| 1. | Does it support parallel and serial job submission 支持并行任务提交还是串行任务提交? |
| 2. | Concurrent job submissions 并行任务提交 |
| 3. | The max degree option on dsntip4 determines the maximum degree of parallelism maximum number of parallel tasks Dsntip4上的max degree选项决定了最大并行度(并行任务的最大数量) 。 |
| 4. | It offers high computational performance and a high degree of flexibility and adaptability by employing a micro task controller unit in conjunction with programmable and configurable hardware 它们多数具有异构的性质,而且由几个对数据并行任务有实时性能要求的子任务组成。 |
| 5. | On account of the real - time algorithm ' s character of multi - task , the key realizing real - time control is good dynamic combination and cooperation between multiple task 由于实时算法中多任务并行的特点,各个并行任务间良好的动态联合与协同作业成为高效准确地实现实时控制任务的关键。 |
| 6. | I recommend that you evaluate the virtual storage capacity and constraints in your z os environment , and adjust this parameter as needed , so that db2 will not create more parallel tasks than your virtual storage can handle 我建议您先估计z / os环境中的虚拟存储能力和局限性,这样db2就不至于创建多于虚拟存储所能处理的并行任务。 |
| 7. | For example , an application consisting of many independent parallel tasks executes much faster when the tasks are spread across a large number of compute resources than by using a single server or cluster 例如,与使用单个服务器或群集执行的执行速度相比,包含多个独立并行任务的应用程序在将任务划分到大量计算资源上,其执行速度要更快一些。 |
| 8. | We tried to understand where all the time goes when performing calculations in a grid computing environment and why , even with an extremely parallel job , there is a finite limit beyond which we cannot reduce the calculation time 中,我们试图理解在网格计算环境中执行计算时,所有的时间都花费到什么地方去了,以及为什么即使我们采用了大量的并行任务,可以减少的计算时间也是有限的? |
| 9. | Then , this thesis implements this system by the design of the architecture , and chiefly describes the parallel - job scheduling model of the loading system , implement the coordinated scheduling between the loading tasks in multi - resource database system 而后本文基于该体系结构设计并实现了该系统,并着重描述了加载系统的并行任务调度模块,实现了多资源数据库系统下的加载任务之间的协同调度。 |
| 10. | We spent some time trying to understand where the time goes when performing a calculations in a grid computing environment and why , even with a parallel job , there is a finite limit beyond which we cannot reduce the calculation time 中,我们花了一些时间来试图理解在网格计算环境中执行计算时,所有的时间都花费到什么地方去了,以及为什么即使我们采用了大量的并行任务,可以减少的计算时间也是有限的? |