scholarly journals A method of two-level parallelization of the Thomas algorithm for solving tridiagonal linear systems on hybrid computers with multicore coprocessors

2016 ◽  
pp. 234-244
Author(s):  
А.А. Федоров ◽  
А.Н. Быков
Keyword(s):  
Linear Systems ◽  
Three Dimensional ◽  
Multiprocessor Systems ◽  
Xeon Phi ◽  
Intel Xeon Phi ◽  
Thomas Algorithm ◽  
Arithmetic Complexity ◽  
Thread Level Parallelism ◽  
Level Parallelism ◽  
Intel Xeon

Приводится описание метода двухуровневого распараллеливания прогонки (на общей памяти средствами OpenMP и на распределенной памяти средствами MPI) для решения трехдиагональных линейных систем, возникающих при моделировании двумерных и трехмерных физических процессов. Анализируются особенности реализации метода как на ЭВМ с универсальными процессорами, так и на гибридных ЭВМ с многоядерными сопроцессорами Intel Xeon Phi. Оценивается арифметическая сложность реализованного метода. Обсуждаются результаты численных экспериментов по исследованию масштабируемости метода. A method of two-level parallelization of the Thomas algorithm for solving tridiagonal linear systems (the thread-level parallelism using OpenMP and the process-level parallelism using MPI) arising when modeling two-dimensional and three-dimensional physical processes is described. The features of its implementation for parallel multiprocessor systems and for hybrid multiprocessor systems with multicore coprocessors Intel Xeon Phi are analyzed. The arithmetic complexity of this method is estimated. Some numerical results obtained when studying its scalability are discussed.

scholarly journals Optimization of throughput, fairness and energy efficiency on asymmetric multicore systems via OS scheduling.

2018 ◽  
Vol 18 (01) ◽  
pp. e09
Author(s):  
Adrian Pousa
Keyword(s):  
Energy Efficiency ◽  
Chip Multiprocessors ◽  
Xeon Phi ◽  
Intel Xeon Phi ◽  
Multicore Systems ◽  
Lower Power ◽  
Thread Level Parallelism ◽  
Good For ◽  
Asymmetric Multicore ◽  
Level Parallelism

Most of chip multiprocessors (CMPs) are symmetric, i.e. they are composed of identical cores. These CMPs may consist of complex cores (e.g., Intel Haswell or IBM Power8) or simple and lower-power cores (e.g. ARM Cortex A9 or Intel Xeon Phi). Cores in the former approach have advanced microarchitectural features, such as out-of-order super-scalar pipelines, and they are suitable for running sequential applications which use them efficiently. Cores in the latter approach have a simple microarchitecture and are good for running applications with high thread-level parallelism (TLP).

scholarly journals Three-dimensional particle-in-cell plasma simulation on Intel Xeon Phi: performance optimization and case study

2015 ◽  
pp. 486-500
Author(s):  
И.Б. Мееров ◽  
С.И. Бастраков ◽  
И.А. Сурмин ◽  
А.А. Гоносков ◽  
Е.С. Ефименко ◽  
...  
Keyword(s):  
Performance Optimization ◽  
Three Dimensional ◽  
Plasma Simulation ◽  
Computational Time ◽  
Xeon Phi ◽  
Intel Xeon Phi ◽  
Simulation Code ◽  
Particle In Cell ◽  
Cell Plasma ◽  
Intel Xeon

Рассматривается проблема эффективного использования ускорителей Xeon Phi при моделировании лазерной плазмы. Приводится анализ особенностей архитектуры Xeon Phi, влияющих на производительность кода при численном моделировании плазмы методом частиц в ячейках. Описывается параллельный программный комплекс PICADOR, оптимизированный ранее для расчетов на ускорителях. Производительность программного комплекса на Xeon Phi в сравнении с CPU исследуется при решении трех вычислительно трудоемких задач. Обсуждается соотношение времени расчета на Xeon Phi и CPU на разных этапах метода частиц в ячейках. Демонстрируется, что в зависимости от особенностей задачи Xeon Phi может как опережать, так и отставать от CPU при выполнении расчетов. An efficient application of computational systems equipped with Intel Xeon Phi coprocessors for the laser-plasma simulation is considered. The features of Xeon Phi architecture that influence the performance of Particle-in-Cell plasma simulation are analyzed. The PICADOR parallel plasma simulation code previously optimized for Xeon Phi is described. Its performance on Xeon Phi compared to CPU is studied on three computationally intensive plasma simulation problems. The ratio of computational time on Xeon Phi to CPU is discussed for the main stages of the Particle-in-Cell method. It is shown that, depending on the features of a physical problem, the use of Xeon Phi can be both advantageous and disadvantageous compared to CPU.

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
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