20-Oct-15 Copyright P.H.Welch1 A Process-Oriented Architecture for Complex System Modelling Peter...

Apr 21, 2023 Copyright P.H.Welch 1

A Process-Oriented A Process-Oriented Architecture for Complex Architecture for Complex

System ModellingSystem Modelling

A Process-Oriented A Process-Oriented Architecture for Complex Architecture for Complex

System ModellingSystem Modelling

Peter Welch and Carl Ritson

Computing Laboratory, University of Kent at Canterbury

Napier University (17Napier University (17th.th. December, 2008) December, 2008)[Based on paper at CPA 2007 (July, 2007)][Based on paper at CPA 2007 (July, 2007)]


Fine-grainedFine-grained Massively parallelMassively parallel Process-orientedProcess-oriented

Architectural Basics (Complex Modellling)Architectural Basics (Complex Modellling)Architectural Basics (Complex Modellling)Architectural Basics (Complex Modellling)

This is the way This is the way of the world ...of the world ...

Processes, networks, networks-within-Processes, networks, networks-within-networksnetworks Channel (reader-writer) synchronisation Barrier (multiway synchronisation)

CSP / CSP / occam-occam-ππ

ππ-calc / -calc / occam-occam-ππ

Ever-changing network topologiesEver-changing network topologies Dynamic birth, re-connections, death Mobile channels and processes Mobile process location and neighbour awareness


Haemostasis: Haemostasis: we consider a greatly simplified model of the we consider a greatly simplified model of the formation of blood clots in response to damage in blood formation of blood clots in response to damage in blood vessels.vessels.

Case Study: Case Study: blood clottingblood clottingCase Study: Case Study: blood clottingblood clotting

When activated, they become stickysticky …

PlateletsPlatelets are passive quasi-cells carried in the bloodstream. They become activatedactivated when a balance between chemical suppressants and activators shift in favour of activation.

We are just going to model the clumping together of such sticky activated platelets to form clotsclots.

To learn and refine our modelling techniques ...


Programmed behaviourProgrammed behaviour Blood platelets (smooth / sticky) Blood vessel (walls) Wounding (punching a hole in the blood vessel) Chemical factors (to stimulate / inhibit platelets) Clotting rules (platelets move together, clots merge)

Emergent behaviourEmergent behaviour Blood loss Clot formation Plugging the wound Stemming the loss of blood



Model sizeModel size Tens of millions of processes (mostly space sites) Hundreds of thousands of platelets (~ 2%)

Model safetyModel safety No race hazards No deadlocks No livelocks No process starvation


byby occam-occam-ππ

Model scalingModel scaling ~ 2M processes per processor PC cluster (24 processors, with reasonable speedup)

only spent 1 only spent 1 week, so farweek, so far

byby designdesign


Show video …Show video …


CarefulCareful Writer blocks if reader is not ready Lots of deadlock possibilities

Synchronised CommunicationSynchronised CommunicationSynchronised CommunicationSynchronised Communicationc

BBAA

BenefitBenefit Once the writer has written, it knowsknows the reader has read

OK: plenty of other processes to OK: plenty of other processes to run and ultra-fast context switch run and ultra-fast context switch (comparable to a procedure call)(comparable to a procedure call)

OK: work with (a small set of) OK: work with (a small set of) synchronisation patterns for which synchronisation patterns for which we have proven safety theoremswe have proven safety theorems


Simple Deadlock ExampleSimple Deadlock ExampleSimple Deadlock ExampleSimple Deadlock Example

c

d

If there is no discipline on when AA and BB communicate, then AA may commit to output on cc, followed by BB on dd … or vice-versa. Either way, neither are listening and both are stuck. Same happens if both commit to input.

AA BB


request

Client - Server PatternClient - Server PatternClient - Server PatternClient - Server Pattern

replyclientclient serverserver

clientclient : makes a requestrequest any time, then commits to taking replyreply.

serverserver : always accepts a requestrequest (within some bounded time), then always makes a replyreply (within some bounded time). It may make requests itself, as a clientclient to other serversservers.

