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ANALYST SUMMIT 2007
Dr. Greg PapadopoulosExecutive Vice President, R&DChief Technology Officer
Redshift: The Explosion ofMassive Scale Systems
These slides contain forward-looking statements regardingthe future results and performance of Sun Microsystems, Inc., including statements regarding future industry trends and growth, demand for HPC and future trends in computing. These forward-looking statements involve risks and uncertainties, and actual results could differ materially from those contained in these forward-looking statements. Factors that could cause actual results to differ materially from those contained in these forward-looking statements include: risks associated with developing, designing, manufacturing and distributing new products; lack of success in technological advancements; pricing pressures; lack of customer acceptance of new products; the possibility of errors or defects in new products; competition; adverse business conditions; failure to retain key employees; the cancellation or delay of projects; our reliance on single-source suppliers; risks associated with our ability to purchase a sufficient amount of components to meet demand; inventory risks; risks associated with our international customers and operations; delays in product development or customer acceptance and implementation of new products and technologies; our dependence on significant customers and specific industries; and our dependence on channel partners. Please also refer to Sun's periodic reports that are filed with the Securities and Exchange Commission, including Sun's annual report on Form 10-K for the fiscal year ended June 30, 2006 and its quarterly report on Form 10-Q for the fiscal quarter ended October 1, 2006. Sun assumes no obligation to, and currently does not intend to, update these forward-looking statements.
25 Yrs: 100,000 to 1M Times More MIPS/$
1880 19201900 1940 1960 1980 2000 202010-15
10-10
10-5
100
105
1010
Year
MIPS
/1000
USD
0.01 MIPS/$1K
10,000MIPS/$1K
Hermann Brunner, Max-Planck-Institut fuer Extraterrestriche Physik, Germany
Where is the Demand?
1985 1995 2005 20151990 2000 2010.1
1
10
100
1K
10K
1M
World GDP
ProcessorPerformance
$36T$17T
Sun 11 MIPS
$40K (2005$)
T100010,000 MIPS$5K (2005$)
Core per Enterprise Demand
1000x
.1
1
10
100
1K
10K
100K
1M
20101995 2000 2005
Core Enterprise Demand
Moore’s Law
“Last Mile” Bandwidth
1K
10K
100K
1M
10M
100M
1G
10G
1985 1995 2005 20151990 2000 2010
9.6kbps14.4k
28.8k
56k 384k1.55m
4m
22m50–100m
POTS
DSL/Cable
Fiber
ΣBW – Filling the Pipe
NingΣBW
In = Out
ΣBW – Filling the Pipe
NingΣBW
In = Out
# Servers * BW/Server = # Devices * BW/Device
ΣBW – Filling the Pipe
.1
1
10
100
1K
10K
100K
1M
1995 2000 2005 2010
1,0001,000
50
1M ΣBW
Moore’s Law
Core
HPC – Insatiable Demand
HPC – Insatiable Demand
1
10
100
1K
10K
100K
1M
1995 2000 2005 2010.1
HPCHPC
Moore’s Law
Core
ΣBW
*-Prise
Internet
WorkdayNetwork.com
*Prise
Moore’s Law
*-Prise
1
10
100
1K
10K
100K
1M
1995 2000 2005 2010.1
ΣBW
CRM Core
HPC
Redshift – a Move to Massive Scale
1
10
100
1K
10K
100K
1M
1995 2000 2005 2010.1
*Prise
Moore’s Law
ΣBW
Core
HPC
Diverging Concerns
1
10
100
1K
10K
100K
1M
1995 2000 2005 2010.1
*Prise
Moore’s Law
ΣBW
CoreConsolidation
CostServices
HPC
Diverging Concerns
1
10
100
1K
10K
100K
1M
1995 2000 2005 2010.1
ScaleEfficiencyProducts *Prise
HPCHPC
Moore’s Law
ΣBW
CoreConsolidation
CostServices
“The Google Question”
If all you cared about was massive scale, what would you build and how would you operate it?
An Answer
With “Brutal Efficiency”• Hardened metrics (utilization, power, security)• Predictability of service level• Idea-to-deploy time and productivity
An Answer
With “Brutal Efficiency”• Hardened metrics (utilization, power, security)• Predictability of service level• Idea-to-deploy time and productivity
Deep, At-scale Engineering of Systems
How Deep?
Efficiency and predictability at massive scale are as
mission-criticalto Redshift as
RAS has been tothe core enterprise
Don’t Confuse
Commoditization ofComputers
Commoditization ofComputing
Don’t Confuse
Commoditization ofComputers
With
System Includes...
