1J. Kim Web Science & Technology Forum

Enabling Hardware Technology for Web Science

John Kim

Department of Computer Science

KAIST

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Computing System

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Moore’s Law

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Increasing number of cores

Rethinking the Design of Interconnection Networks

1975 1980 1985 1990 1995 2000 2005 2010 20150.512

5.12

51.2

512

Year

# Co

res

8086 80286 80386 80486 PentiumPentium Pro

P-II P-III

P-4Itanium

Power4

MIT-RAW

UltraSPARC IVPentium-D

Xeon Brisbane

Niagara

Core 2 Quad

Turion X2Core 2 DuoDenmark

Teraflops

Larrabee

TILE64

Sun Rock

Cell

XeonAgena Barcelona

Toliman

Core i7

IstanbulBecktonMagny-Cours

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Challenges for Future Hardware

• Energy-Efficient Mobile Systems– Need to extend battery life– Provide the performance capability of a laptop with a smaller

power budget– Exploit parallelisms available in future multi/many-core

processors

• Scalable Datacenter– Future datacenters will continue to increase in the number of

servers interconnected– Need to minimize energy consumption

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Energy Consumption

• Datacenters have a huge electricity bill– e.g.) US datacenters will consume 100 billion kWh at a cost

of $7.4 billion per year [EPA report]

• Total cost of ownership is no longer dominated by the hardware but by

Energy-Efficient Datacenters

Source: C. Belady “In the data center, power and cooling costs more than the it equipment it supports”

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Which costs more?

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20mm

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Supercomputers to Datacenters

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Can we leverage the network used in high-performance computing for

datacenter networks?

funded in part by Microsoft Research Asia

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Existing approaches

• Tree– Oversubscribed– Bottlenecked root

• Fat tree– 1:1 subscription– Costly as large number

of switches

With the number of servers growing

Container0 Container1 ...

TOR

switches

TOR

switches

With the number of servers growing

Scale up

Scale out

High end router

10slide from C. Guo

11J. KimRethinking the Design of Interconnection

Networks

Flattened Butterfly

John Kim, William Dally, Dennis Abts, “Flattened Butterfly: Cost-Efficient High-Radix Networks” ISCA 2007

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Dragonfly Topology [ISCA’08]

• Increase scalability by using a collection of routers as a ”supernode”

• Leverage the packaging hierarchy found in systems to match the hierarchical network of the topology?

• What is the challenge of mapping this topology?

Adaptive Routing

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Packaging Hierarchy

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Rackable Systems Container

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Load-Balanced Routing

• Load-balancing required in both inter- and intra-container routing

• Randomized routing can be leveraged to load balance the channels

• Adaptive routing need to determine whether to route using minimal routing and nonminimal routing

Approach :

- Leverage the centralized management capability in datacenters and provide a centralized adaptive routing.

- Focus on load-balancing the “elephant” flows while other short-lived flows can be routed minimally

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