(0 of 12) High Performance λnetworking for Grid Applications. Cees de Laat

Transcription

1 High Performance λnetworking for Grid Applications Cees de Laat (0 of 12)

2 λeu High Performance Networking for Grid Applications Cees de Laat λaat SURFnet University of Amsterdam SARA NIKHEF NCF (1 of 12)

3 Contents of this talk λ This slide is intentionally left blank

4 (1 of 12) evlbi λ

5 λvlbi (2 of 12)

6 igrid 2002 (3 of 12) September 24-26, 2002, Amsterdam, The Netherlands 28 demonstrations from 16 countries: Australia, Canada, CERN, France, Finland, Germany, Greece, Italy, Japan, The Netherlands, Singapore, Spain, Sweden, Taiwan, United Kingdom, United States Applications demonstrated: art, bioinformatics, chemistry, cosmology, cultural heritage, education, high-definition media streaming, manufacturing, medicine, neuroscience, physics, tele-science Grid technologies demonstrated: Major emphasis on grid middleware, data management grids, data replication grids, visualization grids, data/visualization grids, computational grids, access grids, grid portals 25Gb transatlantic bandwidth (100Mb/attendee, 250x igrid2000!)

7 (3b of 12) Experimental Networks High-performance trials of new technologies that support application-dictated development of software toolkits, middleware, computing and networking. Provide known and knowable characteristics with deterministic and repeatable behavior on a persistent basis, while encouraging experimentation with innovative concepts. Experimental Networks are seen as the missing link between Research and Production Networks.

8 What is a LambdaGrid? (3c of 12) A grid is a set of networked, middleware-enabled computing resources. A LambdaGrid is a grid in which the lambda networks themselves are resources that can be scheduled, like all other computing resources. The ability to schedule and provision lambdas provides deterministic end-to-end network performance for real-time or time-critical applications, which cannot be achieved on today s grids.

9 # u s e r s (4a of 12) A. Lightweight users, browsing, mailing, home use Need full Internet routing, one to many B. Business applications, multicast, streaming, VPN s, mostly LAN Need VPN services and full Internet routing, several to several + uplink C. Special scientific applications, computing, data grids, virtual-presence Need very fat pipes, limited multiple Virtual Organizations, few to few A ADSL B GigE λbw requirements F(t) C

10 # u s e r s (4b of 12) A. Lightweight users, browsing, mailing, home use Need full Internet routing, one to many B. Business applications, multicast, streaming, VPN s, mostly LAN Need VPN services and full Internet routing, several to several + uplink C. Special scientific applications, computing, data grids, virtual-presence Need very fat pipes, limited multiple Virtual Organizations, few to few A ADSL B GigE λbw requirements F(t) C

11 λscale (5 of 12)

12 The only formula s λ # λ(rtt) 200 e(t 2002) rtt Now, having been a High Energy Physicist we set c = 1 e = 1 h = 1 and the formula reduces to: # λ 200 e(t 2002) rtt (6 of 12)

13 dummy SURFnet Lambda s fibers (old already) λd (7 of 12)

14 CLASS A B C # λ SCALE 200 e(t 2002) rtt λservices 2 Metro Switching/ routing VPN s, (G)MPLS dark fiber Optical switching 20 National/ regional Routing VPN s Routing Lambda switching 200 World ROUTER$ Routing Sublambdas, ethernetsdh (8 of 12)

15 Current technology λ+ (re)definition Current (to me) available technology consists of SONET/SDH switches, 10 gig ethernet and dark fiber environments Optical switch installed (this week)! DWDM+switching included Starlight/NetherLight deploy VLAN s on Ethernet switches to connect [exactly two] ports (but also routing) We want to understand routerless limited environments So redefine a λ as: (9 of 12) a λ is a pipe where you can inspect packets as they enter and when they exit, but principally not when in transit. In transit one only deals with the parameters of the pipe: number, color, bandwidth

16 (9a of 12) MEMS optical λswitch (CALIENT)

17 So λwhat are the facts Costs of fat pipes (fibers) are one/third of cost of equipment to light them up Is what Lambda salesmen tell me Costs of optical equipment 10% of switching 10 % of full routing equipment for same throughput 100 Byte 40 Gb/s -> 20 ns to look up in 140 kentries routing table (light speed from me to you!) Big sciences need fat pipes Bottom line: look for a hybrid architecture which serves all users in a cost effective way (10 of 12)

18 Long haul λ TDM λ R Architectures - L1 - L3 Internet Internet R SW L2 VPN s R (10b of 13) R

19 (11 of 14) Application Middleware Transport Application Middleware Transport High bandwidth app UvA SURFnet5 3 rd party carriers UBC Vancouver ams chi λ Switch lambda for high bandwidth 2.5Gb Router lambda applications GbE Bypass of production network Middleware may request (optical) Router Lambda pipe Switch Router RATIONALE: GbE Lower the cost of transport per Router packet Lambda Switch Router GbE Router Switch

