Cost-efficiency of Large-scale Electronic Structure Simulations with Intel Xeon Phi Processors

2019 ◽  
Author(s):  
Hoon Ryu ◽  
Seungmin Lee
Keyword(s):  
Electronic Structure ◽  
Cost Efficiency ◽  
Large Scale ◽  
Xeon Phi ◽  
Intel Xeon Phi ◽  
Intel Xeon

scholarly journals Implementation of an Agent-Based Parallel Tissue Modelling Framework for the Intel MIC Architecture

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Maciej Cytowski ◽  
Zuzanna Szymańska ◽  
Piotr Umiński ◽  
Grzegorz Andrejczuk ◽  
Krzysztof Raszkowski
Keyword(s):  
High Performance ◽  
Large Scale ◽  
Spatial Scales ◽  
Biological Processes ◽  
Xeon Phi ◽  
Intel Xeon Phi ◽  
Variable Environment ◽  
Modelling Framework ◽  
Computational Performance ◽  
Intel Xeon

Timothy is a novel large scale modelling framework that allows simulating of biological processes involving different cellular colonies growing and interacting with variable environment. Timothy was designed for execution on massively parallel High Performance Computing (HPC) systems. The high parallel scalability of the implementation allows for simulations of up to 109 individual cells (i.e., simulations at tissue spatial scales of up to 1 cm3 in size). With the recent advancements of the Timothy model, it has become critical to ensure appropriate performance level on emerging HPC architectures. For instance, the introduction of blood vessels supplying nutrients to the tissue is a very important step towards realistic simulations of complex biological processes, but it greatly increased the computational complexity of the model. In this paper, we describe the process of modernization of the application in order to achieve high computational performance on HPC hybrid systems based on modern Intel® MIC architecture. Experimental results on the Intel Xeon Phi™ coprocessor x100 and the Intel Xeon Phi processor x200 are presented.

Fast Epistasis Detection in Large-Scale GWAS for Intel Xeon Phi Clusters

2015 ◽  
Author(s):  
Glenn R. Luecke ◽  
Nathan T. Weeks ◽  
Brandon M. Groth ◽  
Marina Kraeva ◽  
Li Ma ◽  
...  
Keyword(s):  
Large Scale ◽  
Xeon Phi ◽  
Intel Xeon Phi ◽  
Intel Xeon

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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