Base HW Plant(Servers, Storage and Switches)
O/S Instances
Network Service
Core Services and Platforms
System Includes...
Base HW Plant(Servers, Storage and Switches)
O/S Instances
Network Service
Core Services and PlatformsMassivelyParallelSystem
SMPs Are Back (With a Vengeance!)
64 Threads in 1997E10K
SizeFull RackPower
(Systems at peak utilization)9620 Watts
Weight1,800 lbs.Performance~150k tpm
SMPs Are Back (With a Vengeance!)
z
64 Threads in 1997E10K
64 Threads in 2007Niagara 2
SizeFull RackPower
(Systems at peak utilization)9620 Watts
Weight1,800 lbs.Performance~150k tpm
SMPs Are Back (With a Vengeance!)
z
64 Threads in 1997E10K
64 Threads in 2007Niagara 2
SizeFull Rack 1UPower
(Systems at peak utilization)9620 Watts 410 Watts
Weight1,800 lbs. 45 lbs.Performance~150k tpm ~300k tpm
24x
40x
30x
2x
SMPs Are Back (With a Vengeance!)
z
64 Threads in 1997E10K
64 Threads in 2007Niagara 2
Neptune and Crossbow
• Solaris virtual networking stacksfor high speed networks, based on protocol, service, or container
• Does the “careful” unleashing of 10G
• A shared, virtualized, non-blocking,multi-homed 10 Gigabit EthernetPCI-e network interface
• Gets the most out of your systemand your I/O bus> Processors get faster faster than I/O buses get
faster – PCI-e is (or soon will be) your bottleneck
Crossbow
Neptune
Neptune and Crossbow
SolarisCrossbow and PEF
MultiCore Microprocessor
PCIe4x10GE
Virtualized Network Streams
1000’s Logical Connections
Neptune
Solaris Zones Processes
Java RTS + Solaris =Open Real Time Operating System
Application
Java RTS 2.0
Solaris
Hardware
Java RTS + Solaris:1000 Times More Predictable
20microseconds
10milliseconds
12milliseconds
10microseconds
5milliseconds
7milliseconds
Maximum Latency Jitter
RTS
Real-Time Application Server ResultsComparison of Conventional Java SE to Java RTS
Distribution of Request/Reply Round-trip Times
0 200,000 400,000 600,000 800,000
10,000
1,000
100
10
1
Round-trip Time (US)
Java RTS Results: ALL priority transactionscomplete in 11 milliseconds or lessStandard Java SE Results: Prioritytransactions range from 11 ms to 3.5 seconds
Numb
er of
Req
uests
Real-Time Javaon Solaris:
Inverted PendulumGreg Bollella
Distinguished Engineer,Sun Microsystems
NetBeans IDE Support
• Cross-develop onthe host
• Deploy over the network
• Execute on the target• ...from the
NetBeans IDE
Download the JavaRTS Plugin, and
Co-Design
Computer+ Storage+ Network+ Power+ Cooling+ Software= BLACKBOX
But Wait, There’s More• The next wave will include leading-edge enterprises• Critical to this wave will be the bridge between
core IT and redshifting services:
Identity and securityProcedural languages and scripting
SOA and Web 2.0New clients
The Bridge
1
10
100
1K
10K
100K
1M
1995 2000 2010.1
*PriseHPCHPC
ΣBW
IdentityRSWSNew
Clients
Enterprise Bridge
Internet
Workday
CoreEnterprise
Network.com
Putting it all Together:The Binary Distribution
Base HW Plant(Servers, Storage and Switches)
O/S Instances
Network Service
Core Services and Platforms“TheDistro”
Source vs. BinaryPlatform Developers
Platform(Open Source)
open Javaopen ...
Source vs. BinaryPlatform Developers
Platform(Open Source)
1.1 1.2
Distributionopen Javaopen ...
1.2.1
...Binary Distribution
Source vs. BinaryPlatform Developers Application Developers
Platform(Open Source)
Applications
1.1 1.2
DistributionApplication Binaries
Binary Distribution
open Javaopen ...
1.2.1
...
Big Computers100Ks – 1Ms NodesGlobally Distributed
Devices
A Likely Scenario
Live.comGCC
Big Computers100Ks – 1Ms NodesGlobally Distributed
Distribution Networks
Devices
A Likely Scenario
Live.comGCC
Big Computers100Ks – 1Ms NodesGlobally Distributed
Distribution Networks
Startups
Devices
A Likely Scenario
Live.comGCC
Thank You.
ANALYST SUMMIT 2007
The Network is the Computer.TM
Dr. Greg PapadopoulosExecutive Vice President, R&DChief Technology Officer