COMRAD-MPI:使用并行计算压缩大型基因组数据集-开源
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2021-05-29
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Future Advancements:
When the input data les are increased correspondingly the memory usage
is also increased. An alternate method for making it memory ecient is to
implement lock free hash table at the master node for the generation of
dictionary so that memory utilization can be drastically reduced. Similarly,
the most frequent k-mers can be identied using Bloom lters for the
creation of dictionary that improves the repeat identication in large
genomic dataset. These improvements were not included in the present
study but will be explored in the future.
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Plant Genome Data set
Memory in GB
Sl
no
Dataset
Descriptio
n Genomes
1 Dataset1 Malus domestica , Zeamays
2 Dataset 2 Malus domestica , Zeamays, solanum lycopersicum
3
Dataset 3
Malus domestica , Zeamays, solanum
lycopersicum,Citrussinensis
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Dataset 4
Malus domestica , Zeamays, solanum
lycopersicum,Citrussinensis, Oryzabrachyantha,
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Dataset 5
Malus domestica , Zeamays, solanum
lycopersicum,Citrussinensis, Oryzabrachyantha,
Fragaria vesca
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Dataset 6
Malus domestica , Zeamays, solanum
lycopersicum,Citrussinensis, Oryzabrachyantha,
Fragaria vesca, Arabidopsis thaliana
Figure 1: Memory Usage of Parallel computing approach for
Genome Compression during the experiment with Plant Genome
Data set.
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