Posts
Jul, 8
Implementability of shading models for current game engines
With the advances in the processor technology, todaypsilas graphical processing unit (GPU) architectures have evolved tremendously. Their speed and computational power has increased to the giga-flops levels. This has brought about a new architectural innovation called Shaders, which are programmable processing units that make all of the resources of the GPUs available to the game […]
Jul, 8
Parallel implementation of a spiking neuronal network model of unsupervised olfactory learning on NVidia CUDA
In this work I present the parallel implementation of a spiking neuronal network model with biologically realistic morphology, elements, and function on a graphical processing unit (GPU) using the NVidia CUDA framework. The comparison to a well-designed C/C++ implementation of the same model reveals a 24x speedup when using an NVidia Tesla C870 device for […]
Jul, 8
Hybrid Core Acceleration of UWB SIRE Radar Signal Processing
To move High-Performance Computing (HPC) closer to forward operating environments and missions, the Army Research Laboratory is developing approaches using hybrid, asymmetric core computing. By blending capabilities found in Graphics Processing Units (GPUs) and traditional von Neumann multicore Central Processing Units (CPUs), approaches are being developed and optimized to provide at or near real-time processing […]
Jul, 8
Visualizing Multiwavelength Astrophysical Data
With recent advances in the measurement technology for allsky astrophysical imaging, our view of the sky is no longer limited to the tiny visible spectral range over the 2D Celestial sphere. We now can access a third dimension corresponding to a broad electromagnetic spectrum with a wide range of allsky surveys; these surveys span frequency […]
Jul, 8
Accelerated video encoding using render context information
In this paper, we present a method to speed up video encoding of GPU rendered 3D scenes, which is particularly suited for the efficient and low-delay encoding of 3D game output as a video stream. The main idea of our approach is to calculate motion vectors directly from the 3D scene information used during rendering […]
Jul, 8
High Performance Remote Sensing Image Processing Using CUDA
This paper presented a high performance method for remote sensing image processing using CUDA-based GPU. And it introduced the process of several common algorithms in remote sensing image processing. Experiments were carried out and results showed that the computing speed of GPU was much faster than that of CPU.
Jul, 7
Enhanced implementation of the NTRUEncrypt algorithm using graphics cards
The NTRU encryption algorithm, also known as NTRUEncrypt, is a parameterized family of lattice-based public key cryptosystems that has been accepted to the IEEE P1363 standards under the specifications for lattice-based public-key cryptography (IEEE P1363.1). The operations of the NTRU encryption algorithm show good characteristics for data parallel processing which makes the NTRU a good […]
Jul, 7
Parallelizing FPGA Technology Mapping Using Graphics Processing Units (GPUs)
GPUs are becoming an increasingly attractive option for obtaining performance speedups for data-parallel applications. FPGA technology mapping is an algorithm that is heavily data parallel; however, it has many features that make it unattractive to implement on a GPU. The algorithm uses data in irregular ways since it is a graph-based algorithm. In addition, it […]
Jul, 7
Acceleration of Streamed Tensor Contraction Expressions on GPGPU-Based Clusters
Tensor contractions are generalized multidimensional matrix multiplication operations that widely occur in quantum chemistry. Efficient execution of tensor contractions on GPUs requires tackling several challenges to be addressed, including index permutation and small dimension-sizes reducing thread block utilization. In this paper, we present our approach to automatically generate CUDA code to execute tensor contractions on […]
Jul, 7
Comparing performance and energy efficiency of FPGAs and GPUs for high productivity computing
This paper provides the first comparison of performance and energy efficiency of high productivity computing systems based on FPGA (Field-Programmable Gate Array) and GPU (Graphics Processing Unit) technologies. The search for higher performance compute solutions has recently led to great interest in heterogeneous systems containing FPGA and GPU accelerators. While these accelerators can provide significant […]
Jul, 7
Optimization of a FDTD code for graphical processing units
Modern graphics processing units (GPUs) provide high computational power which can significantly decrease simulation time. We present two implementations of the FDTD algorithm on GPU and compare their performance with the CPU version.
Jul, 7
Pricing of cross-currency interest rate derivatives on Graphics Processing Units
We present a Graphics Processing Unit (GPU) parallelization of the computation of the price of cross-currency interest rate derivatives via a Partial Differential Equation (PDE) approach. In particular, we focus on the GPU-based parallel computation of the price of long-dated foreign exchange interest rate hybrids, namely Power Reverse Dual Currency (PRDC) swaps with Bermudan cancelable […]
