Pecero, J.E., Bouvry, P.: An improved genetic algorithm for efficient scheduling on dis- tributed memory parallel systems. In: IEEE/ACS International Conference on Computer Systems and Applications, AICCSA 2010 (2010), doi:10.1109/AICCSA.2010.5587030...
Scheduling plays an important role in improving the performance of big data-parallel processing. Spark is an in-memory parallel computing framework that uses a multi-threaded model in task scheduling. Most Spark task scheduling processes do not take the memory into account, but the number of concu...
Dask is a flexible parallel computing library for analytics. See documentation for more information. LICENSE New BSD. See License File.About Parallel computing with task scheduling dask.org Topics python numpy scikit-learn pydata pandas scipy dask Resources Readme License BSD-3-Clause license ...
Scheduling plays an important role in improving the performance of big data-parallel processing. Spark is an in-memory parallel computing framework that uses a multi-threaded model in task scheduling. Most Spark task scheduling processes do not take the memory into account, but the number of concu...
Cao. An online parallel scheduling method with application to energy-efficiency in cloud computing. J. Supercomput., 66(3):1773-1790, Dec. 2013.Tian, Wenhong, Qin Xiong, and Jun Cao(2013)." An online parallel scheduling method with application to energy-efficiency in cloud computing.& quot...
O. Plata and F. F. Rivera. Combining static and dynamic scheduling on distributedmemory multiprocessors. InProc. of the 1994 ACM Int. Conf. on Supercomputing, pages 186–195, 1994. J. Saltz et al. Runtime and Language Support for Compiling Adaptive Irregular Programs on Distributed Memory Mac...
It can be seen that other factors such as memory, hard disk, and network interface have a very small impact on total power consumption. In Ref. [19], authors find that CPU utilization is typically proportional to the overall system load and propose a power model defined in Eq. (6.2): ...
Second, to optimize system throughput, PAR-BS employs a parallelism-aware DRAM scheduling policy that aims to process requests from a thread in parallel in the DRAM banks, thereby reducing the memory-related stall-time experienced by the thread. PAR-BS seamlessly incorporates ...
When parallelizing loop nests for distributed memory parallel computers, we have to specify when the different computations are carried out (computation scheduling), where they are carried out (computation mapping), and where the data are stored (data mapping). We show that even the “best” sch...
1. In a computing system having a processor, a memory and a kernel level scheduler, wherein the processor includes a user mode and a protected kernel mode, a method of scheduling a plurality of threads from a multi-threaded program for execution in user mode, wherein the multi-threaded pro...