16779

Posts

Nov, 30

Deep, Dense, and Low-Rank Gaussian Conditional Random Fields

In this work we introduce a fully-connected graph structure in the Deep Gaussian Conditional Random Field (G-CRF) model. For this we express the pairwise interactions between pixels as the inner-products of low-dimensional embeddings, delivered by a new subnetwork of a deep architecture. We efficiently minimize the resulting energy by solving the resulting low-rank linear system […]
Nov, 30

Optimization of Pattern Matching Algorithms for Multi- and Many-Core Platforms

Image and video compression play a major role in the world today, allowing the storage and transmission of large multimedia content volumes. However, the processing of this information requires high computational resources, hence the improvement of the computational performance of these compression algorithms is very important. The Multidimensional Multiscale Parser (MMP) is a pattern-matching-based compression […]
Nov, 29

dCUDA: hardware supported overlap of computation and communication

Over the last decade, CUDA and the underlying GPU hardware architecture have continuously gained popularity in various high-performance computing application domains such as climate modeling, computational chemistry, or machine learning. Despite this popularity, we lack a single coherent programming model for GPU clusters. We therefore introduce the dCUDA programming model, which implements device-side remote memory […]
Nov, 27

2nd International Conference on Robotics and Automation Engineering (ICRAE), 2017

The ICRAE conference is an international forum for the presentation of technological advances and research results in the fields of Robotics and Automation Engineering.Researchers from across the world are welcome to attend and submit their best work to ICRAE 2017 conference to exchange ideas about the latest theories, technology, data, and videos furthering the state-of-the-art […]
Nov, 27

2nd International Conference on Computational Intelligence and Applications (ICCIA), 2017

The aim objective of ICCIA 2017 is to present the latest research and results of scientists related to Computational Intelligence and Applications topics. This conference provides opportunities for the different areas delegates to exchange new ideas and application experiences face to face, to establish business or research relations and to find global partners for future […]
Nov, 25

A Metric for Performance Portability

The term "performance portability" has been informally used in computing to refer to a variety of notions which generally include: 1) the ability to run one application across multiple hardware platforms; and 2) achieving some notional level of performance on these platforms. However, there has been a noticeable lack of consensus on the precise meaning […]
Nov, 25

Fast and Energy-Efficient CNN Inference on IoT Devices

Convolutional Neural Networks (CNNs) exhibit remarkable performance in various machine learning tasks. As sensor-equipped internet of things (IoT) devices permeate into every aspect of modern life, it is increasingly important to run CNN inference, a computationally intensive application, on resource constrained devices. We present a technique for fast and energy-efficient CNN inference on mobile SoC […]
Nov, 25

PVR: Patch-to-Volume Reconstruction for Large Area Motion Correction of Fetal MRI

In this paper we present a novel method for the correction of motion artifacts that are present in fetal Magnetic Resonance Imaging (MRI) scans of the whole uterus. Contrary to current slice-to-volume registration (SVR) methods, requiring an inflexible anatomical enclosure of a single investigated organ, the proposed patch-to-volume reconstruction (PVR) approach is able to reconstruct […]
Nov, 25

Efficient Kernel Synthesis for Performance Portable Programming

The diversity of microarchitecture designs in heterogeneous computing systems allows programs to achieve high performance and energy efficiency, but results in substantial software re-development cost for each type or generation of hardware. To mitigate this cost, a performance portable programming system is required. One fundamental difference between architectures that makes performance portability challenging is the […]
Nov, 25

dMath: Distributed Linear Algebra for DL

The paper presents a parallel math library, dMath, that demonstrates leading scaling when using intranode, internode, and hybrid-parallelism for deep learning (DL). dMath provides easy-to-use distributed primitives and a variety of domain-specific algorithms including matrix multiplication, convolutions, and others allowing for rapid development of scalable applications like deep neural networks (DNNs). Persistent data stored in […]
Nov, 23

Performance Analysis of CUDA and OpenCL By Implementation of Cryptographic Algorithms

This paper presents a Performance Analysis of CUDA and OpenCL. Three different cryptographic algorithms, i.e. DES, MD5, and SHA-1 have been selected as the benchmarks for extensive analysis of the performance gaps between the two. Our results show that, on the average scenario, CUDA performs 27% better than OpenCL while in the best case scenario […]
Nov, 23

A Metaprogramming and Autotuning Framework for Deploying Deep Learning Applications

In recent years, deep neural networks (DNNs), have yielded strong results on a wide range of applications. Graphics Processing Units (GPUs) have been one key enabling factor leading to the current popularity of DNNs. However, despite increasing hardware flexibility and software programming toolchain maturity, high efficiency GPU programming remains difficult: it suffers from high complexity, […]
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