Supercomputing and Algorithms Group, Associated Unit CSIC-UAL, University of Almería, 04120 Almería, Spain.
Ultramicroscopy. 2012 Apr;115:109-14. doi: 10.1016/j.ultramic.2012.02.003. Epub 2012 Feb 18.
Modern computers are equipped with powerful computing engines like multicore processors and GPUs. The 3DEM community has rapidly adapted to this scenario and many software packages now make use of high performance computing techniques to exploit these devices. However, the implementations thus far are purely focused on either GPUs or CPUs. This work presents a hybrid approach that collaboratively combines the GPUs and CPUs available in a computer and applies it to the problem of tomographic reconstruction. Proper orchestration of workload in such a heterogeneous system is an issue. Here we use an on-demand strategy whereby the computing devices request a new piece of work to do when idle. Our hybrid approach thus takes advantage of the whole computing power available in modern computers and further reduces the processing time. This CPU+GPU co-processing can be readily extended to other image processing tasks in 3DEM.
现代计算机配备了强大的计算引擎，如多核处理器和 GPU。3DEM 社区已经迅速适应了这种情况，许多软件包现在都使用高性能计算技术来利用这些设备。然而，到目前为止的实现纯粹专注于 GPU 或 CPU。这项工作提出了一种混合方法，该方法协同结合计算机中可用的 GPU 和 CPU，并将其应用于层析重建问题。在这样的异构系统中，对工作负载进行适当的协调是一个问题。在这里，我们使用按需策略，即计算设备在空闲时请求做新的工作。因此，我们的混合方法利用了现代计算机中可用的全部计算能力，并进一步减少了处理时间。这种 CPU+GPU 协同处理可以很容易地扩展到 3DEM 中的其他图像处理任务。
