high performance computing on graphics processing units: hgpu.org

We develop methods for accelerating metric similarity search that are effective on modern hardware. Our algorithms factor into easily parallelizable components, making them simple to deploy and efficient on multicore CPUs and GPUs. Despite the simple structure of our algorithms, their search performance is provably sublinear in the size of the database, with a factor […]

Scaling up the sparse matrix-vector multiplication kernel on modern Graphics Processing Units (GPU) has been at the heart of numerous studies in both academia and industry. In this article we present a novel non-parametric, self-tunable, approach to data representation for computing this kernel, particularly targeting sparse matrices representing power-law graphs. Using real data, we show […]

Detecting people in images is a challenging task because of the variability in clothing and illumination conditions, and the wide range of poses that people can adopt. To discriminate the human shape clearly, Dalal and Triggs [1] proposed a gradient based, robust feature set that yielded excellent detection results. This method computes locally normalized gradient […]

We investigate a fast pedestrian localization framework that integrates the cascade-of-rejectors approach with the Histograms of Oriented Gradients (HoG) features on a data parallel architecture. The salient features of humans are captured by HoG blocks of variable sizes and locations which are chosen by the AdaBoost algorithm from a large set of possible blocks. We […]

We present an integral image algorithm that can run in real-time on a Graphics Processing Unit (GPU). Our system exploits the parallelisms in computation via the NIVIDA CUDA programming model, which is a software platform for solving non-graphics problems in a massively parallel high-performance fashion. This implementation makes use of the work-efficient scan algorithm that […]

Optimal heuristic searches such as A* search are commonly used for low-dimensional planning such as 2D path finding. These algorithms however, typically do not scale well to high-dimensional planning problems such as motion planning for robotic arms, computing motion trajectories for non-holonomic robotic vehicles and motion synthesis for humanoid characters. A recently developed randomized version […]

Graphics processing units provide a large computational power at a very low price which position them as an ubiquitous accelerator. General purpose programming on the graphics processing units (GPGPU) is best suited for regular data parallel algorithms. They are not directly amenable for algorithms which have irregular data access patterns such as list ranking, and […]

Recently many-core graphic processor units (GPUs) are delivering impressive power for general purpose computing applications. Thanks to their high memory bandwidth and computing throughput, GPUs could often significantly accelerate many applications. In this paper, we present a CPU-GPU cooperative implementation for a Viola-Jones based face detection system. The experiment results show that our face detector […]

In recent years, Graphics Processing Units (GPUs) have been opened to general purpose programming. As a result, researchers and developers have access to the massively parallel GPU architecture for applications beyond that of graphics rendering and gaming. We first investigate a design and implementation of the trinomial lattice strategy for the pricing of simple European […]

Tracing secondary rays, such as reflection, refraction and shadow rays, can often be the most costly step in a modern real-time ray tracer. In this paper, we propose a new approach to ray tracing on GPU. Our approach is especially efficient for incoherent rays. Combined with the common packets ray tracing, we propose a different […]

This book deals with the acceleration of EDA algorithms using hardware platforms such as FPGAs and GPUs. Widely applied CAD algorithms are evaluated and compared for potential acceleration on FPGAs and GPUs. Coverage includes discussion of conditions under which it is preferable to use one platform over another, e.g., when an EDA problem has a […]

Supporting up to 16 PCI Express devices in a flexible, highly efficient design, the Dell PowerEdge C410x expansion chassis helps organizations take advantage of the next step in high-performance computing architectures: GPU computing.