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Computing at LLNL advances scientific discovery through foundational and innovative research; mission-driven data science; complex modeling, simulation, and analysis on powerful supercomputers; and creative technologies and software solutions. Everything at Livermore is Team Science.
Extreme Parallel MPI Strong Scalability of a 2D Sedov Simulation with Very High-Order Finite Elements. Comparing extreme strong scaling results on 131,072 processors of LLNL's Vulcan computer for the 2D Sedov test problem using two different approaches for high-order parallel finite element computations: our default approach where high-order matrices are assembled and applied globally (left) and a new "action-based" approach where finite element matrices are computed and applied on the fly ...
Giorgis Georgakoudis: program analysis, compiler optimization (Clang/LLVM), parallel programming models and runtimes, performance analysis and tuning, fault tolerance. Maya Gokhale: data intensive computing, reconfigurable computing, co-processor accelerators, HPC architectures. Elena Green
Projects: Inspired R&D at the Heart of LLNL Computing Exascale-class systems will exhibit a new level of complexity, in terms of their underlying architectures and their system software. At the same time, the complexity of applications will rise sharply, both to implement new science possible at exascale and to exploit the new hardware features necessary to achieve exascale performance.
并行计算(Parallel Computing)是指同时使用多种计算资源解决计算问题的过程,是提高计算机系统计算速度和处理能力的一种有效手段。 它的基本思想是用多个处理器来协同求解同一问题,即将被求解的问题分解成若干个部分,各部分均由一个独立的处理机来并行计算。
"Highly Scalable Parallel Algorithms for Sparse Matrix Factorization," Parallel and Distributed Systems, IEEE Transactions on Volume 8, Issue 5, May 1997, pp. 502-520. 8) K. Thearling and S. Smith. "An Improved Supercomputer Sorting Benchmark," Conference on High Performance Networking and Computing, Proceedings of the 1992 ACM/IEEE conference on Supercomputing, pp. 14-19, 1992.
IEEE Transactions on Dependable and Secure Computing. 3. IEEE Transactions on parallel and distributed ...
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