TH-A-19A-08: Intel Xeon Phi Implementation of a Fast Multi-Purpose Monte Carlo Simulation for Proton Therapy

2014 ◽  
Vol 41 (6Part31) ◽  
pp. 535-535 ◽  
Author(s):  
K Souris ◽  
J Lee ◽  
E Sterpin
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Proton Therapy ◽  
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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