high performance computing on graphics processing units: hgpu.org

We present a fast, fully parameterizable GPU implementation of Convolutional Neural Network variants. Our feature extractors are neither carefully designed nor pre-wired, but rather learned in a supervised way. Our deep hierarchical architectures achieve the best published results on benchmarks for object classification (NORB, CIFAR10) and handwritten digit recognition (MNIST), with error rates of 2.53%, […]

In this paper, we investigate the suitability of the GPU for a parallel implementation of the pinwheel error diffusion. We demonstrate a high-performance GPU implementation by efficiently parallelizing and unrolling the image processing algorithm. Our GPU implementation achieves a 10 – 30x speedup over a two-threaded CPU error diffusion implementation with comparable image quality. We […]

Radar is a data-intensive measurement technique often requiring significant processing to make full use of the received signal. However, computing capacity is limited at remote or mobile radar installations thereby limiting radar data products used for real-time decisions. We used graphics processing units (GPUs) to accelerate processing of high resolution phase-coded radar data from the […]

Heterogeneous systems are becoming more common on High Performance Computing (HPC) systems. Even using tools like CUDA [1] and OpenCL [2] it is a non-trivial task to obtain optimal performance on the GPU. Approaches to simplifying this task include Merge [3] (a library based framework for heterogeneous multi-core systems), Zippy [4] (a framework for parallel […]

The graphics processing unit (GPU) continues to make significant strides as an accelerator in commodity cluster computing for high-performance computing (HPC). For example, three of the top five fastest supercomputers in the world, as ranked by the TOP500, employ GPUs as accelerators. Despite this increasing interest in GPUs, however, optimizing the performance of a GPU-accelerated […]

Numerical simulation and its huge computational demands require a close coupling between efficient mathematical methods and their hardware-aware implementation on emerging and highly parallel computing platforms. The paradigm shift towards manycore parallelism not only offers a high potential of computing capabilities but also comes up with urgent challenges in designing scalable, portable, and flexible software […]

We present parallel algorithms for processing, extracting and rendering adaptively sampled regular terrain datasets represented as a multiresolution model defined by a super-square-based diamond hierarchy. This model represents a terrain as a nested triangle mesh generated through a series of longest edge bisections and encoded in an implicit hierarchical structure, which clusters triangles into diamonds […]

We demonstrate that radically differing implementations of finite element methods are needed on multicore (CPU) and many-core (GPU) architectures, if their respective performance potential is to be realised. Our experimental investigations using a finite element advection-diffusion solver show that increased performance on each architecture can only be achieved by committing to specific and diverse algorithmic […]

Graphics processing units (GPUs) greatly improved their performance over the last ten years. The first graphics cards have been developed in the late 90’s and were targeted for the mass market. These first cards were special purpose hardware, designed to accelerate graphic processing required in computer games. As the interest in computer games continued, GPU […]

Recent advances in wireless/mobile communication and body worn sensors, together with ambient intelligence and seamless integrated pervasive technology have paved the way for applications operating based on social signals, i. e., sensing and processing of group behavior, interpersonal relationships, or emotions. Thinking in large, it should be apparent that modeling social systems allowing to study […]

In this paper we present a highly optimized implementation of Gaussian mixture acoustic model evaluation algorithm. Evaluation of these likelihoods is one of the most computationally intensive parts of automatics speech recognizers but it can be well-parallelized and offloaded to GPU devices. Our approach offers significant speed-up compared to the recently published approaches, since it […]

We report on the acceleration of annual daylighting simulations for fenestration systems in the Radiance raytracing program. The algorithm was optimized to reduce both the redundant data input/output operations and the floating-point operations. To further accelerate the simulation speed, the calculation for matrix multiplications was implemented using parallel computing on a graphics processing unit. We […]