Distribution of metadata in a metadata server cluster is important in mass storage system. A good distribution algorithm has a significant influence on the system performance, availability and scalability. Subtree par...Distribution of metadata in a metadata server cluster is important in mass storage system. A good distribution algorithm has a significant influence on the system performance, availability and scalability. Subtree partition and hash are two traditional metadata distribution algorithms used in distributed file systems. They both have a defect in system scalability. This paper proposes a new directory hash (DH) algorithm. By treating directory as the key value of hash function, implementing concentrated storage of metadata, pipelining operations and prefetching technology, DH algorithm can enhance the system scalability on the premise without sacrificing system performance.展开更多
Particle-resolved direct numerical flow solvers predominantly use a projection method to decouple the non-linear mass and momentum conservation equations.The computing performance of such solvers often decays beyond O...Particle-resolved direct numerical flow solvers predominantly use a projection method to decouple the non-linear mass and momentum conservation equations.The computing performance of such solvers often decays beyond O(1000)cores due to the cost of solving at least one large three-dimensional pressure Poisson problem per time step.The parallelization may perform moderately well only or even poorly sometimes despite using an efficient algebraic multigrid preconditioner[38].We present an accurate and scalable solver using a direction splitting algorithm[12]to transform all three-dimensional parabolic/elliptic problems(and in particular the elliptic pressure Poisson problem)into a sequence of three one-dimensional parabolic sub-problems,thus improving its scalability up to multiple thousands of cores.We employ this algorithm to solve mass and momentum conservation equations in flows laden with fixed non-spherical rigid bodies.We consider the presence of rigid bodies on the(uniform or non-uniform)fixed Cartesian fluid grid by modifying the diffusion and divergence stencils on the impacted grid node near the rigid body boundary.Compared to[12],we use a higher-order interpolation scheme for the velocity field to maintain a secondorder stress estimation on the particle boundary,resulting in more accurate dimensionless coefficients such as drag C_(d)and lift C_(l).We also correct the interpolation scheme due to the presence of any nearby particle to maintain an acceptable accuracy,making the solver robust even when particles are densely packed in a sub-region of the computational domain.We present classical validation tests involving a single or multiple(up to O(1000))rigid bodies and assess the robustness,accuracy and computing speed of the solver.We further show that the Direction Splitting solver is∼5 times faster on 5120 cores than our solver[38]based on a classical projection method[5].展开更多
基金Project supported by the National Grand Fundamental Research 973 Program of China (Grant No.2004CB318203), and the National Natural Science Foundation of China (Grant No.60603074)
文摘Distribution of metadata in a metadata server cluster is important in mass storage system. A good distribution algorithm has a significant influence on the system performance, availability and scalability. Subtree partition and hash are two traditional metadata distribution algorithms used in distributed file systems. They both have a defect in system scalability. This paper proposes a new directory hash (DH) algorithm. By treating directory as the key value of hash function, implementing concentrated storage of metadata, pipelining operations and prefetching technology, DH algorithm can enhance the system scalability on the premise without sacrificing system performance.
基金support of the University of British Columbia via its Four Year Doctoral Fellowship programThe authors greatly appreciate the financial support of the Natural Sciences and Engineering Research Council of Canada(NSERC)via Anthony Wachs’s Discovery Grant RGPIN-2016-06572+1 种基金This research was enabled by the support provided by Compute Canada(http://www.computecanada.ca)through Anthony Wachs’s 2020,2021,and 2022 Resources for Research Groups allocation qpf-764-abThis research was also supported in part through computational resources and services provided by Advanced Research Computing at the University of British Columbia.
文摘Particle-resolved direct numerical flow solvers predominantly use a projection method to decouple the non-linear mass and momentum conservation equations.The computing performance of such solvers often decays beyond O(1000)cores due to the cost of solving at least one large three-dimensional pressure Poisson problem per time step.The parallelization may perform moderately well only or even poorly sometimes despite using an efficient algebraic multigrid preconditioner[38].We present an accurate and scalable solver using a direction splitting algorithm[12]to transform all three-dimensional parabolic/elliptic problems(and in particular the elliptic pressure Poisson problem)into a sequence of three one-dimensional parabolic sub-problems,thus improving its scalability up to multiple thousands of cores.We employ this algorithm to solve mass and momentum conservation equations in flows laden with fixed non-spherical rigid bodies.We consider the presence of rigid bodies on the(uniform or non-uniform)fixed Cartesian fluid grid by modifying the diffusion and divergence stencils on the impacted grid node near the rigid body boundary.Compared to[12],we use a higher-order interpolation scheme for the velocity field to maintain a secondorder stress estimation on the particle boundary,resulting in more accurate dimensionless coefficients such as drag C_(d)and lift C_(l).We also correct the interpolation scheme due to the presence of any nearby particle to maintain an acceptable accuracy,making the solver robust even when particles are densely packed in a sub-region of the computational domain.We present classical validation tests involving a single or multiple(up to O(1000))rigid bodies and assess the robustness,accuracy and computing speed of the solver.We further show that the Direction Splitting solver is∼5 times faster on 5120 cores than our solver[38]based on a classical projection method[5].