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GTC On-Demand

Developer - Algorithms
Presentation
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DAG-Scheduled Linear Algebra Using Template-Based Building Blocks
Jonathan Hogg (Science and Technology Faciliities Council)
We describe our experiences using DAG-driven algorithms built from templated BLAS-like building blocks to implement LAPACK-like functionality at the single kernel level. There will be a particular focus on strong scaling of multiple small dense facto ...Read More
We describe our experiences using DAG-driven algorithms built from templated BLAS-like building blocks to implement LAPACK-like functionality at the single kernel level. There will be a particular focus on strong scaling of multiple small dense factorizations, as required for sparse direct methods. The main objective is to overlap expensive latency-bound pivoting operations with highly parallel matrix-matrix multiplication operations. As the later are dependent on the output of previous pivoting decisions, a directed-acyclic graph (DAG) scheduler is implemented using global memory to manage fine-grained inter-block parallelism.  Back
 
Keywords:
Developer - Algorithms, Developer - Tools & Libraries, GTC 2015 - ID S5316
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Numerical Algorithms & Libraries
Presentation
Media
A GPU Sparse Direct Solver for AX=B
Jonathan Hogg (Science and Technology Facilities Council (STFC))
The solution of Ax=b for sparse A is one of the core computation kernels ("dwarves") used in scientific computing. While there are many GPU iterative methods libraries available, these can only tackle a limited range of problems due to prec ...Read More
The solution of Ax=b for sparse A is one of the core computation kernels ("dwarves") used in scientific computing. While there are many GPU iterative methods libraries available, these can only tackle a limited range of problems due to preconditioning requirements. On the CPU, black box direct solvers are often the first port of call for more challenging problems, however little GPU support is present in existing libraries. We present a new direct solver library capable of performing entirely on GPU factorization and solve for symmetric problems. The talk will cover our solution to a number of the challenges involved in making this reality, and present results across a number of application areas including FEM and Optimization.   Back
 
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Numerical Algorithms & Libraries, GTC 2014 - ID S4243
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