20 How low can you go? (12 of 15) Application Endpoint A Router Ethernet SONET DWDM fiber Local Ethernet POS NetherLight MEMS Regional dark fiber NetherLight Application ONS Endpoint B Trans-Atlantic TransLight

21 Layer 2 VPN Univ B Virtual λorganization on L2 Univ A SN5 CHICAGO lambda Univ X SN5 A DAM (13 of 15) Univ Y

22 (15 of 17) NetherLight Network: 2003 Emerging international lambda grid New York City Stockholm Northern Light Chicago StarLight 10 Gbit/s Tyco/IEEAF 10 Gbit/s SURFnet Operational 1H03 Expected 2H03 10 Gbit/s NSF London UKLight Amsterdam NetherLight 10 Gbit/s NSF Geneva CERN 10 Gbit/s SURFnet DWDM SURFnet Dwingeloo ASTRON/JIVE 2.5 Gbit/s CESNET Prague CzechLight E. Radius, 2 nd evlbi workshop, Dwingeloo, May 15-16,

23 (16 of 18) NetherLight DAS: 32*2cpu s IBM Myrinet 1 Gbs 100Mbs SURFnet backbone Lambda s to Chicago, Geneve, Praha, NYC London calient 10 Gbs F O R C E 1 0 Fat pc server E X T R E M E Dark fiber To Dwingeloo 1 Gbs 4 HP servers UvA/NikHEF/SARA

24 (intermezzo) N et h e r L i g h t

25 (17 of 19) Early Lambda/LightPath WS fast L2 fast->slow λ TDM experiences slow high RTT L2 slow->fast fast WS

26 λ (17b of 20)

27 5000 λ1 kbyte UDP packets (18 of 20)

28 WS Layer - λ2 requirements from 3/4 fast TCP is bursty due to sliding window protocol and slow start algorithm. Window = BandWidth * RTT & BW == slow fast - slow Memory-at-bottleneck = * slow * RTT fast So pick from menu: Flow control Traffic Shaping RED (Random Early Discard) Self clocking in TCP Deep memory L2 fast->slow slow high RTT L2 slow->fast fast (18a of 20) WS

29 Self-clocking of TCP (19 of 20) WS fast 14 µsec L2 fast->slow λhigh RTT 20 µsec 20 µsec L2 slow->fast 20 µsec fast WS 20 µsec

30 WS Layer - λ2 requirements from 3/4 fast L2 fast->slow Window = BandWidth * RTT & BW == slow fast - slow Memory-at-bottleneck = * slow * RTT fast Given M and f, solve for slow ===> f * M 0 = s 2 - f * s + RTT high RTT L2 slow->fast f M s 1,s 2 = ( 1 +/- sqrt( 1-4 ) ) 2 f * RTT fast (19b of 20) WS

31 Forbidden area, solutions for s when f = 1 Gb/s, M = 0.5 Mbyte λ AND NOT USING FLOWCONTROL s 158 ms = RTT Amsterdam - Vancouver rtt (19c of 20) OC12 OC9 OC6 OC3 OC1

32 (19d of 20) Problem Solving Environment Applications and Supporting Tools Application Development Support High performance computing and Processor memory co-allocation Security and Generic AAA Optical Networking Researched in other programlines Imported from the Globus toolkit Collective Grid Services Brokering Global Queuing Co- Scheduling Data Cataloguing Auditing Authorization Monitoring Fault Management Common Grid Services Grid Information Service Uniform Resource Access Global Event Services Uniform Data Access Data Replication Communicatio n Services Grid Security Infrastructure (authentication, proxy, secure transport) Communication Fabric Grid task initiation Grid access (proxy authentication, authorization, initiation) Local Resources Resource Manager CPUs Resource Manager Monitors layers of increasing abstraction taxonomy Resource Manager On-Line Storage Resource Manager Scientific Instruments Resource Manager Tertiary Storage Resource Manager Highspeed Data Transport Resource Manager net QoS

33 4 λpolicy API Generic AAA server Rule based engine 2 Application Specific Module 5 Service Starting point 3 Accounting Metering 3 RFC , 3334, policy draft 5 3 Data Policy Data Acct Data (19e of 20) PDP PEP

34 Multi λdomain case (19f of 20)

35 (Future) λprojects National: NCF Grid project VLE GigaPort-NG LOFAR European DataGrid DataTAG International NetherLight StarLight AnyLight, LowLight, BackLight Optiputer Research: (19g of 20) Models of Lambda networking Transport AAA

36 BW*RTT C Transport λin the corners Needs more App & Middleware interaction B For what current Internet was designed? Full optical future A # FLOWS (19h of 20)

37 The λend (21 Thanks to SURFnet: Kees Neggers,UIC&iCAIR: Tom DeFanti, Joel Mambretti, CANARIE: Bill St. Arnaud This work is supported by:, SURFnet, EU-IST project DATATAG of 21)