%0 Conference Paper
%B VECPAR 2014
%D 2014
%T Heterogeneous Acceleration for Linear Algebra in Mulit-Coprocessor Environments
%A Azzam Haidar
%A Piotr Luszczek
%A Stanimire Tomov
%A Jack Dongarra
%K Computer science
%K factorization
%K Heterogeneous systems
%K Intel Xeon Phi
%K linear algebra
%X We present an efficient and scalable programming model for the development of linear algebra in heterogeneous multi-coprocessor environments. The model incorporates some of the current best design and implementation practices for the heterogeneous acceleration of dense linear algebra (DLA). Examples are given as the basis for solving linear systemsâ€™ algorithms â€“ the LU, QR, and Cholesky factorizations. To generate the extreme level of parallelism needed for the efficient use of coprocessors, algorithms of interest are redesigned and then split into well-chosen computational tasks. The tasks execution is scheduled over the computational components of a hybrid system of multi-core CPUs and coprocessors using a light-weight runtime system. The use of light-weight runtime systems keeps scheduling overhead low, while enabling the expression of parallelism through otherwise sequential code. This simplifies the development efforts and allows the exploration of the unique strengths of the various hardware components.
%B VECPAR 2014
%C Eugene, OR
%8 2014-06
%G eng