Design and Implementation of the Linpack Benchmark for Single and Multi-node Systems Based on Intel® Xeon Phi Coprocessor

Author(s):  
Alexander Heinecke ◽  
Karthikeyan Vaidyanathan ◽  
Mikhail Smelyanskiy ◽  
Alexander Kobotov ◽  
Roman Dubtsov ◽  
...  
2009 ◽  
Vol 17 (1-2) ◽  
pp. 43-57 ◽  
Author(s):  
Michael Kistler ◽  
John Gunnels ◽  
Daniel Brokenshire ◽  
Brad Benton

In this paper we present the design and implementation of the Linpack benchmark for the IBM BladeCenter QS22, which incorporates two IBM PowerXCell 8i1processors. The PowerXCell 8i is a new implementation of the Cell Broadband Engine™2 architecture and contains a set of special-purpose processing cores known as Synergistic Processing Elements (SPEs). The SPEs can be used as computational accelerators to augment the main PowerPC processor. The added computational capability of the SPEs results in a peak double precision floating point capability of 108.8 GFLOPS. We explain how we modified the standard open source implementation of Linpack to accelerate key computational kernels using the SPEs of the PowerXCell 8i processors. We describe in detail the implementation and performance of the computational kernels and also explain how we employed the SPEs for high-speed data movement and reformatting. The result of these modifications is a Linpack benchmark optimized for the IBM PowerXCell 8i processor that achieves 170.7 GFLOPS on a BladeCenter QS22 with 32 GB of DDR2 SDRAM memory. Our implementation of Linpack also supports clusters of QS22s, and was used to achieve a result of 11.1 TFLOPS on a cluster of 84 QS22 blades. We compare our results on a single BladeCenter QS22 with the base Linpack implementation without SPE acceleration to illustrate the benefits of our optimizations.


2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Jack Dongarra ◽  
Mark Gates ◽  
Azzam Haidar ◽  
Yulu Jia ◽  
Khairul Kabir ◽  
...  

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 here and, more broadly, provides the DLA functionality equivalent to that of the popular LAPACK library while targeting heterogeneous architectures that feature a mix of multicore CPUs and coprocessors. 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 the use of the high-performance BLAS, hardware-specific tuning, and a hybridization methodology whereby we split the algorithm into computational tasks of various granularities. Execution of those tasks is properly scheduled over the heterogeneous hardware 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.


2015 ◽  
Vol 24 (3) ◽  
pp. 106-113 ◽  
Author(s):  
Stephen N. Calculator

Purpose To provide an overview of communication characteristics exhibited by individuals with Angelman Syndrome (AS) and special considerations associated with the design and implementation of augmentative and alternative communication (AAC) programs. Method Results of recent studies exploring individuals' uses of AAC are reviewed, with particular emphasis on factors related to individuals' acceptance and successful uses of AAC systems. Results Not applicable Conclusion Despite their inconsistent access to practices previously found to foster individuals' acceptance of AAC systems, individuals with AS demonstrate the ability to use AAC systems, including high-tech AAC devices, successfully.


2017 ◽  
Author(s):  
Alicia Papas ◽  
Anthony D. LaMontagne ◽  
Allison J. Milner ◽  
Amanda Allisey ◽  
Andrew J. Noblet ◽  
...  

2015 ◽  
Vol 6 (4) ◽  
pp. 171-184
Author(s):  
Liangbo Xie ◽  
Jiaxin Liu ◽  
Yao Wang ◽  
Chuan Yin ◽  
Guangjun Wen

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