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HOPE: Hotspot Prevention Congestion Control for Clos Network On-Chip. Najla Alfaraj, Junjie Zhang, Yang Xu, and H. Jonathan Chao Department of Electrical and Computer Engineering Polytechnic Institute of New York University. NOCS 2011. VOQ: Virtual Output Queue IM: Input Module

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hope hotspot prevention congestion control for clos network on chip

HOPE: Hotspot Prevention Congestion Control for Clos Network On-Chip

Najla Alfaraj, Junjie Zhang, Yang Xu, and H. Jonathan Chao

Department of Electrical and Computer Engineering

Polytechnic Institute of New York University

NOCS 2011

clos network

VOQ: Virtual Output Queue

IM: Input Module

CM: Central Module

OM: Output module

Clos Network

0

0

IM0

CM0

OM0

1

1

2

2

VOQ

Crossbar

Input Ports

Output Ports

3

3

IM1

CM1

OM1

4

4

5

5

VOQs input-buffer Switch Module

6

6

IM2

CM2

OM2

7

7

8

8

Features:

1. Low zero-load latency

  • Yu-Hsiang Kao, Najla Alfaraj, Ming Yang, and H. Jonathan Chao, “Design of High-Radix Clos Network-on-Chip”, 4th Annual ACM/IEEE International Symposium on Networks-on-Chip (NOCS), Grenoble, France, May 2010.
clos network1

VOQ: Virtual Output Queue

IM: Input Module

CM: Central Module

OM: Output module

Clos Network

0

0

IM0

CM0

OM0

1

1

2

2

VOQ

Crossbar

3

3

IM1

CM1

OM1

Input Ports

Output Ports

4

4

5

5

6

6

VOQs input-buffer Switch Module

IM2

CM2

OM2

7

7

8

8

Features:

1. zero-load latency

2. Multipath and load-balance routing

  • Yu-Hsiang Kao, Najla Alfaraj, Ming Yang, and H. Jonathan Chao, “Design of High-Radix Clos Network-on-Chip”, 4th Annual ACM/IEEE International Symposium on Networks-on-Chip (NOCS), Grenoble, France, May 2010.
clos network2

VOQ: Virtual Output Queue

IM: Input Module

CM: Central Module

OM: Output module

Clos Network

0

0

IM0

CM0

OM0

1

1

2

2

VOQ

Crossbar

3

3

IM1

CM1

OM1

Input Ports

Output Ports

4

4

5

5

6

6

VOQs input-buffer Switch Module

IM2

CM2

OM2

7

7

8

8

Features:

1. zero-load latency

2. Multipath and load-balance routing

  • Yu-Hsiang Kao, Najla Alfaraj, Ming Yang, and H. Jonathan Chao, “Design of High-Radix Clos Network-on-Chip”, 4th Annual ACM/IEEE International Symposium on Networks-on-Chip (NOCS), Grenoble, France, May 2010.
hotspot congestion problem

Design effective low cost hotspot congestion control to avoid saturation tree and achieve maximum effective throughput.

Effective throughput: number of flits received at their destinations with latency less than or equal D within time period.

  • Saturation-tree congestion
Hotspot Congestion Problem
  • Hotspot is an overloaded destination

Hotspot

  • hotspot refers to the congested destinations (i.e., end-points)
cnoc performance with load balance routing
CNOC Performance with load-balance routing

Hotspot problem

  • Simulation setup:
  • 64 3-stage Clos Network with 8x8 VOQ switch modules
  • 64 flits/input port
  • Cut-through scheduling algorithm
  • Module-to-Module load-balance routing
  • Packet size = 8 flits
hope hotspot prevention
HOPE: HOtspot PrEvention
  • Each destination aggregates its backlogged traffic from each IM
  • Evaluate congestion status using two thresholds (THLow , THHigh)
  • Regulate hotspot destination using Stop-and-go mechanism
hope hotspot prevention1
HOPE: HOtspot PrEvention

