high performance computing on graphics processing units: hgpu.org

2017 9th International Conference on Signal Processing Systems (ICSPS 2017) is the main annual research conference aims to bring together top researchers around the world to exchange research results and address open issues in all aspects of Signal Processing Systems. Publication Two options: 1 Conference Proceedings, Ei Compendex and Scopus and submitted to be reviewed […]

2017 The 5th International conference on Control, Mechatronics and Automation will be held in University of Alberta, Canada during October 11-13, 2017. ICCMA 2013 was held in Sydney, ICCMA 2014 was held in Dubai, ICCMA 2015 and ICCMA 2016 were both held in Barcelona. The idea of the conference is for the scientists, scholars, engineers […]

2017 8th International Conference on Biology, Environment and Chemistry (ICBEC 2017) will be held in Busan, South Korea during October 11-13, 2017. ICBEC 2017 is sponsored by the Hong Kong Chemical, Biological & Environmental Engineering Society (HKICBEES). It is one of the leading international conferences for presenting novel and fundamental advances in the fields of […]

ICCIS 2017 will be a perfect platform to share experience, foster collaborations across industry and academia, and evaluate emerging technologies across the globe. Publication Peer reviewed and presented papers in ICCIS 2017 will be published in the conference proceedings, which will be submitted for Ei Compendex and Scopus index. Submission Methods Full Paper(publication and oral […]

Increasingly complex memory systems and onchip interconnects are developed to mitigate the data movement bottlenecks in manycore processors. One example of such a complex system is the Xeon Phi KNL CPU with three different types of memory, fifteen memory configuration options, and a complex on-chip mesh network connecting up to 72 cores. Users require a […]

Many modern parallel computing systems are heterogeneous at their node level. Such nodes may comprise general purpose CPUs and accelerators (such as, GPU, or Intel Xeon Phi) that provide high performance with suitable energy-consumption characteristics. However, exploiting the available performance of heterogeneous architectures may be challenging. There are various parallel programming frameworks (such as, OpenMP, […]

This work presents a method for a computer vision-based detection of biological viruses in PAMONO sensor images and, related to this, methods to explore cyber-physical systems such as those consisting of the PAMONO sensor, the detection software, and processing hardware. The focus is especially on an exploration of Graphics Processing Units (GPU) hardware for "General-Purpose […]

In this paper, we study various parallelization schemes for the Variable Neighborhood Search (VNS) metaheuristic on a CPU-GPU system via OpenMP and OpenACC. A hybrid parallel VNS method is applied to recent benchmark problem instances for the multi-product dynamic lot sizing problem with product returns and recovery, which appears in reverse logistics and is known […]

In this work we present an evaluation of GPUs as a possible L1 Track Trigger for the High Luminosity LHC, effective after Long Shutdown 3 around 2025. The novelty lies in presenting an implementation based on calculations done entirely in software, in contrast to currently discussed solutions relying on specialized hardware, such as FPGAs and […]

While most filtering approaches based on random finite sets have focused on improving performance, in this paper, we argue that computation times are very important in order to enable real-time applications such as pedestrian detection. Towards this goal, this paper investigates the use of OpenCL to accelerate the computation of random finite set-based Bayesian filtering […]

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 […]

Convolutional neural networks (CNNs) have emerged as one of the most successful machine learning technologies for image and video processing. The most computationally intensive parts of CNNs are the convolutional layers, which convolve multi-channel images with multiple kernels. A common approach to implementing convolutional layers is to expand the image into a column matrix (im2col) […]