@article {1189, title = {Symmetric Indefinite Linear Solver using OpenMP Task on Multicore Architectures}, journal = {IEEE Transactions on Parallel and Distributed Systems}, volume = {29}, year = {2018}, month = {2018-08}, pages = {1879{\textendash}1892}, abstract = {Recently, the Open Multi-Processing (OpenMP) standard has incorporated task-based programming, where a function call with input and output data is treated as a task. At run time, OpenMP{\textquoteright}s superscalar scheduler tracks the data dependencies among the tasks and executes the tasks as their dependencies are resolved. On a shared-memory architecture with multiple cores, the independent tasks are executed on different cores in parallel, thereby enabling parallel execution of a seemingly sequential code. With the emergence of many-core architectures, this type of programming paradigm is gaining attention-not only because of its simplicity, but also because it breaks the artificial synchronization points of the program and improves its thread-level parallelization. In this paper, we use these new OpenMP features to develop a portable high-performance implementation of a dense symmetric indefinite linear solver. Obtaining high performance from this kind of solver is a challenge because the symmetric pivoting, which is required to maintain numerical stability, leads to data dependencies that prevent us from using some common performance-improving techniques. To fully utilize a large number of cores through tasking, while conforming to the OpenMP standard, we describe several techniques. Our performance results on current many-core architectures-including Intel{\textquoteright}s Broadwell, Intel{\textquoteright}s Knights Landing, IBM{\textquoteright}s Power8, and Arm{\textquoteright}s ARMv8-demonstrate the portable and superior performance of our implementation compared with the Linear Algebra PACKage (LAPACK). The resulting solver is now available as a part of the PLASMA software package.}, keywords = {linear algebra, multithreading, runtime, symmetric indefinite matrices}, doi = {10.1109/TPDS.2018.2808964}, author = {Ichitaro Yamazaki and Jakub Kurzak and Panruo Wu and Mawussi Zounon and Jack Dongarra} }