Posts
Jan, 6
Artifact-Free JPEG Decompression with Total Generalized Variation
We propose a new model for the improved reconstruction of JPEG (Joint Photographic Experts Group) images. Given a JPEG compressed image, our method first determines the set of possible source images and then specifically chooses one of these source images satisfying additional regularity properties. This is realized by employing the recently introduced Total Generalized Variation […]
Jan, 6
Hyper neural network on OpenCL
The goal of this thesis is to design and implement a hyper neural network that has a topology with limited number inputs of individual neurons and uses genetic programming as the learning algorithm. Parallelization of this neural network is done with use of OpenCL standard which allows running it on wide range of devices. From […]
Jan, 6
Lossless Compression of Variable-Precision Floating-Point Buffers on GPUs
In this work, we explore the lossless compression of 32-bit floating-point buffers on graphics hardware. We first adapt a state-of-the-art 16-bit floating-point color and depth buffer compression scheme for operation on 32-bit data and propose two specific enhancements: dynamic bucket selection and a Fibonacci encoder. Next, we describe a unified codec for any type of […]
Jan, 6
Optimizing a Biomedical Imaging Orientation Score Framework
A branch of Biomedical image processing involves analyzing images containing elongates structures. The enhancement of these structures in noisy image data is often required to enable automatic image analysis. A framework for such noise reduction based on Coherence Enhancing Diffusion (CED) using Orientation Scores (OS) has been developed. However, owing to the high computational complexity […]
Jan, 6
CodePy
The C/C++ metaprogramming toolkit for Python [16], CodePy [2], is analysed according to its source code generation possibility and its way to generate extension modules for Python. The combination of both results in generating C code in a Python script and executing it from within the same script. Insights are given on how this roundtrip […]
Jan, 6
Low-power Task Scheduling for GPU Energy Reduction
Graphics processing units (GPU) have been intensively used by high-performance computing applications. However, GPU’s large power consumption is a big issue coexisting with the high parallelism. Although Dynamic Voltage and Frequency Scaling (DVFS) [1] has been heavily studied and successfully applied to real products for saving CPU power consumption, DVFS is still relatively new for […]
Jan, 6
Multiple-GPU Scalability of Phase-Field Simulation for Dendritic Solidification
Mechanical properties of metallic materials like steel depend on the solidification process. In order to study the morphology of the microstructure in the materials, the phase-field model derived from the non-equilibrium statistical physics is applied and the interface dynamics is solved by GPU computing. Since very high performance is required, 3-dimensional simulations have not been […]
Jan, 6
Efficient 3D reconstruction of large-scale urban environments from street-level video
Recovering the 3-dimensional (3D) structure of a scene from 2-dimensional (2D) images is a fundamental problem in computer vision. This technology has many applications in computer graphics, entertainment, robotics, transportation, manufacturing, security, etc. One application is 3D mapping. For example, Google Earth and Microsoft Bing Maps provide a 3D virtual replica of many of the […]
Jan, 6
Applying OOC Techniques in the Reduction to Condensed Form for Very Large Symmetric Eigenproblems on GPUs
In this paper we address the reduction of a dense matrix to tridiagonal form for the solution of symmetric eigenvalue problems on a graphics processor (GPU) when the data is too large to fit into the accelerator memory. We apply out-of-core techniques to a three-stage algorithm, carefully redesigning the first stage to reduce the number […]
Jan, 5
A GPU Implementation of Inclusion-based Points-to Analysis
Graphics Processing Units (GPUs) have emerged as powerful accelerators for many regular algorithms that operate on dense arrays and matrices. In contrast, we know relatively little about using GPUs to accelerate highly irregular algorithms that operate on pointer-based data structures such as graphs. For the most part, research has focused on GPU implementations of graph […]
Jan, 5
PARRAY: A Unifying Array Representation for Heterogeneous Parallelism
This paper introduces a programming interface called PARRAY (or Parallelizing ARRAYs) that supports system-level succinct programming for heterogeneous parallel systems like GPU clusters. The current practice of software development requires combining several low-level libraries like Pthread, OpenMP, CUDA and MPI. Achieving productivity and portability is hard with different numbers and models of GPUs. PARRAY extends […]
Jan, 5
Selecting the Best Tridiagonal System Solver Projected on Multi-Core CPU and GPU Platforms
Nowadays multicore processors and graphics cards are commodity hardware that can be found in personal computers. Both CPU and GPU are capable of performing high-end computations. In this paper we present and compare parallel implementations of two tridiagonal system solvers. We analyze the cyclic reduction method, as an example of fine-grained parallelism, and Bondeli’s algorithm, […]