high performance computing on graphics processing units: hgpu.org

For papers submitted to ICDSP 2017, we offer the publications as following: 1. Publication in proceedings, which will be indexed by EI Compendex, Scopus, and ISI CPCS. 2. Publication published in the International Journal of Signal Processing Systems, which will be indexed by EI (INSPEC, IET), Google Scholar, etc There are two methods for submitting […]

For papers submitted to ICFIT 2017, we offer the publications as following: 1. Publication in Proceedings. Submissions will be peer reviewed by conference committees, and accepted papers will be published in proceedings, which will be indexed by EI Compendex, Scopus, and ISI CPCS. 2. Publication in Journal. Submissions will be reviewed by the conference committees […]

For papers submitted to ICSCT 2017, we offer the publications as following: 1. Publication in Proceedings. Submissions will be peer reviewed by conference committees, and accepted papers will be published in proceedings, which will be indexed by EI Compendex, Scopus, and ISI CPCS. 2. Publication in Journal. Submissions will be reviewed by the conference committees […]

1.Publication: After a careful reviewing process, all accepted papers after proper registration and presentation, will be published in the conference Proceedings by IEEE, and sent to be reviewed by the IEEE Conference Publication Program for IEEE Xplore and Ei Compendex. 2.Submission Methods: Electronic Submission System (.pdf) https://www.easychair.org/conferences/?conf=icsip2017

Deep Convolutional Neural Networks have received a lot of attention over the past few years as a promising technique for object classification in images. In this thesis, we implemented the frequency domain convolution for the popular Caffe framework. Deep Convolutional Neural Networks suffer from long training times even on contemporary hardware, which we want to […]

Graph analytics is becoming ever more ubiquitous in today’s world. However, situational dynamic changes in input graphs, such as changes in traffic and weather patterns, lead to variations in concurrency. Moreover, graph algorithms are known to have data dependent loops and fine-grain synchronization that makes them hard to scale on parallel machines. Recent trends in […]

In cryo-electron microscopy (EM), molecular structures are determined from large numbers of projection images of individual particles. To harness the full power of this single-molecule information, we use the Bayesian inference of EM (BioEM) formalism. By ranking structural models using posterior probabilities calculated for individual images, BioEM in principle addresses the challenge of working with […]

Current processors provide a variety of different processing units to improve performance and power efficiency. For example, ARM’s big.LITTLE, AMD’s APUs, and Oracle’s M7 provide heterogeneous processors, on-die GPUs, and on-die accelerators. However, the performance experienced by programs using these processing units can vary widely due to contention from multiprogramming, thermal constraints and other issues. […]

Heterogeneous architectures nowadays are becoming very attractive in the embedded and mobile markets thanks to the possibility to exploit the best computational resource to optimize the performance per Watt figure of merit. Unfortunately, deciding the right resource to use and its operating frequency is a difficult problem that depends on the actual conditions in which […]

Sparse matrix-vector multiplication (SpMV) is an important operation in computational science, and needs be accelerated because it often represents the dominant cost in many widely-used iterative methods and eigenvalue problems. We achieve this objective by proposing a novel SpMV algorithm based on the compressed sparse row (CSR) on the GPU. Our method dynamically assigns different […]

This paper demonstrates translation schemes by which programs written in a functional subset of APL can be compiled to code that is run efficiently on general purpose graphical processing units (GPGPUs). Furthermore, the generated programs can be straightforwardly interoperated with mainstream programming environments, such as Python, for example for purposes of visualization and user interaction. […]

Convolutional Neural Networks (CNNs) have gained significant traction in the field of machine learning, particularly due to their high accuracy in visual recognition. Recent works have pushed the performance of GPU implementations of CNNs to significantly improve their classification and training times. With these improvements, many frameworks have become available for implementing CNNs on both […]