high performance computing on graphics processing units: hgpu.org

Massively-parallel devices of various architectures are being adopted by the newest supercomputers to overcome the actual power constraint in the context of the exascale challenge. This progress leads to an increasing hybridisation of HPC systems and makes the design of computing applications a rather complex problem. Therefore, the software efficiency and portability are of crucial […]

Random program generation – fuzzing – is an effective technique for discovering bugs in compilers but successful fuzzers require extensive development effort for every language supported by the compiler, and often leave parts of the language space untested. We introduce DeepSmith, a novel machine learning approach to accelerating compiler validation through the inference of generative […]

It will bring together the researchers to exchange their research results and address open issues in: Computer Systems and Engineering Artificial Intelligence Computer Modeling Internet of Things (IoT) Decision Support System and Models Software Engineering Computer Graphics and Multimedia Image Processing System software support for multimedia Communication Technology Network and Wireless Communication VLSI Circuits and […]

Keynote speakers: Prof. Jalel Ben-Othman – University of Paris 13, France. Prof. Herwig Unger – University of Hagen, Germany. Published by: The accepted paper of ICCIP 2018 will be published into ICCIP 2018 Conference Proceedings, which will be published in the International Conference Proceedings Series by ACM and archived in the ACM Digital Library. The […]

Over the past few years, energy consumption has become the main limiting factor for computing in general. This has led CPU vendors to aggressively promote parallel computing using multiple cores without significantly increasing the thermal design power of the processor. However, achieving maximum performance and energy efficiency from the available resources on the multi-core and […]

Deep neural networks (DNN) have demonstrated effectiveness for various applications such as image processing, video segmentation, and speech recognition. Running state-of-the-art DNNs on current systems mostly relies on either general purpose processors, ASIC designs, or FPGA accelerators, all of which suffer from data movements due to the limited on chip memory and data transfer bandwidth. […]

Graphics processing units (GPUs) in embedded mobile platforms are reaching performance levels where they may be useful for computer vision applications. We compare two generations of embedded GPUs for mobile devices when running a state-of-the-art feature detection algorithm, i.e., Harris-Hessian/FREAK. We compare architectural differences, execution time, temperature, and frequency on Sony Xperia Z3 and Sony […]

We publish an extension of openQCD-1.6 with AVX-512 vector instructions using Intel intrinsics. Recent Intel processors support extended instruction sets with operations on 512-bit wide vectors, increasing both the capacity for floating point operations and register memory. Optimal use of the new capabilities requires reorganising data and floating point operations into these wider vector units. […]

With the recent success of embeddings in natural language processing, research has been conducted into applying similar methods to code analysis. Most works attempt to process the code directly or use a syntactic tree representation, treating it like sentences written in a natural language. However, none of the existing methods are sufficient to comprehend program […]

Field-Programmable Gate Arrays (FPGAs) are widely used in the central signal processing design of the Square Kilometre Array (SKA) as acceleration hardware. The frequency domain acceleration search (FDAS) module is an important part of the SKA1-MID pulsar search engine. To develop for a yet to be finalised hardware, for cross-discipline interoperability and to achieve fast […]

We introduce a novel meme generation system, which given any image can produce a humorous and relevant caption. Furthermore, the system can be conditioned on not only an image but also a user-defined label relating to the meme template, giving a handle to the user on meme content. The system uses a pretrained Inception-v3 network […]

Scene representation – the process of converting visual sensory data into concise descriptions – is a requirement for intelligent behaviour. Recent work has shown that neural networks excel at this task when provided large labelled datasets. However, removing the reliance on human labelling remains an important open problem. To this end, we introduce the Generative […]