A scalable queue for work distribution on GPUs

B. Kerbl, Jörg Müller, Michael Kenzel, D. Schmalstieg, M. Steinberger
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引用次数: 1

Abstract

Harnessing the power of massively parallel devices like the graphics processing unit (GPU) is difficult for algorithms that show dynamic or inhomogeneous workloads. To achieve high performance, such advanced algorithms require scalable, concurrent queues to collect and distribute work. We present a new concurrent work queue, the Broker Queue, a highly efficient, linearizable queue for fine-granular work distribution on the GPU. We evaluate its usability and benefits in contrast to existing queuing algorithms. Our queue is up to one order of magnitude faster than non-blocking queues, and outperforms simpler queue designs that are unfit for fine-granular work distribution.
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用于gpu上的工作分发的可扩展队列
对于显示动态或非均匀工作负载的算法来说,利用图形处理单元(GPU)等大规模并行设备的能力是很困难的。为了实现高性能,这种高级算法需要可扩展的并发队列来收集和分发工作。我们提出了一种新的并发工作队列——Broker queue,它是一种高效的、可线性化的队列,用于在GPU上进行细粒度的工作分配。与现有的排队算法相比,我们评估了它的可用性和优点。我们的队列比非阻塞队列快一个数量级,并且优于不适合细粒度工作分配的简单队列设计。
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