Measuring Network Performance of Multi-Core Multi-Cluster (MCMCA) Norhazlina Hamid Supervisor: R J Walters and G B Wills PUBLIC SERVICE DEPARTMENT OF MALAYSIA

Outline  Introduction and Definition  Motivation  Related Work  Research Objectives  The Architecture  Methodology  Conclusion and Progress Work 2

Introduction  The emergence of High Performance computing (HPC) that includes Cluster computing has improved the availability of powerful computers and high speed network technologies.  The implementation of multi-core cluster as a platform of high performance network will supports high availability and enables scalability of the networks. 3

Definition  Multi-Core Multi-Cluster Architecture (MCMCA) is a collection of multiple multi- core cluster, interconnect by a network.  MCMCA are built from:  Cluster computing is a collection of computer, interconnect by a network which work together to form a single computer 4

Definition  A multi-core cluster is a cluster where some or all the nodes in the cluster have multi- core processors  Multi-cluster architecture is a multiple cluster system that is connected via the cluster interconnection networks 5 Cluster computi ng Multi- core process or Multi- cluster MCMCA

Motivation  Existing models do not address the potential performance of the interconnection networks within large-scale multi-core clusters.  A high communication latency of interconnection network can dramatically reduce the efficiency of the cluster system.  Scaling up by adding more processors to each cluster increase the processing power. 6

Related Works  Furhad et al. (2013) proposed the EnMesh topology to address the issue of communication delays that occur with long distance communication within the remote nodes of a NoC.  Mohsen et al. (2013) proposed a new mapping technique to assign parallel processes into processing cores of a multi- core cluster which based on queuing network modelling of a limited-size cluster. 7

Objectives  To propose a new architecture for multi- core multi-cluster.  To investigate the performance of interconnection networks of multi-core multi-cluster architecture.  To demonstrate the feasibility of the proposed architecture by computer simulation experiment and measurements. 8

The Architecture of MCMCA 9

Communication Network  There are five communication networks in MCMCA 1.IntrA-chip Communication network (AC) 2.IntEr-chip Communication network (EC) 3.IntrA-Cluster Network (ACN) 4.IntEr-Cluster Network (ECN) 5.Multi-Cluster Network (MCN) 10

IntrA-chip Communication network (AC) 11 Message passing between two processor cores on the same chip

IntEr-chip Communication network (EC) 12 Message passing across processors on different chips but within a node

IntrA-Cluster Network (ACN) 13 Message passing between processors on different nodes but within the same cluster

Communication Network 14 Message passing between clusters

Methodology  Computer simulation experiments using OMNeT network simulation tool.  Focus on network latency to measure the performance.  Early stage experiments are based on a single-core multi-cluster architecture.  The experiments have been performed using given configuration and parameters of previous paper to create baseline results. 15

Experiment Results  Results from the experiments have shown that as the traffic rate increases, the average communication latency increases following the assumptions that the messages are delayed by having to wait for resources before traversing into a network.  The results confirm that the simulation model is a good basis to measure the communication latency for a large-scale cluster, and can be extended to multi-core multi-cluster architecture. 16

Methodology  Network Latency (∑NL) are obtained from: – Total Network Latency of Message Passing Within Cluster (L  ) – Total Network Latency of Message Passing Between Clusters (L  ) – Probability of outgoing message in a cluster (P) – Probability of message in a cluster (1-P)  Analytical Formula: ∑NL = ( L  x (1-P)) + ( L  x P) 17

Methodology  Both Network Latency (L  and L  ) are obtained from: – Waiting time at the source node (W) – Delay while traversing the network(D) – Time for each packet to reach its destination node (E) – Waiting time at transfer switch between clusters ( Wts)  Analytical Formula: L  = W  + D  + E  L  = W  + D  + E  + 2Wts 18

Conclusion  Presenting a new architecture for measuring the performance of interconnection networks in MCMCA.  Progress work: 1.Developing a MCMCA simulation model. 2.Conduct a simulation experiments with different network technology and bandwidth. 3.Developing analytical equation for the architecture. 19

Published Paper 1.Hamid, Norhazlina, Walters, Robert John and Wills, Gary Brian (2014) Performance evaluation of multi-core multi-cluster architecture. In, Emerging Software as a Service and Analytics, Barcelona, ES, Apr Scitepress9pp, Performance evaluation of multi-core multi-cluster architecture. 2.Hamid, Norhazlina, Walters, Robert John and Wills, Gary Brian, " An Architecture for Measuring Network Performance in Multi- Core Multi-Cluster Architecture (MCMCA). In, Euro-Asia Conference on Computational Intelligence and Communication Networks, Antalya, Turkey, Apr 2014." 3.Hamid, Norhazlina, Walters, Robert John and Wills, Gary Brian, " An Architecture for Measuring Network Performance in Multi- Core Multi-Cluster Architecture (MCMCA)," International Journal of Computer Theory and Engineering vol. 7, no. 1, pp , February

Q & A Thank you. 21

22 Queuing in the network

23 Illustration of message passing in simulation model

Results & Discussion  Experiments of single-core multi-cluster simulation model have been performed with 8-single-core cluster.  Two case have been examined as follow: 24 CASE 1CASE 2 Message Length (M) = 32 flitsMessage Length (M) = 64 flits Flit Length (F) = 256 and 512 bytes

Results & Discussion  The results obtained from the single-core multi-cluster architecture closely match the results from the published model when compared. 25

Related Works  Wu et al. (2012) present a new analytical model for prediction of communication networks performance in multi-cluster systems in the presence of the spatio- temporal bursty traffic.  Wang et al. (2012) extended a multithreaded PDES simulator to support multi-core cluster and investigate the impact of communication latency in multi- core cluster environment. 26