Workshop on Numerical Algorithms on Hybrid Architectures
- Venue and location
- The 10th International Conference on Parallel Processing and Applied Mathematics (PPAM 2013)
- Polish-Japanese Institute of Information Technology, Warsaw, Poland
- September 8-11, 2013
The workshop is devoted to numerical algorithms with the particular
attention to issues related to implementation of libraries for
efficient numerical algorithms on modern hybrid architectures.
- Jerzy Wasniewski, Danish Technical University Lyngby, Copenhagen, Denmark
- Przemyslaw Stpiczynski Maria Curie-Sklodowska University Lublin, Poland
Wednesday, September 9, 2013
15:20 AM - 15:40
- 9:30-9:55 Accelerating Dense Numerical Linear Algebra with Intel Xeon Phi (MIC) Coprocessors,
Piotr Luszczek, University of Tennessee, Knoxville, USA
Abstract. This paper presents the design and implementation of several fundamental dense
linear algebra (DLA) algorithms for multicore with Intel Xeon Phi Coprocessors.
In particular, we consider algorithms for solving linear systems.
Further, we give an overview of the
MAGMA MIC library, an open source, high performance library that
incorporates the developments presented, and in general provides to heterogeneous
architectures of multicore with coprocessors the DLA functionality of the popular
LAPACK library. The LAPACK-compliance simplifies the use of the MAGMA MIC library in
applications, while providing them with portably performant DLA. High
performance is obtained through use of the high-performance BLAS,
hardware-specific tuning, and a hybridization methodology
where we split the algorithm into computational tasks of various granularities.
Execution of those tasks is properly scheduled over the heterogeneous hardware
components by minimizing data movements and mapping algorithmic requirements to
the architectural strengths of the various heterogeneous hardware components.
Our methodology and programming techniques are incorporated into the MAGMA MIC API,
which abstracts the application developer from the specifics of the Xeon Phi architecture
and is therefore applicable to algorithms beyond the scope of DLA.
- Accelerating Dense Numerical Linear Algebra with Intel Xeon Phi (MIC) Coprocessors