The Impact of Multicore on Math Software
The Impact of Multicore on Math Software
复制标题
多核对数学软件的影响
DOI：
10.1007/978-3-540-75755-9_1
复制
发表时间：
2006
影响因子：
5.4
通讯作者：
S. Tomov
中科院分区：
文献类型：
--
作者：
A. Buttari;J. Dongarra;J. Kurzak;J. Langou;P. Luszczek;S. Tomov
功耗和散热问题正在推动微处理器行业走向多核设计模式。考虑到内核频率和功耗之间的立方关系，多核技术利用了将内核数量增加一倍和内核频率减半可实现大致相同的性能的想法，将功耗降低了四倍。随着多核芯片上的核数量预计在几年内达到数十个，使用共享内存编程模型的高效数值库的实现引起了人们的高度兴趣。ScaLAPACK和其他地方使用的当前消息传递范例引入了不必要的内存开销和内存复制操作，这会降低性能，并使调度可以并行完成的操作变得更加困难。将共享内存的使用限制为fork-Join并行性(可能使用OpenMP)或在BLAS中使用共享内存并不能解决所有这些问题。
Power consumption and heat dissipation issues are pushing the microprocessors industry towards multicore design patterns. Given the cubic dependence between core frequency and power consumption, multicore technologies leverage the idea that doubling the number of cores and halving the cores frequency gives roughly the same performance reducing the power consumption by a factor of four. With the number of cores on multicore chips expected to reach tens in a few years, efficient implementations of numerical libraries using shared memory programming models is of high interest. The current message passing paradigm used in ScaLAPACK and elsewhere introduces unnecessary memory overhead and memory copy operations, which degrade performance, along with the making it harder to schedule operations that could be done in parallel. Limiting the use of shared memory to fork-join parallelism (perhaps with OpenMP) or to its use within the BLAS does not address all these issues.