high performance computing on graphics processing units: hgpu.org

Outlier detection (also known as anomaly detection) is a common data mining task in which data points that lie outside expected patterns in a given dataset are identified. This is useful in areas such as fault detection, intrusion detection and in pre-processing before further analysis. There are many approaches already in use for outlier detection, […]

Recently, in many important domains, high-level languages have become the code representations with widest platform support surpassing any low-level language in their area with respect to completeness and importance as exchange format (e.g. OpenCL for data-parallel computing, GLSL/HLSL for shader programs, JavaScript for the web). The code representations of many actively-developed compiler frameworks [JVM,LLVM,FIRM] are […]

Modern Graphical Processing Units (GPUs) can perform general purpose computing, next to standard graphical processing. Open frameworks, such as the OpenCL standard by the Khronos Group, enable developers to easily harness the computational power of GPUs. While in certain aspects, these are more powerful than standard CPUs, the latter are still a more suitable solution […]

SkePU is a C++ template library that provides a simple and unified interface for specifying data-parallel computations with the help of skeletons on GPUs using CUDA and OpenCL. The interface is also general enough to support other architectures, and SkePU implements both a sequential CPU and a parallel OpenMP backend. It also supports multi-GPU systems. […]

We explore a novel algorithm to analyze arbitrary distributions of 3D-points. Using a direct tensor field visualization technique allows to easily identify regions of linear, planar or isotropic structure. This approach is very suitable for visual data mining and exemplified upon geoscience applications. It allows to distinguish, for example, power lines and flat terrains in […]

This paper will report our evaluation to use openCL as a platform for hard realtime scheduling. Specifically, we have evaluated which types of tasks are faster on GPGPU than on CPU. We have investigated computational tasks, memory intensive tasks (especially tasks using low latency GDDR memory) and disk intensive tasks. This study is the first […]

Markov chains are a useful tool in statistics that allow us to sample and model a large population of individuals. We can extend this idea to the challenge of sampling solutions to problems. Using Markov chain Monte Carlo (MCMC) techniques we can also attempt to approximate the number of solutions with a certain confidence based […]

This thesis addresses the memory efficiency of general-purpose applications running on massively multi-threaded, data-parallel GPU architectures. Although scalable, data-parallel GPU architectures and their associated general-purpose programming models offer impressive computational capability and attractive power budgets, the pace of migrating general-purpose applications to this emerging class of architectures is significantly hindered by the efficiency of memory […]

Acceleration of cryptographic applications on massive parallel computing platforms, such as Graphic Processing Units (GPUs), becomes a real challenge concerning practical implementations. In this paper, we propose a parallel algorithm for Elliptic Curve (EC) point multiplication in order to compute EC cryptography on these platforms. The proposed approach relies on the usage of the Residue […]

The recent rise in the popularity of Graphics Processing Units (GPUs) has been fueled by software frameworks, such as NVIDIA’s Compute Unified Device Architecture (CUDA) and Khronos Group’s OpenCL that make GPUs available for general purpose computing. However, CUDA and OpenCL are still lowlevel approaches that require users to handle details about data layout and […]

Graphics processing units (GPU) have taken an important role in the general purpose computing market in recent years. At present, the common approach to programming GPU units is to write GPU specific code with low level GPU APIs such as CUDA. Although this approach can achieve good performance, it creates serious portability issues as programmers […]

Radiosity is a popular global illumination algorithm capable of achieving photorealistic rendering results. However, its use in interactive environments is limited by its computational complexity. This paper presents a GPGPU-based implementation of the gathering radiosity approach using texture-based discretisation and the OpenCL framework. Hemicubes are rendered to a texture array and processed by OpenCL kernels […]