| 1. | The job scheduler will probably attempt to resubmit the calculation
任务调度程序可能试图重新提交计算。 |
| 2. | Build powerful clusters with grid services and job schedulers
用网格服务和作业调度程序构建功能强大的群集 |
| 3. | This entity would then direct the underlying job scheduler and data mover to do what we need
这个实体然后应该引导底层的任务调度器和数据移动程序来执行我们需要的功能。 |
| 4. | However , a number of job schedulers are available that already are or can be integrated with globus
不过，有一些任务调度器已经和globus集成起来了，还有一些也可以集成进来。 |
| 5. | In this article , learn about the powerful combination of a grid job scheduler , using openpbs with the ogsa - based globus toolkit 3 . 2
本文将学习如何用openpbs ，结合基于ogsa的globus toolkit 3 . 2 ，构建一个功能强大的网格作业调度程序。 |
| 6. | Once the state of all resources is known and made available in a standard format , job schedulers and data movers will be able to use the same view of the grid to make their decisions
一旦所有资源的状态都变成已知的，并且可以按照标准的格式使用之后，任务调度器和数据启动程序就可以使用相同的网格视图来制定决策。 |
| 7. | But as we add more complexity into the grid , particularly with geographically dispersed sites or nodes , it becomes more common for the job scheduler and data mover to make conflicting decisions
但是由于我们增加了网格的复杂性，尤其是那些地理上分布的站点或节点的复杂性，因此任务调度程序和数据移动程序很可能会作出相互冲突的决定。 |
| 8. | The approach is based on experience gained in many customer engagements . most organizations start their grid journeys by virtualizing workload , using a job scheduler like platform lsf or altairs pbs professional
大部分组织都是通过使用诸如platform lsf或altair的pbs professional之类的作业调度器，对任务负载进行虚拟化而开始构建自己的网格的。 |
| 9. | When the decision is obvious , the decisions made by the job scheduler the entity moving the compute component to the node and the data mover the entity moving the data component align , and both computation and data align on the same node
当决策非常明显时，由任务调度程序（将计算组件移动到节点上的实体）和数据移动程序（移动数据组件的实体）所制定的决策就可以进行调整，计算和数据组件也可以在同一节点上进行调整。 |
| 10. | Grid job schedulers provide advanced clustering capabilities required by today s most demanding applications , like those in e - science or e - business that rely on heavy - duty computing resources - multiple processors , terabytes of storage , and gigabytes of memory
网格作业调度程序提供的高级群集能力，正是当前要求最高的应用程序所需要的，比如说电子科学或电子商务应用程序，它们依赖于繁忙的计算资源，其中包括多处理器、 tb级的存储，以及gb级的内存等。 |
