high performance computing on graphics processing units: hgpu.org

The growing interest to incorporate new features into mobile devices has increased the number of signal processing applications running over processors designed for mobile computing. A challenging signal processing field is acoustic source localization, which is attractive for applications such as automatic camera steering systems, human-machine interfaces, video gaming or audio surveillance. In this context, […]

In this paper, we revisit, explore and extend the Particle Trajectory Sonification (PTS) model, which supports cluster analysis of high-dimensional data by probing a model space with virtual particles which are "gravitationally" attracted to a mode of the dataset’s potential function. The particles’ kinetic energy progression of as function of time adds directly to a […]

Due to increased demand for computational efficiency for the training, validation and testing of artificial neural networks, many open source software frameworks have emerged. Almost exclusively GPU programming model of choice in such software frameworks is CUDA. Symptomatic is also lack of the support for complex-valued neural networks. With our research going exactly in that […]

The two-dimensional discrete wavelet transform has a huge number of applications in image-processing techniques. Until now, several papers compared the performance of such transform on graphics processing units (GPUs). However, all of them only dealt with lifting and convolution computation schemes. In this paper, we show that corresponding horizontal and vertical lifting parts of the […]

The proliferation of a diverse set of heterogeneous computing platforms in conjunction with the plethora of programming languages and optimization techniques on each language for each underlying architecture exacerbate widespread adoption of such platforms. This is especially true for novice programmers and the non-technical-savvy masses that are largely precluded from enjoying the advantages of high-performance […]

In recent years, deep convolutional neural networks (ConvNet) have shown their popularity in various real world applications. To provide more accurate results, the state-of-the-art ConvNet requires millions of parameters and billions of operations to process a single image, which represents a computational challenge for general purpose processors. As a result, hardware accelerators such as Graphic […]

The 2-D discrete wavelet transform (DWT) can be found in the heart of many image-processing algorithms. Until recently, several studies have compared the performance of such transform on various shared-memory parallel architectures, especially on graphics processing units (GPUs). All these studies, however, considered only separable calculation schemes. We show that corresponding separable parts can be […]

Crowd simulations are used to imitate the behaviour of a large group of people. Such simulations are used in industries ranging from video-games to public security. In recent years, research has turned to the parallel nature of GPUs to simulate the behaviour of individuals in a crowd in parallel. This allows for real time visualisation […]

The computational landscape is dominated by the use of a very high number of CPU resources; this has however provided diminishing returns in recent years, pushing for a paradigm shift in the choice for computational systems. The following work was aimed at determining the maturity of heterogeneous computer systems in terms of computational performance and […]

With the advent of many-core general-purpose processors (CPUs), the use of an increased number of cores has provided a certain speedup for algorithms that can be parallized. Nowadays, there are distributed and parallel data processing platforms, such as Apache Flink, which inherently makes use of parallel computing. On the other hand, graphics processors(GPUs) offers high […]

Built for massive parallelism, General Purpose computing on Graphic Processing Unit (GPGPU) has superseded high-performance CPU in several important tasks, including computer graphics, physics calculations, encryption/decryption and scientific computations. The goal of this workshop is to provide a forum to discuss and evaluate emerging techniques, platforms and applications capable of harvesting the power of current […]

Heterogeneous system architectures are evolving towards tighter integration among devices, with emerging features such as shared virtual memory, memory coherence, and systemwide atomics. Languages, device architectures, system specifications, and applications are rapidly adapting to the challenges and opportunities of tightly integrated heterogeneous platforms. Programming languages such as OpenCL 2.0, CUDA 8.0, and C++ AMP allow […]