The AMD Fusion Family of Accelerated Processing Units (APUs), introduced to market in January 2011, is a new generation of processors that combines the computing processing unit (CPU) and graphics processing unit (GPU) capabilities in a single chip (die). APU-based platforms can deliver a prodigious amount of computational horsepower, and can present enormous opportunities in developing an appl...

Providing untrusted applications with shared and dependable access to modern display hardware is of increasing importance. Our new display system, called Blink, safely multiplexes complex graphical content from multiple untrusted virtual machines onto a single Graphics Processing Unit (GPU). Blink does not allow clients to program the GPU directly, but instead provides a virtual processor abstr...

We have ported image characterization algorithm implemented in doc2learn application to the Graphics Processing Unit (GPU) platform using both CUDA C targeting NVIDIA GPUs and OpenCL targeting NVIDIA and AMD GPU architectures. We also implemented doc2learn image analysis algorithm in C targeting microprocessor architecture. Our conclusion is that doc2learn image processing part can be accelerat...

An interactive multi-display cluster-style rendering system is presented which runs on a single PC rather than a cluster of PCs. Many Direct3D features, including support for a programmable pipeline, are supported via a drop-in library replacement for Direct3D. While the presented profiling results are bandwidth limited, PCI cards have been used. It is expected that the greater bandwidth of PCI...

This paper presents a new high precision integral image algorithm that can execute in real-time on a commodity graphics processing unit (GPU). This system makes use of the general processing GPU (GPGPU) paradigm via a stream computing abstraction. The stream computing language used is Brook which allows portability across GPGPUs from multiple manufacturers. The paper analyses the high precision...

Graphics Processing Units (GPU) allow for running massively parallel applications offloading the Central Processing Unit (CPU) from computationally intensive resources. However GPUs have a limited amount of memory. In this paper, a trie compression algorithm for massively parallel pattern matching is presented demonstrating 85% less space requirements than the original highly efficient parallel...

This paper describes the implementation of a streaming spectral processing system for realtime audio in a consumer-level onboard GPU (Graphics Processing Unit) attached to an off-the-shelf laptop computer. It explores the implementation of four processes: standard phase vocoder analysis and synthesis, additive synthesis and the sliding phase vocoder. These were developed under the CUDA developm...

We use the graphics processing unit (GPU) for fast calculations of helicity amplitudes of physics processes. As our first attempt, we compute uu → nγ (n=2 to 8) processes in pp collisions at √ s = 14TeV by transferring the MadGraph generated HELAS amplitudes (FORTRAN) into newly developed HEGET (HELAS Evaluation with GPU Enhanced Technology) codes written in CUDA, a C-platform developed by NVID...

In Fourier domain optical coherence tomography (FD-OCT), a large amount of interference data needs to be resampled from the wavelength domain to the wavenumber domain prior to Fourier transformation. We present an approach to optimize this data processing, using a graphics processing unit (GPU) and parallel processing algorithms. We demonstrate an increased processing and rendering rate over th...

Graphics processing unit (GPU), although a powerful performance-booster, also has many security vulnerabilities. Due to these, the GPU can act as a safe-haven for stealthy malware and the weakest ‘link’ in the security ‘chain’. In this paper, we present a survey of techniques for analyzing and improving GPU security. We classify the works on key attributes to highlight their similarities and di...