1. © 2005, it - instituto de telecomunicações. Todos os direitos reservados. System Level Resource Discovery and Management for Multi Core Environment Javad Zarrin S(o)OS Project - CASTNESS'11 Roma, January17-18 2011

2. 2 Outline Introduction Challenges Resource Description Resource Discovery Resource Management Current SDPs Proposed Solution Simulation & Results COTSon HPL Conclusion System Level Resource Discovery & Management For Multi Core Environment 17 January 2011, CASTNESS’11

3. 3 Introduction Resource Discovery in So(o)S Project – Scenario – network topology for a cluster combined of n heterogeneous nodes with n CPUs ( n core per CPU), n>=100 System Level Resource Discovery & Management For Multi Core Environment 17 January 2011, CASTNESS’11 Core n Private Cache – L1 Shared Cache – L2

4. 4 Introduction Problems? Memory latency, Bandwidth Bottleneck, Interconnection Network Using all available resources in an efficient manner How to define resources as services? What is a resource? Core Chip Board Memory Chip Pluggable Device What are relevant? System Level Resource Discovery & Management For Multi Core Environment 17 January 2011, CASTNESS’11 Shared Cache – L2 Board and Memory Parameters Chip Parameters Core Parameters

5. 5 Challenges - Resource Description How to describe a resource? Resource description for a huge number of heterogeneous resources (cores) in an adequate and efficient manner. The heterogonous resources in the network needs to be defined by set of strict parameters, these parameters describe the characteristics and performance factors of the corresponded resources as services on the network. Example parameters> Clock rate, MIPS, GFLOPS, cache size, SPEC Benchmark, etc., System Level Resource Discovery & Management For Multi Core Environment 17 January 2011, CASTNESS’11

6. 6 Challenges - Resource Discovery Massive amount of resources Discovering all the existing cores on the local chip or on the network with a large scale is costly due to the excessive information exchange Scalable search for required resources Rate of Discovery Parallel search algorithms Packet Propagation System Level Resource Discovery & Management For Multi Core Environment 17 January 2011, CASTNESS’11

7. 7 Challenges - Resource Management Smart Resource Management What is the best resource for a specific requirement? What is the metric? Fault tolerance System Level Resource Discovery & Management For Multi Core Environment 17 January 2011, CASTNESS’11

8. 8 Service Discovery Protocols System Level Resource Discovery & Management For Multi Core Environment 17 January 2011, CASTNESS’11

9. 9 Service Discovery Protocols System Level Resource Discovery & Management For Multi Core Environment 17 January 2011, CASTNESS’11

10. 10 The Proposed Solution Architecture : combination of distributed and centralized Search : Informed -Heuristic Search Methods Message Propagation : Unicast, Anycast Announcement : Pull (Reactive, Query-based) in Network, Push (Proactive, Announcement-based) in Node Scalable (Consistency and Service Validation) System Level Resource Discovery & Management For Multi Core Environment 17 January 2011, CASTNESS’11

11. 11 The Proposed Solution – RD Mechanism System Level Resource Discovery & Management For Multi Core Environment 17 January 2011, CASTNESS’11 QMS If queue(i).lenght(i) > threshold then generate.query(minReq) resource(m).setrank=query(z).getorigin.getrank(m) resourceQuery(minReq) reply(RO) Search in the next neighboring tires RCT 5 5 5 4 3 2 1

12. 12 The Proposed Solution Service Cost, Cost Table and Resource Ranking Algorithms Performance Parameters and Metrics Memory, Cache Clock Rate GFLOPS Alternatives: Real time Benchmarking, Micro Benchmarks (MHPC, SMB, MIBA) System Level Resource Discovery & Management For Multi Core Environment 17 January 2011, CASTNESS’11

13. 13 Simulation & Result –Simulation Tools COTson HP Lab’s COTSon is a full system simulation framework based on AMD’s SimNow.COTSon allows for simulating complete computing systems, ranging from a single node to a large cluster of hundreds of multicore nodes. High Performance Linkpack Benchmark (HPL) "HPL is a software package that solves a (random) dense linear system in double precision (64 bits) arithmetic on distributed- memory computers. It can thus be regarded as a portable as well as freely available implementation of the High Performance Computing Linpack Benchmark.” Alternative:NAMD System Level Resource Discovery & Management For Multi Core Environment 17 January 2011, CASTNESS’11

14. 14 Simulation & Result –Simulation System Level Resource Discovery & Management For Multi Core Environment 17 January 2011, CASTNESS’11 Objective of simulation To make comparison between the performance results of running HPL on simulated cluster with the proposed RD and also with SNMP Sample Resource Cost Table Core IDLatencyFrequencyCache sizeRank #117800 MHz128KB12 #2261GHz256KB7

15. 15 Simulation & Result –Simulation Architecture System Level Resource Discovery & Management For Multi Core Environment 17 January 2011, CASTNESS’11 COTSON Control Host DataBase Control Script XML-RPC SimNow-Node2SimNow-Node1 Simnow-Node4SimNow-Node3 Control Daemon Core1Core2 Memory Core1Core2 Memory Core1Core2 Memory Core1Core2 Memory Q –Mediator - Network BSD HDD BSD 12 3 4

16. 16 Results System Level Resource Discovery & Management For Multi Core Environment 17 January 2011, CASTNESS’11

17. 17 Results System Level Resource Discovery & Management For Multi Core Environment 17 January 2011, CASTNESS’11

18. 18 Conclusion & Future Work System Level Resource Discovery & Management For Multi Core Environment 17 January 2011, CASTNESS’11 According to the results of the simulation, we can conclude that : The proposed method is scalable, when we increase the problem size and the cluster size, it shows better results. The proposed resource discovery mechanism enhanced the total performance of the cluster with multi core nodes This work still is in preliminary states, we will extend it to be more efficient and adapted with multi core environment.

19. 19 Thank You System Level Resource Discovery & Management For Multi Core Environment 17 January 2011, CASTNESS’11