In unstructured finite volume method,loop on different mesh components such as cells,faces,nodes,etc is used widely for the traversal of data.Mesh loop results in direct or indirect data access that affects data local...In unstructured finite volume method,loop on different mesh components such as cells,faces,nodes,etc is used widely for the traversal of data.Mesh loop results in direct or indirect data access that affects data locality significantly.By loop on mesh,many threads accessing the same data lead to data dependence.Both data locality and data dependence play an important part in the performance of GPU simulations.For optimizing a GPU-accelerated unstructured finite volume Computational Fluid Dynamics(CFD)program,the performance of hot spots under different loops on cells,faces,and nodes is evaluated on Nvidia Tesla V100 and K80.Numerical tests under different mesh scales show that the effects of mesh loop modes are different on data locality and data dependence.Specifically,face loop makes the best data locality,so long as access to face data exists in kernels.Cell loop brings the smallest overheads due to non-coalescing data access,when both cell and node data are used in computing without face data.Cell loop owns the best performance in the condition that only indirect access of cell data exists in kernels.Atomic operations reduced the performance of kernels largely in K80,which is not obvious on V100.With the suitable mesh loop mode in all kernels,the overall performance of GPU simulations can be increased by 15%-20%.Finally,the program on a single GPU V100 can achieve maximum 21.7 and average 14.1 speed up compared with 28 MPI tasks on two Intel CPUs Xeon Gold 6132.展开更多
Poly-γ-glutamic acid is an extracellular polymeric substance with various applications owing to its valuable properties of biodegradability,flocculating activity,water solubility,and nontoxicity.However,the ability o...Poly-γ-glutamic acid is an extracellular polymeric substance with various applications owing to its valuable properties of biodegradability,flocculating activity,water solubility,and nontoxicity.However,the ability of natural strains to produce poly-γ-glutamic acid is low.Atmospheric and room temperature plasma was applied in this study to conduct mutation breeding of Bacillus licheniformis CGMCC 2876,and a mutant strain M32 with an 11%increase in poly-γ-glutamic acid was obtained.Genome resequencing analysis identified 7 nonsynonymous mutations of ppsC encoding lipopeptide synthetase associated with poly-γ-glutamic acid metabolic pathways.From molecular docking,more binding sites and higher binding energy were speculated between the mutated plipastatin synthase subunit C and glutamate,which might contribute to the higher poly-γ-glutamic acid production.Moreover,the metabolic mechanism analysis revealed that the upregulated amino acids of M32 provided substrates for glutamate and promoted the conversion between L-and D-glutamate acids.In addition,the glycolytic pathway is enhanced,leading to a better capacity for using glucose.The maximum poly-γ-glutamic acid yield of 14.08 g·L^(–1)was finally reached with 30 g·L^(–1)glutamate.展开更多
基金supported by National Numerical Wind tunnel project NNW2019ZT6-B18 and Guangdong Introducing Innovative&Entrepreneurial Teams under Grant No.2016ZT06D211.
文摘In unstructured finite volume method,loop on different mesh components such as cells,faces,nodes,etc is used widely for the traversal of data.Mesh loop results in direct or indirect data access that affects data locality significantly.By loop on mesh,many threads accessing the same data lead to data dependence.Both data locality and data dependence play an important part in the performance of GPU simulations.For optimizing a GPU-accelerated unstructured finite volume Computational Fluid Dynamics(CFD)program,the performance of hot spots under different loops on cells,faces,and nodes is evaluated on Nvidia Tesla V100 and K80.Numerical tests under different mesh scales show that the effects of mesh loop modes are different on data locality and data dependence.Specifically,face loop makes the best data locality,so long as access to face data exists in kernels.Cell loop brings the smallest overheads due to non-coalescing data access,when both cell and node data are used in computing without face data.Cell loop owns the best performance in the condition that only indirect access of cell data exists in kernels.Atomic operations reduced the performance of kernels largely in K80,which is not obvious on V100.With the suitable mesh loop mode in all kernels,the overall performance of GPU simulations can be increased by 15%-20%.Finally,the program on a single GPU V100 can achieve maximum 21.7 and average 14.1 speed up compared with 28 MPI tasks on two Intel CPUs Xeon Gold 6132.
基金This work was financially supported by the National Natural Science Foundation of China(Grant Nos.32170061 and 31871779).
文摘Poly-γ-glutamic acid is an extracellular polymeric substance with various applications owing to its valuable properties of biodegradability,flocculating activity,water solubility,and nontoxicity.However,the ability of natural strains to produce poly-γ-glutamic acid is low.Atmospheric and room temperature plasma was applied in this study to conduct mutation breeding of Bacillus licheniformis CGMCC 2876,and a mutant strain M32 with an 11%increase in poly-γ-glutamic acid was obtained.Genome resequencing analysis identified 7 nonsynonymous mutations of ppsC encoding lipopeptide synthetase associated with poly-γ-glutamic acid metabolic pathways.From molecular docking,more binding sites and higher binding energy were speculated between the mutated plipastatin synthase subunit C and glutamate,which might contribute to the higher poly-γ-glutamic acid production.Moreover,the metabolic mechanism analysis revealed that the upregulated amino acids of M32 provided substrates for glutamate and promoted the conversion between L-and D-glutamate acids.In addition,the glycolytic pathway is enhanced,leading to a better capacity for using glucose.The maximum poly-γ-glutamic acid yield of 14.08 g·L^(–1)was finally reached with 30 g·L^(–1)glutamate.
