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.
Original language | English |
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Title of host publication | Parallel Processing and Applied Mathematics - 10th International Conference, PPAM 2013, Revised Selected Papers |
Publisher | Springer Verlag |
Pages | 571-581 |
Number of pages | 11 |
Edition | PART 1 |
ISBN (Print) | 9783642552236 |
DOIs | |
State | Published - 2014 |
Event | 10th International Conference on Parallel Processing and Applied Mathematics, PPAM 2013 - Warsaw, Poland Duration: Sep 8 2013 → Sep 11 2013 |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Number | PART 1 |
Volume | 8384 LNCS |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | 10th International Conference on Parallel Processing and Applied Mathematics, PPAM 2013 |
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Country/Territory | Poland |
City | Warsaw |
Period | 09/8/13 → 09/11/13 |
Funding
The authors would like to thank the National Science Foundation, the Department of Energy and ISTC for Big Data for supporting this research effort.
Keywords
- Communication and computation overlap
- Dynamic runtime scheduling using dataflow dependences
- Hardware accelerators and coprocessors
- Intel Xeon Phi processor
- Many Integrated Cores
- Numerical linear algebra