high-performance networks and architectures (hina) - flowtune · 2019. 12. 30. · datacenter...
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![Page 1: High-performance Networks and Architectures (HiNA) - Flowtune · 2019. 12. 30. · Datacenter Networks. Software in the Datacenter •Response Time: Productivity, Revenue, Reputation](https://reader033.vdocuments.net/reader033/viewer/2022060904/609fe38d044e13056f2f38cb/html5/thumbnails/1.jpg)
Jonathan Perry, Hari Balakrishnan and Devavrat Shah
Flowtune
Flowlet Control for
Datacenter Networks
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Software in the Datacenter
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• Response Time: Productivity, Revenue, Reputation
• microservices develop network is centraldeployscale
Software in the Datacenter
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Traditional approach is packet-centric
Switch Mechanisms
Server Mechanisms
Implicit Allocation
Several RTTto converge
Changes manycomponents
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Implicit Allocation
Several RTTto converge
Changes manycomponents
Allocate network resources• Explicitly (maximize utility)
• Quickly, Consitently
• Flexibly (in software)
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Flowtune’s approach
1. Flowlet control
send() flowlet
2. Logically centralized• Reduce RTT dependence
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Example
AB
Allocator
R2R1
C
Hadoop on Server A has data for B:
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Example
A Allocator “Hadoop on A has data for B”
AB
Allocator
R2R1
C
Hadoop on Server A has data for B:
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Example
A Allocator “Hadoop on A has data for B”
Allocator Assign rates
AB
Allocator
R2R1
C
Hadoop on Server A has data for B:
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Example
A Allocator “Hadoop on A has data for B”
Allocator Assign rates
Allocator A “Send at 40Gbps”
AB
Allocator
R2R1
C
Hadoop on Server A has data for B:
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Example
Now say ad_server on Server C has data for B:
AB
Allocator
R2R1
C
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Example
Now say ad_server on Server C has data for B:
C Allocator “ad_server on C has data for B”
AB
Allocator
R2R1
C
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Example
Now say ad_server on Server C has data for B:
C Allocator “ad_server on C has data for B”
Allocator Assign rates
AB
Allocator
R2R1
C
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Example
Now say ad_server on Server C has data for B:
C Allocator “ad_server on C has data for B”
Allocator Assign rates
Allocator A “Send at 5Gbps”
Allocator C “Send at 35Gbps”
AB
Allocator
R2R1
C
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Hadoop flowlet rate 2x $0.05Ads flowlet rate 2x $0.20
Network Utility Maximization (NUM)
Ads flowlet:Hadoop flowlet:
Kelly et al., Journal of the Operational Research Society, 1998
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NUM Iterative Optimizer
- =
2. Each flow 𝑠 chooses rate 𝑥𝑠
1. Each link ℓ chooses price 𝑝ℓ using
×
3. Goto 1
SupplyDemand
flow rates on ℓ − link capacity
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Adjusting prices
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Adjusting prices
NewtonExact
Diagonal(NED)
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Increasing responsiveness
Solution 1: Updateinputs
Run 100iterations
Outputrates
But: too slow!
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Increasing responsiveness
Solution 1:
Solution 2:
Updateinputs
Run 100iterations
Outputrates
But: too slow!
Updateinputs
Run 1iteration
Outputrates
$0.01$0.05$0.09
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Increasing responsiveness
Solution 1:
Solution 2:
Updateinputs
Run 100iterations
Outputrates
But: too slow!
But: queueing, packet drops!
Updateinputs
Run 1iteration
Outputrates
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Increasing responsiveness
Solution 1:
Solution 2:
Solution 3:
Updateinputs
Run 100iterations
Outputrates
But: too slow!
But: queueing, packet drops!
Updateinputs
Run 1iteration
Outputrates
Updateinputs
Run 1iteration
Normalizerates
Outputrates
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Flowtune normalizes rates
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Flowtune normalizes rates
𝑟ℓ =allocation
capacity
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Flowtune normalizes rates
ෝ𝑥𝑠 =𝑥𝑠
max 𝑟ℓ
𝑟ℓ =allocation
capacity
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Flowtune normalizes rates
99.7% of optimal
throughput
ෝ𝑥𝑠 =𝑥𝑠
max 𝑟ℓ
𝑟ℓ =allocation
capacity
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Architecture
Endpoints
Optimizer
Normalizer
rates
flowletstart/end
normalizedrates
Allocator
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Multicore
Core 1: 𝑝1 𝑝2 𝑝3 𝑝4
Core 2: 𝑝5 𝑝6 𝑝7 𝑝81 2 3 4
8
76
5
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Multicore
Core 1: 𝑝1 𝑝2 𝑝3 𝑝4
Core 2: 𝑝5 𝑝6 𝑝7 𝑝81 2 3 4
8
76
5
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Multicore
Core 1: 𝑝1 𝑝2 𝑝3 𝑝4
Core 2: 𝑝5 𝑝6 𝑝7 𝑝81 2 3 4
8
76
5
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Multicore
For each flow 𝑥 compute 𝑔(links 𝑥 traverses)
For each link ℓ compute 𝑓(flows on ℓ)
Core 1: 𝑝1 𝑝2 𝑝3 𝑝4
Core 2: 𝑝5 𝑝6 𝑝7 𝑝81 2 3 4
8
76
5
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In the paper…
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Flow view Link view
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4608 servers in < 31𝜇𝑠
Communication
>1
2of time
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EC2: Resource Allocation
senders
receiver
8 senders, every 50 milliseconds
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Ns-2: Flowtune converges quickly to a fair allocation
Every 10 milliseconds:
senders
receiver
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Overhead is lowFr
acti
on
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net
wo
rk c
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ity
Inside the Social Network’s (Datacenter) Network, Roy et al., SIGCOMM’15
99% of links< 10% utilized
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Open Questions
• Handling mice• Bypass the allocator? Fastpass?
• External traffic• Measure & react?
• Deadlines, Co-flow• Market?
• Multicore: 3-tier Clos, WAN
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Flowtune
Give application developers control over network transport
Explicit PolicyApplication
DevelopersNetworkEngineers