high performance computing on graphics processing units: hgpu.org

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 […]

The focus of this work is the automatic performance tuning of stencil computations on Graphics Processing Units (GPUs). A strategy is presented that uses machine learning to determine the best way to use the GPU memory followed by a heuristic that divides the remaining optimizations into groups and exhaustively explores one group at a time. […]

This paper describes usage of CUDA parallelization scheme for forward and inverse gravity problems for structural boundaries. Forward problem is calculated using the finite elements approach. This means that the whole calculation volume is split into parallelepipeds and then the gravity effect of each is calculated using known formula. Inverse problem solution is found using […]

Science and Engineering has benefited enormously from the advent of modern (digital) computing. As technology continues to grow, computation capability becomes exponentially faster, more reliable, and more efficient. While modeling and simulations have hurdled analysis past many years of trial and error, they still are restricted by resources, even with modern computing. Whether running Monte […]

This project aims to port the scientific application GADGET-3 to multiple accelerators, research on the performance achieved and compare the porting/optimisations on the given accelerators with different architectures. In this project, the most time-consuming functions of GADGET-3 was identified based on the profiling. Partial functions in GADGET-3 were ported to the accelerator NVIDIA K40 card […]

Advection is the transport of a quantity due to fluid flow, and is an important, computationally intensive part of any fluid simulation. OpenACC GPU acceleration of the advection components of MONC, an atmospheric LES, was pursued. Although this yielded no speedup, the reasons for this are examined, and the conditions under which it may become […]