high performance computing on graphics processing units: hgpu.org

Simulation and visualization of particles in real-time can be a computationally intensive task. This intensity comes from diverse factories, being one of them is the O(n^2) complexity of the traversal algorithm, necessary for the proximity queries of all pair of particles that decide the need to compute collisions. Previous works reduced this complexity by considerably […]

Branch-and-Bound (B&B) is a general problem solving paradigm and it has been successfully used to prove the optimality of combinatorial optimization problems. The development of GPU-based parallel Branch-and-Bound algorithm is a brandnew and challenging topic on high performance computing and combinatorial optimization, motivated by GPU’s high performance and low cost. This work presents a strategy […]

Spectral unmixing amounts at automatically finding the signatures of pure spectral components (called endmembersin the hyperspectral imaging literature) and their associated abundance fractions in each pixel of the hyperspectral image. Many algorithms have been proposed to automatically find spectral endmembers in hyperspectral data sets. Perhaps one of the most popular ones is the pixel purity […]

We introduce GRay, a massively parallel integrator designed to trace the trajectories of billions of photons in a curved spacetime. This GPU-based integrator employs the stream processing paradigm, is implemented in CUDA C/C++, and runs on nVidia graphics cards. The peak performance of GRay using single precision floating-point arithmetic on a single GPU exceeds 300 […]

Graphics processors, or GPUs, have recently been widely used as accelerators in the shared environments such as clusters and clouds. In such shared environments, many kernels are submitted to GPUs from different users, and throughput is an important metric for performance and total ownership cost. Despite the recently improved runtime support for concurrent GPU kernel […]

The integral histogram for images is an efficient preprocessing method for speeding up diverse computer vision algorithms including object detection, appearance-based tracking, recognition and segmentation. Our proposed Graphics Processing Unit (GPU) implementation uses parallel prefix sums on row and column histograms in a cross-weave scan with high GPU utilization and communication-aware data transfer between CPU […]

In recent years the use of graphical processing units (GPUs) in the diverse fields of science has increase dramatically. This increase is not only due to the GPU tremendous computational power, but also because they are relatively cheap when compared to clusters. In this work we explore the use of the GPU to reduce the […]

It has often been claimed that SBSE uses so-called "embarrassingly parallel" algorithms that will imbue SBSE applications with easy routes to dramatic performance improvements. However, despite recent advances in multicore computation, this claim remains largely theoretical; there are few reports of performance improvements using multicore SBSE. This paper shows how inexpensive General Purpose computing on […]

With the ever increasing volume of data and the ability to integrate different data sources, data quality problems abound. Duplicate detection, as an integral part of data cleansing, is essential in modern information systems. We present a complete duplicate detection workflow that utilizes the capabilities of modern graphics processing units (GPUs) to increase the efficiency […]

The window-based stream join is an important operator in all data streaming systems. It has often high resource requirements so that many efficient sequential as well as parallel versions of it were proposed in the literature. The parallel stream join operators recently gain increasing interest because hardware is getting more and more parallel. Most of […]

In this thesis we present a symbolic execution-based technique for cross-checking programs accelerated using SIMD or OpenCL against an unaccelerated version, as well as a technique for detecting data races in OpenCL programs. Our techniques are implemented in KLEE-CL, a symbolic execution engine based on KLEE that supports symbolic reasoning on the equivalence between expressions […]

This paper presents a variation of Evolutionary Particle Swarm Optimization applied to the concept of master/slave swarm with mechanism of sharing data for the acceleration of convergence. The implementation called Cooperative Evolutionary MultiSwarm Optimization on Graphics Processing Units (CMEPSOGPU) consists in using thousands of threads in various slave swarms on the CUDA parallel architecture, where […]