use and do not address multiple levels of design space abstraction. Our research aims to bridge the gap between reliable performance model selection and user-friendly analysis. […]

This document summarizes our first experience with the Intel Xeon Phi. This is a coprocessor that uses Intel’s Many Integrated Core (MIC) architecture to speed up highly parallel processes involving intensive numerical computations. The MIC coprocessor communicates with a regular Intel Xeon ("host") processor through its operating system. The Xeon Phi coprocessor is sometimes referred […]

A novel technique for point rendering in a CUDA path tracer is introduced in this proposal. The approach makes it possible to render point represented geometries with global illumination effects. Octree data structure is combined in order for more efficient intersection determination. Furthermore, Octree enables the users/artists to choose the level of details of the […]

This paper presents an integrated analytical and profile-based cross-architecture performance modeling tool to specifically provide inter-architecture performance prediction for Sparse Matrix-Vector Multiplication (SpMV) on NVIDIA GPU architectures. To design and construct the tool, we investigate the inter-architecture relative performance for multiple SpMV kernels. For a sparse matrix, based on its SpMV kernel performance measured on […]

The Projected Spatial Rich Model (PSRM) generates powerful steganalysis features, but requires the calculation of tens of thousands of convolutions with image noise residuals. This makes it very slow: the reference implementation takes an impractical 20{30 minutes per 1 megapixel (Mpix) image. We present a case study which first tweaks the definition of the PSRM […]

Genetic Programming (GP) may dramatically increase the performance of software written by domain experts. GP and autotuning are used to optimise and refactor legacy GPGPU C code for modern parallel graphics hardware and software. Speed ups of more than six times on recent nVidia GPU cards are reported compared to the original kernel on the […]

With an aim to realizing highly accurate position estimation, we propose in this paper a method for efficiently and accurately detecting the 3D positions and poses of traditional fiducial markers with black frames in high-resolution images taken by ordinary web cameras. Our tracking method can be efficiently executed utilizing GPGPU computation, and in order to […]

Intel Many Integrated Core (MIC) Architecture combines about 60 cores onto a single chips. Intel MIC brand named Xeon Phi offers a theoretical maximum of more than 3 double precision GFLOPs than Intel Xeon E5 core. We carry out benchmarks for Intel MIC with a Monte Carlo simulation of LIBOR Market Model. The results show […]

The implementation of stencil computations on modern, massively parallel systems with GPUs and other accelerators currently relies on manually-tuned coding using low-level approaches like OpenCL and CUDA, which makes it a complex, time-consuming, and error-prone task. We describe how stencil computations can be programmed in our SkelCL approach that combines high level of programming abstraction […]

Graphics processing units (GPUs) are increasingly used for non-graphics computing. However, applications with divergent control flow incur performance degradation on current GPUs. These GPUs implement the SIMT execution model by serializing the execution of different control flow paths encountered by a warp. This serialization can mask thread level parallelism among the scalar threads comprising a […]

Recent developments in radiotherapy therapy demand high computation powers to solve challenging problems in a timely fashion in a clinical environment. The graphics processing unit (GPU), as an emerging high-performance computing platform, has been introduced to radiotherapy. It is particularly attractive due to its high computational power, small size, and low cost for facility deployment […]

Deformation of tissue can be accurately estimated from radio-frequency ultrasound data using a 2-dimensional normalized cross correlation (NCC)-based algorithm. This procedure, however, is very computationally time-consuming. A major time reduction can be achieved by parallelizing the numerous computations of NCC. In this paper, two approaches for parallelization have been investigated: the OpenMP interface on a […]