【SIGGRAPH Asia 2012专题*技术论文】图形绘制：软壳：在GPU上的动态调度

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【SIGGRAPH Asia 2012专题*技术论文】
图形绘制：软壳：在GPU上的动态调度Softshell: Dynamic Scheduling on GPUs
Markus Steinberger, Bernhard Kainz, Bernhard Kerbl, Stefan Hauswiesner, Michael Kenzel, Dieter Schmalstieg 摘要：在本文中，我们提出软壳，多个处理内核运行在一个单指令，多数据的时尚，如图形处理单元（GPU）的设备组成一个新的执行模型。软壳模型直观，更灵活的流处理模式，这是目前通用的GPU computation.Using软壳模型的主要模式比基于内核的适应，算法的并行度相对较低的地方，可以有效地执行大规模并行架构。软壳具有以下显着的优点：（1）的工作可以被动态地发出直接在设备上，消除了需要与外部源的同步，即，CPU;（2）三层动态调度程序支持任意的调度策略，包括动态优先级的实时调度;（3）用户可以影响，暂停，取消已经提交的并行执行的工作。软壳处理模式，从而带来功能以前只从操作系统的设计，并保留CPU编程的GPU架构。作为一个证明我们的要求，我们提出了一个公开可用的执行的CUDA上实现的软壳处理模型。实施的基准，这表明我们的的处理模式很容易使用，也大大优于国家的最先进的基于内核的处理模型问题一直难以并行化，在过去的表现。 Abstract：In this paper we present Softshell, a novel&nbsp***cution model for devices composed of multiple processing cores operating in a single ins***ction, multiple data fashion, such as graphics processing units(GPUs). The Softshell model is intuitive and more flexible than the kernel-based adaption of the stream processing model, which is currently the dominant model for general purpose GPU computation.Using the Softshell model, algorithms with a relatively low local degree of parallelism can&nbsp***cute efficiently on massively parallel architectures. Softshell has the following distinct advantages: (1)work can be dynamically issued directly on the device, eliminating the need for synchronization with an external source, i.e., the CPU;(2) its three-tier dynamic scheduler supports arbitrary scheduling strategies, including dynamic priorities and real-time scheduling;and (3) the user can influence, pause, and cancel work already submitted for parallel&nbsp***cution. The Softshell processing model thus brings capabilities to GPU architectures that were previously only known from operating-system designs and reserved for CPU programming. As a proof of our claims, we present a publicly available implementation of the Softshell processing model realized on top of CUDA. The benchmarks of this implementation demonstrate that our processing model is easy to use and also performs substantially better than the state-of-the-art kernel-based processing model for problems that have been difficult to parallelize in the past. 要了解该论文的详情呢，就下载附件好好研究一下哈~更多新技术分享尽在web3D纳金网http://www.narkii.com/