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—Stencil calculations comprise an important class of kernels in many scientific computing applications ranging from simple PDE solvers to constituent kernels in multigrid methods as well as image processing applications. In such types of solvers, stencil kernels are often the dominant part of the computation , and an efficient parallel implementation of the(More)
We report on our experience with integrating and using graphics processing units (GPUs) as fast parallel floating-point co-processors to accelerate two fundamental computational scientific kernels on the GPU: sparse direct factorization and nonlinear interior-point optimization. Since a full re-implementation of these complex kernels is typically not(More)
We present a PDE-constrained optimization algorithm which is designed for parallel scalability on distributed-memory architectures with thousands of cores. The method is based on a line-search interior-point algorithm for large-scale continuous optimization, it is matrix-free in that it does not require the factorization of derivative matrices. Instead, it(More)
In this paper, we present PATUS, a code generation and auto-tuning framework for stencil computations targeted at multi-and manycore processors, such as mul-ticore CPUs and graphics processing units. PATUS, which stands for " Parallel Autotuned Stencils, " generates a compute kernel from a specification of the stencil operation and a strategy which(More)
Patus is a code generation and auto-tuning framework for stencil computations targeting modern multi and many-core processors. The goals of the framework are productivity and portability for achieving high performance on the target platform. Its stencil specification language allows the programmer to express the computation in a concise way independently of(More)
Individual cell heterogeneity is commonly observed within populations, although its molecular basis is largely unknown. Previously, using FRET-based microscopy, we observed heterogeneity in cellular c-di-GMP levels. In this study, we show that c-di-GMP heterogeneity in Pseudomonas aeruginosa is promoted by a specific phosphodiesterase partitioned after cell(More)
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