No deadlock is now possible from No deadlock is now possible from

this client-server relationship.this client-server relationship.


Client - Server PatternClient - Server PatternClient - Server PatternClient - Server Pattern

clientclient : makes a requestrequest any time, then commits to taking replyreply.

clientclient serverserver

serverserver : always accepts a requestrequest (within some bounded time), then always makes a replyreply (within some bounded time). It may make requests itself, as a clientclient to other serversservers.

Symbology:Symbology: this represents this representsa client-server relation. It points a client-server relation. It points toto the the

server and allows a server and allows a 2-way2-way conversation conversation(initiated by the client)(initiated by the client)


Client - Server PatternClient - Server PatternClient - Server PatternClient - Server PatternA serverserver may have many clientsclients …

Only one clientclient at a time converses with the serverserver . They form an orderly queue. Still no deadlock possible – and no clientclient starvation. No polling on the queue, so no livelock either.


Client - Server TheoremClient - Server TheoremClient - Server TheoremClient - Server TheoremA client-serverclient-server system that has no cycles in its client-serverclient-server

relations is deadlock, livelock and starvation free.


BarriersBarriersBarriersBarriers

Basic CSPCSP semantics apply. When a process synchronisessynchronises on a barrier, it blocks until all other processes enrolledenrolled on the barrier have also synchronisedsynchronised. Once the barrier has completed (i.e. all enrolledenrolled processes have synchronisedsynchronised), all blocked processes are rescheduled for execution.

The occam-occam- BARRIERBARRIER type corresponds to a multiway CSPCSP eventevent, though some higher level design patterns (such as resignationresignation) have been built in.

bb

worker (0) worker (1) worker (n-1)∙∙∙



bb


BARRIERBARRIER b b::PARPAR i = 0 FOR n i = 0 FOR n ENROLLENROLL b b worker (i, worker (i, bb))

The number of processes enrolled on an in-scope barrier is unchanged by a

non-enrolling PARPAR – only one of its components may reference it.

The number of processes enrolled on an in-scope barrier is unchanged by a

non-enrolling PARPAR – only one of its components may reference it.

A PARPAR construct must explicitly ENROLLENROLL its

components on barriers



cc

bb

BARRIERBARRIER b b,, cc::PARPAR i = 0 FOR n i = 0 FOR n ENROLLENROLL b b, , cc worker (i, worker (i, bb, , cc))


To synchronise on a barrier:

SYNCSYNC b b

Processes may synchronise on more than one barrier:

SYNCSYNC ccor



Barriers are commonly used to synchronise multiple phasesphases of computation between a set of parallel processes. Within each phase, other synchronisations (channel / barrier) may take place:

PROC worker (VAL INT id, PROC worker (VAL INT id, BARRIER bBARRIER b, , cc)) ... local declarations / initialisation... local declarations / initialisation WHILE runningWHILE running SEQSEQ SYNC bSYNC b ... phase b computation... phase b computation SYNC cSYNC c ... phase c computation... phase c computation::

Phased Parallel ComputationPhased Parallel ComputationPhased Parallel ComputationPhased Parallel Computation


occam-occam- BARRIERBARRIER synchronisationsynchronisation is safesafe in the sense that enrollmentenrollment and resignationresignation are automatically managed. A process may synchronisesynchronise on a BARRIERBARRIER if and only if it is enrolledenrolled.

Try to break this rule … your program won’t compile. There are zero memory and run-time costs to enforce it. Try to break this rule … your program won’t compile. There are zero memory and run-time costs to enforce it.

Barrier SynchronisationBarrier SynchronisationBarrier SynchronisationBarrier Synchronisation


MultiClient-Server PatternMultiClient-Server PatternMultiClient-Server PatternMultiClient-Server PatternSometimes, a serverserver cannot reply to a clientclient until it has been given information from allall its clientsclients. . [This is like a [This is like a barrier synchronisation, but with a message exchange.]barrier synchronisation, but with a message exchange.]

