scholarly journals An Experimental Evaluation of the OpenMP Thread Mapping for LU Factorisation on Xeon Phi Coprocessor and on Hybrid CPU-MIC Platform

2018 ◽  
Vol 19 (3) ◽  
pp. 259-274
Author(s):  
Beata Bylina ◽  
Jaroslaw Bylina
Keyword(s):  
Experimental Evaluation ◽  
Xeon Phi ◽  
Intel Xeon Phi ◽  
The Matrix ◽  
Execution Mode ◽  
Thread Mapping ◽  
System Characteristics ◽  
Intel Xeon

Efficient thread mapping relies upon matching the behaviour of the application with system characteristics. The main aim of this paper is to evaluate the influence of the OpenMP thread mapping on the computation performance of the matrix factorisations on Intel Xeon Phi coprocessor and hybrid CPU-MIC platforms. The authors consider parallel LU factorisations with and without pivoting, both from MKL (Math Kernel Library) library. The results show that the choice of thread affinity, the number of threads and the execution mode have a measurable impact on the performance and the scalability of the LU factorisations.

scholarly journals MILC Code Performance on High End CPU and GPU Supercomputer Clusters

2018 ◽  
Vol 175 ◽  
pp. 02009
Author(s):  
Carleton DeTar ◽  
Steven Gottlieb ◽  
Ruizi Li ◽  
Doug Toussaint
Keyword(s):  
Conjugate Gradient ◽  
Memory Hierarchy ◽  
Xeon Phi ◽  
Intel Xeon Phi ◽  
Code Performance ◽  
Recent Developments ◽  
Knights Landing ◽  
Many Core ◽  
Intel Xeon

With recent developments in parallel supercomputing architecture, many core, multi-core, and GPU processors are now commonplace, resulting in more levels of parallelism, memory hierarchy, and programming complexity. It has been necessary to adapt the MILC code to these new processors starting with NVIDIA GPUs, and more recently, the Intel Xeon Phi processors. We report on our efforts to port and optimize our code for the Intel Knights Landing architecture. We consider performance of the MILC code with MPI and OpenMP, and optimizations with QOPQDP and QPhiX. For the latter approach, we concentrate on the staggered conjugate gradient and gauge force. We also consider performance on recent NVIDIA GPUs using the QUDA library.

Performance Evaluation of NAS Parallel Benchmarks on Intel Xeon Phi

2013 ◽  
Author(s):  
Arunmoezhi Ramachandran ◽  
Jerome Vienne ◽  
Rob Van Der Wijngaart ◽  
Lars Koesterke ◽  
Ilya Sharapov
Keyword(s):  
Performance Evaluation ◽  
Xeon Phi ◽  
Intel Xeon Phi ◽  
Intel Xeon

Modern Code Applied in Stencil in Edge Detection of an Image for Architecture Intel Xeon Phi KNL

2019 ◽  
pp. 151-163
Author(s):  
Mario Hernández-Hernández ◽  
José Luis Hernández-Hernández ◽  
Edilia Rodríguez Maldonado ◽  
Israel Herrera Miranda
Keyword(s):  
Edge Detection ◽  
Xeon Phi ◽  
Intel Xeon Phi ◽  
Intel Xeon
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