high performance computing on graphics processing units: hgpu.org

Dedispersion, the removal of deleterious smearing of impulsive signals by the interstellar matter, is one of the most intensive processing steps in any radio survey for pulsars and fast transients. We here present a study of the parallelization of this algorithm on many-core accelerators, including GPUs from AMD and NVIDIA, and the Intel Xeon Phi. […]

We study the effect of isospin-dependent nuclear forces on the pasta phase in the inner crust of neutron stars. To this end we model the crust within the framework of quantum molecular dynamics (QMD). For maximizing the numerical performance, the newly developed code has been implemented on GPU processors. As a first application of the […]

High performance computing studies the construction and programming of computing system with tremendous computational power playing a key role in scientific computing and research across disciplines. The graphics processing unit (GPU) developed for fast 2D and 3D visualizations has turned into a programmable general purpose accelerator device boosting today’s high performance clusters. Leveraging these computational […]

The MapReduce framework is a programming model proposed by Google to process large datasets. It is an efficient framework that can be used in many areas, such as social network, scientific research, electronic business, etc. Hence, more and more MapReduce frameworks are implemented on different platforms, including Phoenix (based on multicore CPU), MapCG (based on […]

In this paper, a fast and practical GPU-based implementation of Fuzzy C-Means (FCM) clustering algorithm for image segmentation is proposed. First, an extensive analysis is conducted to study the dependency among the image pixels in the algorithm for parallelization. The proposed GPU-based FCM has been tested on digital brain simulated dataset to segment white matter(WM), […]

Tsunamis generated by earthquakes commonly propagate as long waves in the deep ocean and develop into sharp-fronted surges moving rapidly towards the coast in shallow water, which may be effectively simulated by hydrodynamic models solving the nonlinear shallow water equations (SWEs). However, most of the existing tsunami models suffer from long simulation time for large-scale […]

We present ESBMC-GPU, an extension to the ESBMC model checker that is aimed at verifying GPU programs written for the CUDA framework. ESBMC-GPU uses an operational model for the verification, i.e., an abstract representation of the standard CUDA libraries that conservatively approximates their semantics. ESBMC-GPU verifies CUDA programs, by explicitly exploring the possible interleavings (up […]

In this paper we present DeepLearningKit – an open source framework that supports using pre- trained deep learning models (convolutional neural networks) for iOS, OS X and tvOS. DeepLearningKit is developed in Metal in order to utilize the GPU efficiently and Swift for integration with applications, e.g. iOS-based mobile apps on iPhone/iPad, tvOS-based apps for […]

Genetic Programming (GP) is a computationally intensive technique which also has a high degree of natural parallelism. Parallel computing architectures have become commonplace especially with regards Graphics Processing Units (GPU). Hence, versions of GP have been implemented that utilise these highly parallel computing platforms enabling significant gains in the computational speed of GP to be […]

Paper Publication The paper acceptecd by ICGIP 2016 will be published in conference proceedings by SPIE and be indexed by Ei Compendex and Scopus. For the historic publication and indexing, visit: http://www.icgip.org/history.html Submission Methods 1. Full Paper (Presentation and publication) 2. Abstract (Presentation only) Please submit paper in the Electronic Submission System (http://www.easychair.org/conferences/?conf=icgip2016) or to […]

The emergence of multicore and heterogeneous architectures requires many linear algebra algorithms to be redesigned to take advantage of the accelerators, such as GPUs. A particularly challenging class of problems, arising in numerous applications, involves the use of linear algebra operations on many small-sized matrices. The size of these matrices is usually the same, up […]

There is a clear trend nowadays to use heterogeneous high-performance computers, as they offer considerably greater computing power than homogeneous CPU systems. Extending traditional CPU systems with specialized units (accelerators such as GPGPUs) has become a revolution in the HPC world. Both the traditional performance-per-Watt and the performance-per-Euro ratios have been increased with the use […]