If we know the server and all its clients are in that state, it is safe to proceed …


MultiClient-Server Pattern 1MultiClient-Server Pattern 1MultiClient-Server Pattern 1MultiClient-Server Pattern 1If the serverserver knows how many clientsclients (say nn) will be calling …

… each clientclient calls the serverserver twice: first on a channel to give its information and, then, on a different channel to request the serverserver ’s answer. The serverserver takes nn pieces of information on its first service channel, then delivers its answer nn times down the other. [Note: each transaction still conforms to the basic client-[Note: each transaction still conforms to the basic client-server pattern.]server pattern.]


If the serverserver does not know how many clientsclients will be calling …

… each clientclient calls the serverserver twice: first to give its information and, then, to request the serverserver ’s answer. In between,In between, they barrier synchronise with each other. The serverserver first consumes information on its service channel; when an answer request arrives, it knows all the clients have reported, computes its answer and delivers it as many times as asked. [Note: each [Note: each transaction still conforms to the basic client-server pattern.]transaction still conforms to the basic client-server pattern.]

MultiClient-Server Pattern 2MultiClient-Server Pattern 2MultiClient-Server Pattern 2MultiClient-Server Pattern 2


An Architecture for EmergenceAn Architecture for EmergenceAn Architecture for EmergenceAn Architecture for EmergenceWe propose a We propose a layeredlayered dynamicdynamic client-serverclient-server phased-barrierphased-barrier architecture.architecture.

Bottom LayerBottom LayerBottom LayerBottom Layer

‘‘Site’ processes:Site’ processes: pure servers representing a locality. They pure servers representing a locality. They hold state information defining world topology hold state information defining world topology (by holding (by holding client-ends of the service channels of neighbouring sites)client-ends of the service channels of neighbouring sites) and local environmental data and local environmental data (such as the presence of (such as the presence of mobile agents, chemical factors, permeability, flow vectors)mobile agents, chemical factors, permeability, flow vectors)..

The topology is usually a Euclidean grid and fixed, though The topology is usually a Euclidean grid and fixed, though this is not essential.this is not essential.



Bottom LayerBottom LayerBottom LayerBottom Layer

They do not use their neighbour client connections. They They do not use their neighbour client connections. They only pass them on to visiting agents who wish to move.only pass them on to visiting agents who wish to move.

‘‘Site’ processes:Site’ processes: pure servers representing a locality. They pure servers representing a locality. They hold state information defining world topology hold state information defining world topology (by holding (by holding client-ends of the service channels of neighbouring sites)client-ends of the service channels of neighbouring sites) and local environmental data and local environmental data (such as the presence of (such as the presence of mobile agents, chemical factors, permeability, flow vectors)mobile agents, chemical factors, permeability, flow vectors)..


Location (Neighbourhood) AwarenessLocation (Neighbourhood) Awareness

The The MatrixMatrixThe The

MatrixMatrix



Second LayerSecond LayerSecond LayerSecond Layer

They keep in step through barrier synchronisation, following They keep in step through barrier synchronisation, following a simple cycle …a simple cycle …

Mobile ‘agent’ processes:Mobile ‘agent’ processes: pure clients (of site servers and pure clients (of site servers and higher-lever controllers). They are attached to sites through higher-lever controllers). They are attached to sites through which they observe the world and change it. They move which they observe the world and change it. They move from site to site under their own (and their contoller’s) rules. from site to site under their own (and their contoller’s) rules.



Second LayerSecond LayerSecond LayerSecond Layer

WHILE aliveWHILE alive SEQ SEQ SYNC discoverySYNC discovery ... observe local neighbourhood... observe local neighbourhood SYNC modifySYNC modify ... change local neighbourhood... change local neighbourhood

Mobile ‘agent’ processes:Mobile ‘agent’ processes: pure clients (of site servers and pure clients (of site servers and higher-lever controllers).higher-lever controllers).

all seeall seea consistent a consistent

viewview

and, possibly, and, possibly, movemove




MatrixMatrix

Mobile Mobile AgentsAgentsMobile Mobile AgentsAgents



Third LayerThird LayerThird LayerThird Layer

‘‘Coordinator’ processes:Coordinator’ processes: server processes managing rules server processes managing rules for group behaviour amongst agents. They may make client for group behaviour amongst agents. They may make client transactions with even higher-level controllers …transactions with even higher-level controllers …

