Configuring a Large-Scale GALS System

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Configuring a Large- Scale GALS System M.M. Khan*, J. Navaridas†, L.A. Plana*, M. Luj ´an*, J.V Woods*, J. Miguel-Alonso† and S.B. Furber* *School of Computer Science, The University of Manchester, UK †University of The Basque Country, Spain

description

Configuring a Large-Scale GALS System. M.M. Khan*, J. Navaridas†, L.A. Plana*, M. Luj´an*, J.V Woods*, J. Miguel-Alonso† and S.B. Furber* *School of Computer Science, The University of Manchester, UK †University of The Basque Country, Spain. SpiNNaker. Objectives High-performance Robust - PowerPoint PPT Presentation

Transcript of Configuring a Large-Scale GALS System

Page 1: Configuring a Large-Scale GALS System

Configuring a Large-Scale GALS System

M.M. Khan*, J. Navaridas†, L.A. Plana*, M. Luj´an*,

J.V Woods*, J. Miguel-Alonso† and S.B. Furber*

*School of Computer Science, The University of Manchester, UK

†University of The Basque Country, Spain

Page 2: Configuring a Large-Scale GALS System

SpiNNaker

• Objectives– High-performance– Robust– Low-power

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SpiNNaker CMP

• System RAM

• Boot ROM

• MC Router

• Sys. Controller

• Ethernet

• SDRAM

• 20 Proc. Nodes

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Processing Node

• ARM968E-S

• Comm. Ctlr.

• Interrupt Ctlr.

• DMA Ctlr.

• Timer

• TCM (100K)

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Communication Network• MC Router• Packets

– MC– P2P– NN

• 1Gb/s inter-chip

• 6Gb/s per Node

• Six two-way inter-chip links

*L.A. Plana et al.An On-Chip and Inter-Chip Communications Network for the Spinnaker Massively-Parallel Neural Net Simulator. In Proc. Second ACM/IEEE

International Symposium on Networks-on-Chip (NoCS 2008), pages 215 – 216, 2008.

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Performance• 64K CMPs

• > 1m ARM968

• 256 tera IPS computing power

• >8 TB memory

• 6 Gb/s/Node Comm. NoC (spike channel)

• 1 Gb/s System NoC (synaptic channel)

• 109 neurons in real-time

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Fault-tolerance

• Redundancy

• Fault-detection and Isolation

• Fault-recovery

• Min. single-point-of-failure

• Run-time configuration

• Run-time recovery

• Run-time application loading

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Low-power• Hardware

– Asynchronous Communication– Low-power ARM968

• Software– Asynchronous Event-Driven Model

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Standard Application Model

• Sleepy processors

• Event-driven application

• No scheduler• No software

threads• Only ISRs• Driven by

Interrupts

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Configuration Process-I

• Min Boot-ROM code

• POST+chip components initialization

• Batch mode

POST

Load Boot code in TCM

Select Monitor Proc.

Configure Interrupts

Monitor

Configure Chip

Go to Sleep

yes

no

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Configuration Process-II

• Event-driven Model

• Real-time Configuration

• Processors on Sleep

Recovery

Host System Comm.

Assign (0, 0)

Status to Host Chip

Host Chip

Frame + Packet Comm.Packet Comm.

Acc. Status to Host

Assign (x, y)

Conf. RouterConf. Router

yesno

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Flood-fill Mechanism• Event-driven

model

• Droplets of data block to origin chip(s)

• A pipelined wave of data from origin(s) to other chips

1 Ethernet Connection

2 Ethernet Connections

animations from http://physics-animations.com/Physics/English/int_ref.htm#Wlb

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Flood-fill Mechanism

• Various Mechs.– Broadcast– 5 Chips fwd– 3 Chips fwd– 2 Chips fwd

• Performance Vs robustness

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Evaluation

• SystemC system-level model

• Cycle-accurate• Instruction

accurate• 129706 cycles

for configuration process-I

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Evaluationa) Impact of System Size

1Eth - 8 KB application + 16 KB data

200

400

600

800

32x32 64x64 128x128 256x256

cycl

es (

thou

sand

s)

2msg

3msg

5msg

bcast

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Evaluation

0

5

10

15

20

32KB + 32KB 32KB + 64KB 32KB +128KB 32KB +256KB 32KB +512KB

Boo

ting

tim

e (M

illi

ons

of c

ycle

s) .

2msg

3msg

5msg

bcast

b) Impact of Data SizeApplication+Data

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Conclusions