<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Expression of gene block, with the GPU parallel thread structure characteristic calculation, according to the structural characteristics of GPU thread design of double parallel mode, and the use of texture cache memory to achieve high efficiency; on the basis of CPU two level cache capacity of basic blocks further subdivided into sub blocks to improve the cache hit rate, the technology to reduce the number of memory accesses the use of data, reduce the thread migration in the core between the use of thread binding technology; according to the calculated capacity allocation of multi-core CPU and GPU CPU and GPU gene in the mutual information calculation task to calculate the load balance of CPU and GPU; in the design of the new threshold calculation algorithm based on the design and implementation of memory efficient construction of global gene control network CPU /GPU parallel algorithm. The experimental results show that compared with the existing algorithms, this algorithm speed is more obvious, and is able to build more large-scale global gene regulation Control network.</p>
</abstract>

Expression of gene block, with the GPU parallel thread structure characteristic calculation, according to the structural characteristics of GPU thread design of double parallel mode, and the use of texture cache memory to achieve high efficiency; on the basis of CPU two level cache capacity of basic blocks further subdivided into sub blocks to improve the cache hit rate, the technology to reduce the number of memory accesses the use of data, reduce the thread migration in the core between the use of thread binding technology; according to the calculated capacity allocation of multi-core CPU and GPU CPU and GPU gene in the mutual information calculation task to calculate the load balance of CPU and GPU; in the design of the new threshold calculation algorithm based on the design and implementation of memory efficient construction of global gene control network CPU /GPU parallel algorithm. The experimental results show that compared with the existing algorithms, this algorithm speed is more obvious, and is able to build more large-scale global gene regulation Control network.

Inferring Genome-Wide Gene Regulatory Networks with GPU or CPU Parallel Algorithm

International Journal of Advanced Network, Monitoring and Controls

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Expression of gene block, with the GPU parallel thread structure characteristic calculation, according to the structural characteristics of GPU thread design...

Inferring Genome-Wide Gene Regulatory Networks with GPU or CPU Parallel Algorithm

Online veröffentlicht: 10. Apr. 2018

Seitenbereich: 15 - 19

DOI: https://doi.org/10.21307/ijanmc-2017-084

Schlüsselwörter
Genome-wide, Gene regulatory network, CPU/GPU cooperative computing, Efficient access cache, Parallel algorithm

© 2017 Ming Zheng et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Inferring Genome-Wide Gene Regulatory Networks with GPU or CPU Parallel Algorithm

Online veröffentlicht: 10. Apr. 2018

Seitenbereich: 15 - 19

DOI: https://doi.org/10.21307/ijanmc-2017-084

SchlüsselwörterGenome-wide, Gene regulatory network, CPU/GPU cooperative computing, Efficient access cache, Parallel algorithm

© 2017 Ming Zheng et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Schlüsselwörter
Genome-wide, Gene regulatory network, CPU/GPU cooperative computing, Efficient access cache, Parallel algorithm