Higher LayersHigher LayersHigher LayersHigher Layers

‘‘Super-coordinator’ processes:Super-coordinator’ processes: server processes managing server processes managing rules for group behaviour amongst coordinators. rules for group behaviour amongst coordinators. Etc …Etc …


An Architecture for EmergenceAn Architecture for EmergenceAn Architecture for EmergenceAn Architecture for Emergence


Blood Clotting ModelBlood Clotting ModelBlood Clotting ModelBlood Clotting Model

Pure servers. Define a 3D Euclidean grid. Each site has 26 Pure servers. Define a 3D Euclidean grid. Each site has 26 neighbours. They allow neighbours. They allow oneone platelet at a time – platelet at a time – any numberany number of chemical factors.of chemical factors.

Stores blood vessel Stores blood vessel wall flagwall flag (no agents may enter if set), a (no agents may enter if set), a voxelvoxel (from a 3D array spanning all sites, (from a 3D array spanning all sites, colouredcoloured if platelet if platelet is present), is present), blood flow vectorblood flow vector..

If a platelet is present, it holds the client-end of the platelet’s If a platelet is present, it holds the client-end of the platelet’s clotting controller processclotting controller process (two layers up). It may give this (two layers up). It may give this to an enquiry from a platelet on a neigbouring site.to an enquiry from a platelet on a neigbouring site.

Site Processes (bottom layer)Site Processes (bottom layer)Site Processes (bottom layer)Site Processes (bottom layer)


Blood Clotting ModelBlood Clotting ModelBlood Clotting ModelBlood Clotting ModelPlatelet Processes (second layer)Platelet Processes (second layer)Platelet Processes (second layer)Platelet Processes (second layer)

Pure clients. Drive the whole model. Engage on Pure clients. Drive the whole model. Engage on discoverydiscovery and and modifymodify barriers. Communicate with and move between barriers. Communicate with and move between site servers. site servers. FORKFORK off and communicate with their clotting off and communicate with their clotting controllers. controllers. SmoothSmooth or or stickysticky (initially (initially smoothsmooth).).

Pure clients. Engage on Pure clients. Engage on discoverydiscovery and and modifymodify barriers. barriers. Communicate with and move between site servers.Communicate with and move between site servers.

Chemical Factor Processes (second layer)Chemical Factor Processes (second layer)Chemical Factor Processes (second layer)Chemical Factor Processes (second layer)

Initial vector away from wound. Modifies factor level and Initial vector away from wound. Modifies factor level and flow vector in sites. Eventually drawn into blood flow.flow vector in sites. Eventually drawn into blood flow.



Controlling servers for groups of stuck-together platelets.Controlling servers for groups of stuck-together platelets.

Accumulate flow vectors from platelets and information on Accumulate flow vectors from platelets and information on adjacent sites (e.g. bumped into another clot?).adjacent sites (e.g. bumped into another clot?).

If sufficiently hard bump (possibly into more than one clot), If sufficiently hard bump (possibly into more than one clot), engages in election with bumped clots to see who takes engages in election with bumped clots to see who takes over all the platelets in a merged clot. Terminates if loses.over all the platelets in a merged clot. Terminates if loses.

Clot Processes (third layer)Clot Processes (third layer)Clot Processes (third layer)Clot Processes (third layer)

Otherwise, informs combined set of platelets of their new Otherwise, informs combined set of platelets of their new controller.controller.

multiclient-server pattern 1multiclient-server pattern 1



Controlling servers for groups of stuck-together platelets.Controlling servers for groups of stuck-together platelets.

Accumulate flow vectors from platelets and information on Accumulate flow vectors from platelets and information on adjacent sites (e.g. bumped into another clot?).adjacent sites (e.g. bumped into another clot?).

Then, makes decision about which way (if any) to move. Then, makes decision about which way (if any) to move. Informs all its platelets.Informs all its platelets.

