Redirigiendo al acceso original de articulo en 22 segundos...
ARTÍCULO
TITULO

Performance Assessment of InfiniBand HPC Cloud Instances on Intel Haswell and Intel Sandy Bridge Architectures

Jonathan Low    
Jakub Chrzeszczyk    
Andrew Howard    
Andrzej Chrzeszczyk    

Resumen

This paper aims to establish a performance baseline of a HPC installation of OpenStack. We created InfiniCloud - a distributed High Performance Cloud hosted on remote nodes of InfiniCortex. InfiniCloud compute nodes use high performance Intel (R) Haswell and Sandy Bridge CPUs, SSD storage and 64-256GB RAM. All computational resources are connected by high performance IB interconnects and are capable of trans-continental IB communication using Obsidian Longbow range extenders.We benchmark the performance of our test-beds using micro-benchmarks for TCP bandwidth, IB bandwidth and latency, file creation performance, MPI collectives and Linpack. This paper compares different CPU generations across virtual and bare-metal environments.The results show modest improvements in TCP and IB bandwidth and latency on Haswell; performance being largely dependent on the IB hardware. Virtual overheads were minimal and near-native performance is possible for sufficiently large messages. From the Linpack testing, users can expect more than twice the performance in their applications on Haswell-provisioned VMs. On Haswell hardware, native and virtual performance differences is still significant for MPI collective operations. Finally, our parallel filesystem testing revealed virtual performance coming close to native only for non-sync/fsync file operations.

 Artículos similares

       
 
Johannes Hofmann,Christie L. Alappat,Georg Hager,Dietmar Fey,Gerhard Wellein     Pág. 54 - 78
We propose several improvements to the execution-cache-memory (ECM) model, an analytic performance model for predicting single- and multicore runtime of steady-state loops on server processors. The model is made more general by strictly differentiating b... ver más

 
David Goz, Georgios Ieronymakis, Vassilis Papaefstathiou, Nikolaos Dimou, Sara Bertocco, Francesco Simula, Antonio Ragagnin, Luca Tornatore, Igor Coretti and Giuliano Taffoni    
New challenges in Astronomy and Astrophysics (AA) are urging the need for many exceptionally computationally intensive simulations. ?Exascale? (and beyond) computational facilities are mandatory to address the size of theoretical problems and data coming... ver más
Revista: Computation

 
Hyundo Yoon, Soojung Moon, Youngki Kim, Changhee Hahn, Wonjun Lee and Junbeom Hur    
Public key encryption with keyword search (PEKS) enables users to search over encrypted data outsourced to an untrusted server. Unfortunately, updates to the outsourced data may incur information leakage by exploiting the previously submitted queries. Pr... ver más
Revista: Applied Sciences

 
Yuzhu Wang, Yuan Zhao, Jinrong Jiang and He Zhang    
Graphics processing unit (GPU)-based computing for climate system models is a longstanding research area of interest. The rapid radiative transfer model for general circulation models (RRTMG), a popular atmospheric radiative transfer model, can calculate... ver más
Revista: Applied Sciences

 
Kunal Banerjee,Evangelos Georganas,Dhiraj D. Kalamkar,Barukh Ziv,Eden Segal,Cristina Anderson,Alexander Heinecke     Pág. 64 - 85
Recurrent neural network (RNN) models have been found to be well suited for processing temporal data. In this work, we present an optimized implementation of vanilla RNN cell and its two popular variants: LSTM and GRU for Intel Xeon architecture. Typical... ver más