Summary
The performance of sparse stiffness matrix‐vector multiplication is essential for large‐scale structural mechanics numerical simulation. Compressed sparse row (CSR) is the most common format for storing sparse stiffness matrices. However, the high sparsity of the sparse stiffness matrix makes the number of nonzero elements per row very small. Therefore, the CSR‐scalar algorithm, light algorithm, and HOLA algorithm in the calculation will cause some threads in the GPU to be in idle state, which will not only affect the computing performance but also waste computing resources. In this article, a new algorithm, CSR‐vector row, is proposed for fine‐grained computing optimization based on the AMD GPU architecture on heterogeneous supercomputers. This algorithm can set a vector to calculate a row based on the number of nonzero elements of the stiffness matrix. CSR‐vector row has efficient reduce operations, deep memory access optimization, better memory access, and calculation overlapping kernel function configuration scheme. The access bandwidth of the algorithm on AMD GPU is more than 700 GB/s. Compared with CSR‐scalar algorithm, the parallel efficiency of CSR‐vector row is improved by 7.2 times. And floating‐point computing performance is 41%–95% higher than that of light algorithm and HOLA algorithm. In addition, CSR‐vector row is used to calculate the examples from CFD, electromagnetics, quantum chemistry, power network, and semiconductor process, the memory access bandwidth and double floating‐point performance are also improved compared with rocSPARSE‐CSR‐vector.
The reactor is an extreme environment of high temperature, high pressure, and high radiation dose. Damage accumulates in structural materials over service time. It will eventually lead to material failure, such as hardening, embrittlement, and swelling. The radiation damage accumulation is an inherent, complex, and multiscale process, which has been studied extensively with multiscale modeling and simulation methods. The rapid development of high-performance computing makes it possible to accurately operate multiscale simulation for the microstructure evolution of irradiated reactor materials. The European Union, the USA, and China have put great effort into this, and many related works have been carried out. This paper first outlines the basic application of multiscale modeling and simulation technology in understanding the effects of radiation on reactor structural materials. Then, some relevant projects carried out by the USA, the European Union, and China in recent years are summarized. Next, the paper focuses on three widely used simulation techniques at different scales: molecular dynamics, kinetic Monte Carlo, and cluster dynamics. For each method, some key developments in algorithms and computer implementations are reviewed. Finally, the comparison between them is discussed.
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