Clot Processes (third layer)Clot Processes (third layer)Clot Processes (third layer)Clot Processes (third layer)



Blood Clotting ModelBlood Clotting ModelBlood Clotting ModelBlood Clotting ModelPlatelet Processes (second layer) – again ...Platelet Processes (second layer) – again ...Platelet Processes (second layer) – again ...Platelet Processes (second layer) – again ...

Discovery phase.Discovery phase. Get chemical factors, flow vector and clot Get chemical factors, flow vector and clot information in the neighbourhood from site. If smooth and information in the neighbourhood from site. If smooth and enough factor, fork off clot controller and become sticky. If enough factor, fork off clot controller and become sticky. If sticky, forward flow vector and neighbourhood info to clot for sticky, forward flow vector and neighbourhood info to clot for movement decision – else make it ourself. Receive info movement decision – else make it ourself. Receive info from clot on possible new clot controller and movement from clot on possible new clot controller and movement decision. decision. If moving, offer move to target site.If moving, offer move to target site.

Modify phase.Modify phase. If not moving, this is null. If not moving, this is null. If trying to move, If trying to move, get decision from target siteget decision from target site – other clots may have tried to – other clots may have tried to move there. If OK, move.move there. If OK, move.



3-D Bloodstream3-D Bloodstream3-D Bloodstream3-D Bloodstream


Results so far …Results so far …Results so far …Results so far …The biological accuracy of the current model is very The biological accuracy of the current model is very approximate. Nevertheless …approximate. Nevertheless …

Emergent BehaviourEmergent BehaviourEmergent BehaviourEmergent Behaviour

Clots do form is apparently realistic ways. They gather Clots do form is apparently realistic ways. They gather round the wound, form a plug and staunch the loss of blood round the wound, form a plug and staunch the loss of blood (deduced from the flow of platelets – we are not directly (deduced from the flow of platelets – we are not directly modeling blood).modeling blood).

Simple experiments are possible – for example, varying the Simple experiments are possible – for example, varying the concentration of platelets. Too high and the clots form too concentration of platelets. Too high and the clots form too fast around the leading edge of the wound, block platelet fast around the leading edge of the wound, block platelet traffic and fail to seal the hole. Too low and the clots form traffic and fail to seal the hole. Too low and the clots form too slow and get swept away. Nature demands a balance!too slow and get swept away. Nature demands a balance!


Results so far …Results so far …Results so far …Results so far …The biological accuracy of the current model is very The biological accuracy of the current model is very approximate. Nevertheless …approximate. Nevertheless …

Emergent BehaviourEmergent BehaviourEmergent BehaviourEmergent Behaviour

The accuracy can be refined in a stable way to greater and The accuracy can be refined in a stable way to greater and greater realism. greater realism.

More agent types can be added – More agent types can be added – clot bustingclot busting factors, factors, proteins (like proteins (like fibrinfibrin that make up the bulk of real clots). that make up the bulk of real clots).

Existing agent types can be refined. Introduce a time lag Existing agent types can be refined. Introduce a time lag delaying the onset of a sufficiently stimulated platelet (so it delaying the onset of a sufficiently stimulated platelet (so it can get a little way past initial encounters with existing clots).can get a little way past initial encounters with existing clots).


Results so far …Results so far …Results so far …Results so far …

PerformancePerformancePerformancePerformance

Models run at reasonable speed with up to ~3M processes Models run at reasonable speed with up to ~3M processes on commodity PCs (3.0 GHz, 1Gbyte RAM). Memory is on commodity PCs (3.0 GHz, 1Gbyte RAM). Memory is main limitation – the above uses most of it! Platelet main limitation – the above uses most of it! Platelet densities up to 2% (a reasonable limit for healthy humans) densities up to 2% (a reasonable limit for healthy humans) imply around 60K agents – actual numbers will be changing imply around 60K agents – actual numbers will be changing continuously. Achieves around 8 simulation cycles per sec.continuously. Achieves around 8 simulation cycles per sec.


Conclusions and Future WorkConclusions and Future WorkConclusions and Future WorkConclusions and Future Work

The The fine-grained massively-parallel process-orientedfine-grained massively-parallel process-oriented architecture proposed has proven remarkably architecture proposed has proven remarkably flexible flexible ......

