Abstract. The emergence and continuing use of multi-core architectures and graphics processing units require changes in the existing software and sometimes even a redesign of the established algorithms in order to take advantage of now prevailing parallelism. Parallel Linear Algebra for Scalable Multi-core Architectures (PLASMA) and Matrix Algebra on GPU and Multics Architectures (MAGMA ) are two projects that aims to achieve high performance and portability across a wide range of multi-core architectures and hybrid systems respectively. We present in this document a comparative study of PLASMA's performance against established linear algebra packages and some preliminary results of MAGMA on hybrid multi-core and GPU systems.

The emergence and continuing use of multi-core architectures require changes in the existing software and sometimes even a redesign of the established algorithms in order to take advantage of now prevailing parallelism. The Parallel Linear Algebra for Scalable Multi-core Architectures (PLASMA) is a project that aims to achieve both high performance and portability across a wide range of multi-core architectures. We present in this paper a comparative study of PLASMA's performance against established linear algebra packages (LAPACK and ScaLAPACK), against new approaches at parallel execution (Task Based Linear Algebra Subroutines -TBLAS), and against equivalent commercial software offerings (MKL, ESSL and PESSL). Our experiments were conducted on one-sided linear algebra factorizations (LU, QR and Cholesky) and used multi-core architectures (based on Intel Xeon EMT64 and IBM Power6). The performance results show improvements brought by new algorithms on up to 32 cores -the largest multi-core system we could access.

In this paper we present scaling results of a FFT library, FFTK, and a pseudospectral code, Tarang, on grid resolutions up to 8192 3 grid using 65536 cores of Blue Gene/P and 196608 cores of Cray XC40 supercomputers. We observe that communication dominates computation, more so on the Cray XC40. The computation time scales as T comp ∼ p −1 , and the communication time as T comm ∼ n −γ2 with γ 2 ranging from 0.7 to 0.9 for Blue Gene/P, and from 0.43 to 0.73 for Cray XC40. FFTK, and the fluid and convection solvers of Tarang exhibit weak as well as strong scaling nearly up to 196608 cores of Cray XC40. We perform a comparative study of the performance on the Blue Gene/P and Cray XC40 clusters.

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Capsule Summary An integrated, high resolution, data-driven regional modeling system has been recently developed for the Red Sea region and is being used for research and various environmental applications.