Posts
Jan, 8
High Performance Multi-dimensional (2D/3D) FFT-Shift Implementation on Graphics Processing Units (GPUs)
Frequency domain analysis is one of the most common analysis techniques in signal and image processing. Fast Fourier Transform (FFT) is a well know tool used to perform such analysis by obtaining the frequency spectrum for time- or spatial-domain signals and vice versa. FFT-Shift is a subsequent operation used to handle the resulting arrays from […]
Jan, 8
Implementation of FDTD-Compatible Green’s Function on Heterogeneous CPU-GPU Parallel Processing System
This paper presents an implementation of the FDTD-compatible Green’s function on a heterogeneous parallel processing system. The developed implementation simultaneously utilizes computational power of the central processing unit (CPU) and the graphics processing unit (GPU) to the computational tasks best suited to each architecture. Recently, closed-form expression for this discrete Green’s function (DGF) was derived, […]
Jan, 8
Efficient Weighted Histogramming on GPUs with CUDA
The histogram is a fundamental statistical tool that has been extensively used in various domains. In data mining and machine learning applications, weighted histogram calculation often serves as a key component in the processing of their massive data sets. However, the atomic operation, which is introduced to resolve the collisions in GPU-based parallel histogramming with […]
Jan, 8
Distributed Massive Model Rendering
Graphics models are getting increasingly bulkier with detailed geometry, textures, normal maps, etc. There is a lot of interest to model and navigate through detailed models of large monuments. Many monuments of interest have both rich detail and large spatial extent. Rendering them for navigation on a single workstation is practically impossible, even given the […]
Jan, 8
GPU-Optimized Coarse-Grained MD Simulations of Protein and RNA Folding and Assembly
Molecular dynamics (MD) simulations provide a molecular-resolution physical description of the folding and assembly processes, but the size and the timescales of simulations are limited because the underlying algorithm is computationally demanding. We recently introduced a parallel neighbor list algorithm that was specifically optimized for MD simulations on GPUs. In our present study, we analyze […]
Jan, 7
CUDA based iterative methods for linear systems
Solving large linear systems of equations is a common problem in the fields of science and engineering. Direct methods for computing the solution of such systems can be very expensive due to high memory requirements and computational cost. This is a very good reason to use iterative methods which computes only an approximation of the […]
Jan, 7
Performance comparison of gauss-Jordan elimination method using OpenMP and CUDA
It is important to obtain the results of methods that are used in solving scientific and engineering problems rapidly for users and application developers. Parallel programming techniques have been developed alongside serial programming because the importance of performance has been increasing day by day while developing computer applications.Various methods such as Gauss Elimination (GE) Method, […]
Jan, 7
Numerical computations in Java with CUDA
Parallel computing can offer an enormous advantage regarding the performance for very large applications in almost any field: scientific computing, computer vision, databases, data mining, and economics. GPUs are high performance many-core processors that can obtain very high FLOP rates. Since the first idea of using GPU for general purpose computing, things have evolved and […]
Jan, 7
Interactive Refactoring for GPU Parallelization of Affine Loops
Considerable recent attention has been given to the problem of porting existing code to heterogeneous computing architectures, such as GPUs. In this paper, we describe a novel, interactive refactoring tool that allows for quick and easy transformation of affine loops to execute on GPUs. Compared to previous approaches, our refactoring approach interactively combines the user’s […]
Jan, 6
High-throughput Analysis of Large Microscopy Image Datasets on CPU-GPU Cluster Platforms
Analysis of large pathology image datasets offers significant opportunities for biomedical researchers to investigate the morphology of disease, but the resource requirements of image analyses limit the scale of those studies. Motivated by such a study, we propose and evaluate a parallel image analysis application pipeline for high throughput computation of large datasets of high […]
Jan, 5
Approximate Subdivision Surface Evaluation in the Language of Linear Algebra
We present an interpretation of approximate subdivision surface evaluation in the language of linear algebra. Specifically, vertices in the refined mesh can be computed by left-multiplying the vector of control vertices by a sparse matrix we call the subdivision operator. This interpretation is rather general: it applies to any level of subdivision, it holds for […]
Jan, 4
Hybrid GATE: A GPU/CPU implementation for imaging and therapy applications
Monte Carlo simulations (MCS) play a key role in medical applications. In this context GATE is a MCS platform dedicated to medical imaging and particle therapy. Yet MCS are very computationally demanding, which limits their applicability in clinical practice. Recently, graphics processing units (GPU) became, in many domains, a cost-effective solution to access high power […]