Accurate Depth of Field Simulation in Real Time

We present a new post processing method of simulating depth of field based on accurate calculations of circles of confusion. Compared to previous work, our method derives actual scene depth information directly from the existing depth buffer, requires no specialized rendering passes, and allows easy integration into existing rendering applications. Our implementation uses an adaptive, two‐pass filter, producing a high quality depth of field effect that can be executed entirely on the GPU, taking advantage of the parallelism of modern graphics cards and permitting real time performance when applied to large numbers of pixels.     

网络对抗训练混合虚拟化平台设计研究

讨论了虚拟化技术实现原理及其在网络对抗教学中的应用上,分析了各类虚拟化技术的优缺点和构建网络对抗训练环境存在的问题。提出了一种混合虚拟化平台设计,该平台利用Libvirt虚拟化的应用程序编程接口（API）调用两种虚拟化技术同时运行在同一物理主机上。并详细叙述了混合虚拟化平台的实现过程和方法,并在多个虚拟机内同时运行测试基准,分析其可扩展性。多种虚拟化技术在同一物理机上的混合,实现了复杂实验环境的创建,对构建大规模的网络实验平台具有一定的参考价值。     

数据中心统一架构网络设计构想

根据企业的需求及业界的发展趋势,数据中心虚拟化的核心是网络虚拟化、计算虚拟化、存储虚拟化。文章重点讨论数据中心虚拟化趋势下的网络架构设计。     

A note on circle packing

The problem of packing circles into a domain of prescribed topology is considered. The circles need not have equal radii. The Collins-Stephenson algorithm computes such a circle packing. This algorithm is parallelized in two different ways and its performance is reported for a triangular, planar domain test case. The implementation uses the highly parallel graphics processing unit (GPU) on commodity hardware. The speedups so achieved are discussed based on a number of experiments.     

基于Linux VMware虚拟机的串口通信

嵌入式开发领域经常使用串口通信,但串口通信方式占用很多硬件资源,设备的利用率较低。文章研究了基于Linux VMware虚拟机进行串口通信的Use Physical Serial Port模式、Use Out File模式以及Use Named Pipe模式的功能和特点,给出了基于VMware构建串口通信环境的方法以及具体实现过程。     

云计算安全：概念、现状与关键技术

随着云计算的广泛应用,云计算安全问题逐渐凸显出来。文章首先阐述了云计算安全相关概念,并对云计算的安全问题和云计算安全特征进行分析,然后对云计算安全的现状和典型的云计算安全体系架构进行了介绍,并对云计算安全的关键技术进行分析,最后给出了结论。     

XVM虚拟环境下并行程序的性能评测

该文引入speedup作为并行程序的性能评测指标,分析了并行程序在不同类型和不同数量的客户虚拟机中运行的性能差异,实验表明,MPI并行程序在xVM虚拟化环境中的运行性能接近非虚拟化本地主机的性能,在半虚拟化环境中的并行程序性能超过全虚拟化环境中的并行程序性能。     

Particle-in-Cell algorithms for emerging computer architectures

We have designed Particle-in-Cell algorithms for emerging architectures. These algorithms share a common approach, using fine-grained tiles, but different implementations depending on the architecture. On the GPU, there were two different implementations, one with atomic operations and one with no data collisions, using CUDA C and Fortran. Speedups up to about 50 compared to a single core of the Intel i7 processor have been achieved. There was also an implementation for traditional multi-core processors using OpenMP which achieved high parallel efficiency. We believe that this approach should work for other emerging designs such as Intel Phi coprocessor from the Intel MIC architecture.     

GPU accelerated online multi-particle beam dynamics simulator for ion linear particle accelerators

An online beam dynamics simulator is being developed for use in the operation of an ion linear particle accelerator. By employing Graphics Processing Unit (GPU) technology, the performance of the simulator has been significantly increased over that of a single CPU and is therefore viable in the demanding accelerator operations environment. Once connected to the accelerator control system, it can rapidly respond to any control set point changes and predict beam properties along an ion linear accelerator in pseudo-real time. This simulator will be a virtual beam diagnostic tool which is especially useful when direct beam measurements are not available. Details about the code structure design, physics algorithms, GPU implementations, and performance are presented.     

Fast computation of computer-generated hologram using Xeon Phi coprocessor

We report fast computation of computer-generated holograms (CGHs) using Xeon Phi coprocessors, which have massively x86-based processors on one chip, recently released by Intel. CGHs can generate arbitrary light wavefronts, and therefore, are promising technology for many applications: for example, three-dimensional displays, diffractive optical elements, and the generation of arbitrary beams. CGHs incur enormous computational cost. In this paper, we describe the implementations of several CGH generating algorithms on the Xeon Phi, and the comparisons in terms of the performance and the ease of programming between the Xeon Phi, a CPU and graphics processing unit (GPU).