It efficiently supports the necessary dynamics. It efficiently supports the necessary dynamics. AgentsAgents move without any complex data structures and algorithms move without any complex data structures and algorithms to manage locality – they find each other simply by to manage locality – they find each other simply by seeingseeing (or (or bumping intobumping into) each other in their neighbourhood. Local ) each other in their neighbourhood. Local environmental factors and topology are maintained by the environmental factors and topology are maintained by the bottom level bottom level sitesite servers. Group dynamics of servers. Group dynamics of compound compound agentsagents are managed by higher level servers. are managed by higher level servers.

It efficiently supports the necessary dynamics. It efficiently supports the necessary dynamics. AgentsAgents move without any complex data structures and algorithms move without any complex data structures and algorithms to manage locality – they find each other simply by to manage locality – they find each other simply by seeingseeing (or (or bumping intobumping into) each other in their neighbourhood. Local ) each other in their neighbourhood. Local environmental factors and topology are maintained by the environmental factors and topology are maintained by the bottom level bottom level sitesite servers. Group dynamics of servers. Group dynamics of compound compound agentsagents are managed by higher level servers. are managed by higher level servers.



The The fine-grained massively-parallel process-orientedfine-grained massively-parallel process-oriented architecture proposed has proven remarkably flexible, architecture proposed has proven remarkably flexible, stablestable ... ...

The The cost of changecost of change in the system is proportional to the in the system is proportional to the size size of the changeof the change – not to the – not to the size of the systemsize of the system..The The cost of changecost of change in the system is proportional to the in the system is proportional to the size size of the changeof the change – not to the – not to the size of the systemsize of the system..

This enables us to This enables us to scale up the complexityscale up the complexity of the models of the models with with no obvious limitsno obvious limits..This enables us to This enables us to scale up the complexityscale up the complexity of the models of the models with with no obvious limitsno obvious limits..



The The fine-grained massively-parallel process-orientedfine-grained massively-parallel process-oriented architecture proposed has proven remarkably flexible, stable architecture proposed has proven remarkably flexible, stable and and safe safe ......

It is free from It is free from race hazardsrace hazards, , deadlockdeadlock, , livelocklivelock and and process process starvationstarvation by designby design..It is free from It is free from race hazardsrace hazards, , deadlockdeadlock, , livelocklivelock and and process process starvationstarvation by designby design..

This comes from language design (This comes from language design (occam-occam-ππ) and a small ) and a small set of synchronisation patterns for which we have set of synchronisation patterns for which we have provenproven safety theorems.safety theorems.

This comes from language design (This comes from language design (occam-occam-ππ) and a small ) and a small set of synchronisation patterns for which we have set of synchronisation patterns for which we have provenproven safety theorems.safety theorems.



The The fine-grained massively-parallel process-orientedfine-grained massively-parallel process-oriented architecture proposed has proven remarkably flexible, stable architecture proposed has proven remarkably flexible, stable and and safesafe. So far, it has . So far, it has scaledscaled (reasonably) on a PC-cluster. (reasonably) on a PC-cluster.

This was a 24 node cluster of This was a 24 node cluster of 3.0 GHz, 1Gbyte RAM with 3.0 GHz, 1Gbyte RAM with fast Ethernet and switchfast Ethernet and switch..This was a 24 node cluster of This was a 24 node cluster of 3.0 GHz, 1Gbyte RAM with 3.0 GHz, 1Gbyte RAM with fast Ethernet and switchfast Ethernet and switch..

But we have But we have (Carl has)(Carl has) only spent one week on this ... only spent one week on this ...But we have But we have (Carl has)(Carl has) only spent one week on this ... only spent one week on this ...

The architecture will just exploit multicore processors The architecture will just exploit multicore processors automaticallyautomatically ... ... bring them on!bring them on!The architecture will just exploit multicore processors The architecture will just exploit multicore processors automaticallyautomatically ... ... bring them on!bring them on!


Conclusions and Future WorkConclusions and Future WorkConclusions and Future WorkConclusions and Future WorkDespite the simplicity of the current model, the emergent Despite the simplicity of the current model, the emergent behaviours observed are strikingly similar to behaviours observed are strikingly similar to haemostasishaemostasis..

