high performance computing on graphics processing units: hgpu.org

We present a multi-GPU graph processing library that allows programmers to easily extend single-GPU graph algorithms to achieve scalable performance on large graph datasets with billions of edges. Our design only requires users to specify a few algorithm-dependent blocks, hiding most multi-GPU related implementation details. Our design effectively overlaps computation and data transfer and implements […]

Deep convolutional neural networks (CNN) have recently been shown in many computer vision and pattern recognition applications to outperform by a significant margin state-of-the-art solutions that use traditional hand-crafted features. However, this impressive performance is yet to be fully exploited in robotics. In this paper, we focus one specific problem that can benefit from the […]

Recent trends of aggressive technology scaling have greatly exacerbated the occurrences and impact of faults in computing systems. This has made `reliability’ a first-order design constraint. To address the challenges of reliability, several techniques have been proposed. This paper provides a survey of architectural techniques for improving resilience of computing systems. We especially focus on […]

We present Caffe con Troll (CcT), a fully compatible end-to-end version of the popular framework Caffe with rebuilt internals. We built CcT to examine the performance characteristics of training and deploying general-purpose convolutional neural networks across different hardware architectures. We find that, by employing standard batching optimizations for CPU training, we achieve up to one […]

This paper proposes a novel representation for symmetric fuzzy numbers that uses the midpoint-radius approach instead of the conventional lower-upper representation. A theoretical analysis based on the alpha-cut concept shows that the proposed format requires half the amount of operations and memory than the traditional one. Also, a novel technique involving radius increments is introduced, […]

In real-world face detection, large visual variations, such as those due to pose, expression, and lighting, demand an advanced discriminative model to accurately differentiate faces from the backgrounds. Consequently, effective models for the problem tend to be computationally prohibitive. To address these two conflicting challenges, we propose a cascade architecture built on convolutional neural networks […]

In recent years, many researchers have used the Navier-Stokes equations and Reaction-Diffusion systems for fluid simulation and for the creation of textures on surfaces, respectively. For this purpose it is necessary to obtain information about operators defined on surfaces. We obtained the metric information of the distortion caused by the parametrization of Catmull-Clark subdivision surfaces. […]

Previous efforts to formally verify code written for GPUs have focused solely on kernels written within the traditional data-parallel GPU programming model. No previous work has considered the higher performance, but more complex, warp-specialized kernels based on producer-consumer named barriers available on current hardware. In this work we present the first formal operational semantics for […]

This whitepaper is intended for Microsoft Windows developers who are considering writing high-performance parallel code in Amazon Web Services (AWS) using the Microsoft C++ Accelerated Massive Parallelism (C++ AMP) library. This paper describes an ASP.NET Model-View-Controller (MVC) web application written in C# that invokes C++ functions running on the graphics processing unit (GPU) for matrix […]

Numerical programs usually include type-casting instructions which convert data among different types. Identifying unsafe type-casting is important for preventing undefined program behaviors which cause serious problems such as security vulnerabilities and result non-reproducibility. While many tools had been proposed for handling sequential programs, to our best knowledge, there isn’t a tool geared toward GPUs. In […]

The majority of computer applications employ numerical data types with a fixed amount of precision for their computations. Their limited numerical range and precision are sufficient for most use cases. However, for some purposes, such as cryptography or geometrical computations, the required range and precision can become arbitrarily large. Numerical types that can handle such […]

Automatic organ segmentation is an important prerequisite for many computer-aided diagnosis systems. The high anatomical variability of organs in the abdomen, such as the pancreas, prevents many segmentation methods from achieving high accuracies when compared to other segmentation of organs like the liver, heart or kidneys. Recently, the availability of large annotated training sets and […]