Backlogged flits destined for destination 0

Status dest 0

THHigh

THLow

Flit Arrives

Stop

Go

Flit Departs

0

0

1

1

2

2

3

3

4

4

5

5

6

6

7

7

8

8

hotspot refers to the congested destinations (i.e., end-points)

two threshold selections
Two-Threshold Selections
  • Case 1: Very Low thresholds
    • Hotspots detection is not accurate
    • Underflow  hotspot throughput decreases
  • Case 2: Very High thresholds
    • Overflow
    • HOL blocking  non-hotspot latency increases
  • How to choose the thresholds?

THHigh

THLow

THHigh

THLow

THHigh

THLow

?

?

two threshold selection rules

BackloggedOccupancy

Max

GC

Two-Threshold Selection Rules

THHigh

THLow

  • To avoid Overflow, THHigh <= Upper bound (THHigh)
  • To avoid Underflow, THLow >= Lower bound (THLow)
  • To maximize Theff under Delay = D:
    • Max(backlogged) < Allowed Buffer occupancy for each flow
      • To avoid HOL blocking and overflow
    • Min(backlogged) > 0
      • To avoid underflow
  • D constraint is critical factor to choose thresholds
    • As D increases, Thresholds increase

Min

Time

hardware evaluation
Hardware Evaluation

Backlogged Calculation

  • Each quadrant has: 2 IMs, 2 CMs, 2 OMs
  • HOPE is placed in the center of the layout
  • Aggregate each 2 adjacent IMs
  • For 64 network size, 8x8 SMs:
      • Each 2 adjacent IMs sends 4-bits/dest
      • Each OM sends 8 bits
      • Total wires/quadrant = 256 + 16 = 272 bits

ij: Input Module j cj: Central Module j oj: Output module j

  • Yu-Hsiang Kao, Najla Alfaraj, Ming Yang, and H. Jonathan Chao, “Design of High-Radix Clos Network-on-Chip”, 4th Annual ACM/IEEE International Symposium on Networks-on-Chip (NOCS), Grenoble, France, May 2010.
slide12

Minimize number of wires by sampling

  • Each IM sends backlogged traffic for one OM each clock cycle in round-robin manner.
  • For 64 network size, 8x8 SMs:
    • Each IMs sends 6-bits/destination for 8 destinations
    • Every 2 OMs sends 16 bits
    • Total wires from each quadrant = 6*8*2 + 16 = 112 bits
hardware evaluation backlogged calculation
Hardware Evaluation: Backlogged Calculation

SUMMARY OF HARDWARE EVALUATION DELAY

SUMMARY OF HARDWARE OVERHEAD

For 64-CNOC size of HOPE is 0.1% of Total area

simulation setup
Simulation Setup
  • Topology: 3 stage Clos network 24 8x8 routers
  • Router Buffer Structure: 64 flits/port VOQ shared input buffer structure
  • Congestion scheme: HOPE with TH(30, 50)
  • Packet size: 8 flits
hope performance
HOPE performance
  • Uniform & Transpose
  • Dynamic Traffic
hope performance1
HOPE performance
  • Hotspots Number
  • Hotspot Traffic Rate
conclusion
Conclusion
  • HOPE (HOtspot PrEvention) can effectively prevent hotspot problem in Clos Network on-Chip (CNOC).
  • HOPE has the following properties:
    • avoids Overflow and Underflow
    • improves CNOC performance under heavy load uniform traffic
    • doesn’t have any extra delay
    • robust with multiple hotspots
    • has minimal hardware cost (i.e. 0.1% of total chip area for 64-CNOC)
  • Thresholds choice depends on delay constraint specified.
  • Simulation results confirms HOPE effectiveness under different:
    • Traffic Pattern
    • Hotspot numbers
    • Hotspot Rate
    • Aggregation and notification Delay between PEs and HOPE controller.
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