Expand and refine the model, introducing new agent types and Expand and refine the model, introducing new agent types and rules to reflect closer and closer the real biology and physics.rules to reflect closer and closer the real biology and physics.

Multiple mechanisms for stimulating and inhibiting platelet Multiple mechanisms for stimulating and inhibiting platelet stickiness, sticky latency, other clot materials (fibrinogen), stickiness, sticky latency, other clot materials (fibrinogen), clot busting, differing platelet types, differing densities of clot busting, differing platelet types, differing densities of platelets within blood vessels, re-growth of the vessel wall platelets within blood vessels, re-growth of the vessel wall (under the clot), clot flexibility and tumbling, fluid dynamics, (under the clot), clot flexibility and tumbling, fluid dynamics, etc...etc...

Multiple mechanisms for stimulating and inhibiting platelet Multiple mechanisms for stimulating and inhibiting platelet stickiness, sticky latency, other clot materials (fibrinogen), stickiness, sticky latency, other clot materials (fibrinogen), clot busting, differing platelet types, differing densities of clot busting, differing platelet types, differing densities of platelets within blood vessels, re-growth of the vessel wall platelets within blood vessels, re-growth of the vessel wall (under the clot), clot flexibility and tumbling, fluid dynamics, (under the clot), clot flexibility and tumbling, fluid dynamics, etc...etc...

We invite We invite (and would really really like)(and would really really like) others to try this others to try this architecture for complex system modelling ... and whatever ...architecture for complex system modelling ... and whatever ...


AcknowledgementsAcknowledgementsAcknowledgementsAcknowledgementsThis work was part of that performed under the This work was part of that performed under the TUNATUNA pilot pilot study involving the Universities of York, Surrey and Kent. It study involving the Universities of York, Surrey and Kent. It was funded by the UK EPSRC from December, 2004, through was funded by the UK EPSRC from December, 2004, through December, 2006).December, 2006).

Many individuals contributed including: Susan Stepney, Jim Many individuals contributed including: Susan Stepney, Jim Woodcock, Ana Cavalcanti, Fiona Polack Woodcock, Ana Cavalcanti, Fiona Polack (York)(York), Steve , Steve Schneider, Helen Treharne Schneider, Helen Treharne (Surrey)(Surrey), Fred Barnes and Adam , Fred Barnes and Adam Sampson Sampson (Kent)(Kent)..

The work will continue under The work will continue under CoSMoSCoSMoS, a 4 year EPSRC grant , a 4 year EPSRC grant starting October, 2007. This will involve real science and real starting October, 2007. This will involve real science and real scientists!scientists!


Any q

uestion

s ... ???

Any q

uestion

s ... ???

Any q

uestion

s ... ???

Any q

uestion

s ... ???


Rapid Review: CSPRapid Review: CSPRapid Review: CSPRapid Review: CSP

We do not need to be mathematically sophisticated to work with CSP. That sophistication is pre-engineered That sophistication is pre-engineered into the model.into the model. We benefit from this simply by using it.

CSP deals with processes, networks of processes and various forms of synchronisation / communication between processes.

A network of processes is also a process - so CSP naturally accommodates layered network structures (networks of networks).


ProcessesProcessesProcessesProcesses

A process is a component that encapsulates some data structures and algorithms for manipulating that data.

Both its data and algorithms are private. The outside world can neither see that data nor execute those algorithms! [They are not [They are not objects …objects …] ] [Think [Think chips …chips …]]

The algorithms are executed by the process in its own thread (or threads) of control.

So, how does one process interact with another?

my.process


The simplest form of interaction is synchronised message-passing along channels.

The simplest forms of channel are zero-buffered and point-to-point (i.e. wireswires).

But, we can have buffered channels (blockingblocking//overwritingoverwriting).

And any-1, 1-any and any-any channels.

And structured multi-way synchronisationstructured multi-way synchronisation (e.g. barriers) …

And high-level (e.g. CREW) shared-memoryshared-memory locks locks …

ProcessesProcessesProcessesProcesses my.process


( A (c) || B (c) )( A (c) || B (c) ) \ {c} \ {c}

cAA BB

Synchronised CommunicationSynchronised CommunicationSynchronised CommunicationSynchronised Communication

BB may readread from cc at any time, but has to wait for a writewrite.

c ? x

AA may writewrite on cc at any time, but has to wait for a readread.

c ! 42


( A (c) || B (c) )( A (c) || B (c) ) \ {c} \ {c}

cAA BB

Synchronised CommunicationSynchronised CommunicationSynchronised CommunicationSynchronised Communication

Only when both AA and BB are ready can the communicationproceed over the channel cc.

c ? xc ! 42




bb


Basic CSPCSP semantics apply. When a process synchronisessynchronises on a barrier, it blocks until allall other processes enrolledenrolled on the barrier have also synchronisedsynchronised. Once the barrier has completed (i.e. all enrolledenrolled processes have synchronisedsynchronised), all blocked processes are rescheduled for execution.


PROC worker (VAL INT id, PROC worker (VAL INT id, BARRIER bBARRIER b, , cc)) ... local declarations / initialisation... local declarations / initialisation WHILE runningWHILE running SEQSEQ SYNC bSYNC b ... phase b computation... phase b computation SYNC cSYNC c ... phase c computation... phase c computation::

PROC worker (VAL INT id, PROC worker (VAL INT id, BARRIER BARRIER b)b) ... local declarations / initialisation... local declarations / initialisation WHILE runningWHILE running SEQSEQ SYNC bSYNC b ... phase 0 computation... phase 0 computation SYNC bSYNC b ... phase 1 computation... phase 1 computation::

Of course, only oneone barrier is actually needed to synchronise the phases in this example:



Site and Agent InteractionSite and Agent InteractionSite and Agent InteractionSite and Agent Interaction

To swing down a chain of 1M1M sites, exchanging one INTINT during each visit: 770 770 nsecs/visit (P3), 280 280 nsecs/visit (P4)

To swing down a chain of 1M1M sites, exchanging one INTINT during each visit: 770 770 nsecs/visit (P3), 280 280 nsecs/visit (P4)

To swing down a chain of 1M1M sites, but doing no business: 450 450 nsecs/visit (P3), 120 120 nsecs/visit (P4)

To swing down a chain of 1M1M sites, but doing no business: 450 450 nsecs/visit (P3), 120 120 nsecs/visit (P4)




MatrixMatrix

Mobile Mobile AgentsAgentsMobile Mobile AgentsAgents


PPPP

Dynamic Construction of AgentsDynamic Construction of AgentsDynamic Construction of AgentsDynamic Construction of Agents

bb

FORKINGFORKING XX

PP


bb

PP PPPP

Dynamic Construction of AgentsDynamic Construction of AgentsDynamic Construction of AgentsDynamic Construction of Agents

FORKINGFORKING XX


keyboardkeyboard

keywatch

drawdraw

Platelet Model (‘lazy’ CA)Platelet Model (‘lazy’ CA)Platelet Model (‘lazy’ CA)Platelet Model (‘lazy’ CA)

gen

∙∙∙∙∙∙ cell cellcell cell cellcell

clot



keyboardkeyboard

keywatch

drawdraw

gen


clot

phase 1

screenscreendisplay



screenscreendisplay

keyboardkeyboard

keywatch

drawdraw

gen


clotphase 0


phase 1


screenscreendisplay

keyboardkeyboard

keywatch

drawdraw

gen


clot



screenscreendisplay

keyboardkeyboard

keywatch

drawdraw

gen


clotphase 0



screenscreendisplay

keyboardkeyboard

keywatch

drawdraw

gen


phase 1

clotclot



screenscreendisplay

keyboardkeyboard

keywatch

drawdraw

gen


phase 1

clot

20-Oct-15 Copyright P.H.Welch1 A Process-Oriented Architecture for Complex System Modelling Peter...

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Transcript of 20-Oct-15 Copyright P.H.Welch1 A Process-Oriented Architecture for Complex System Modelling Peter...