how to build an artificial intelligence web system that can support more than 5000 request per...
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PRESENTED BY AZHAR K MUSTAPHANERVESIS SDN BHD
HOW TO BUILD AN ARTIFICIAL INTELLIGENCEWEB SYSTEM that can support more
than 5000 request per second
Platform: http://www.zygy.com Company: http://www.nervesis.com
WITH ARTIFICIAL INTELLIGENCE
NERVESIS SDN BHD
Zygy gatekeeperPersonalAssistantPlatform,Identitymanagement&SingleSignonsystem
midasTypo-based“pagenotfound”advertisingtargetingTelcosubscribers
Zygy smart streamingAsolutionforVideoonDemand(VOD)andlivewebcastingforVideoandAudio(AV).
PROPHECYPublicConversationIntelligence
PERSONAL ASSISTAnT PLATFORMRELATE WHAT MATTERS WITHOUT EFFORT
SSO | COLLATE | JOURNALIZE | RELATE
NERVESIS SDN BHD
What is midas?
Turn URL typos into your
goldminesNow, “page not found” can be converted into a relevant advertising page for your business, noticed by millions of unique viewers.
www.lazadah.com.my/
WebServer
DatabaseServer
Handle PresentationHandle AI LogicHandle Other Logic
Web Server
1-Webserver-1-Database with HIGH LOAD?
Store DataData CRUD (Create, RetrieveUpdate, Delete)
DATABASE Server NO RESPONSE
NERVESIS SDN BHD
SCALING with COMPUTATIONAL THINKING
* http://www.cs.cmu.edu/~CompThink/* http://www.bbc.co.uk/education/guides/zp92mp3/revision
Divide & ConquerBootstrapping
Generalization /
SimilaritiesRules
NERVESIS SDN BHD
Decomposition StEPS INTO LAYERS
Web RequestHTML PresentationAI and Logic LayerDatabase Layer
Request Routed by Session
Routed By Capacity
Static Content Dynamic HTML Boxes (Pagelet)
Probability Calculation | Edit Distance | Score |Feature Classification | More …Cache | Database Read | Write
NERVESIS SDN BHD
PATTERNS OR SIMILARITIESWeb Request Can be routed by session
and capacityStatic HTML Characterized by file,
images, videos Pagelet Pagelets are independent if
content are independentProbability Calculation & Edit Distance
Some values are almost static
Cache Almost static values can be cached
Database Read Read cannot catch up with 4 million rows although with indexCertain group of tables are independent
Database Write Data update is not frequent
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ALGORITHMS / RULES
ROUTInG DISTRIBUTION
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PAGELETS DISTRIBUTION
$("#shop“).load(“/pageletA“)
$("#shop“).load(“/pageletB“)
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AI POST-TRAINING: PRECALCULATION & ANTICIPATION
Cache INPUTS ( xi )
PRECALCULATED PARAMETERS
MATRIX PRUNING (RE)
Naïve Bayes Classifier
Cost function for Deep Neural Network
CACHE OUTPUTS ( fi )
PRECALCULATED PROBABILITIES
ANTICIPATED CALCULATION
cMAP = argmaxc∈C
P(x1, x2,…, xn | c)P(c)
Feature-based Linear Classifier
NERVESIS SDN BHD
Anticipatecalculationfor
nextiteration
ANTICIPATE
CacheInputs thatarealmost
staticwithcachestrategy
basedonsize.
OUTPUT
Precalculatecertain
probabilitiesand
parameters,
PRECALCULATION
CacheInputs thatarealmoststatic
withcachestrategybasedonsize
INPUT
ANTICIPATE
OUTPUTINPUT
PRECALCULATIO
N
DISTRIBUTED SMART CACHING
DATABASE
Persistent layer (part of Logic Layer) will update data thru cache instead directly to database
NERVESIS SDN BHD
DISTRIBUTED DATABASES
NERVESIS SDN BHD
Database divided into several independent segmentsCache layer will update data only thru Master DB
APPLICATION ARCHITECTURE
Distribution by weight or capacity (CPU, Memory, Disk IO, Network IO)
NERVESIS SDN BHD
ABSTRACTION / GENERALIZATION
INDEPENDENT DISTRIBUTED LAYERING Static Content
Routing
Static Content Clusters
AI Logic 1
Precalc Cache
Slave DB 1
PageletRouting
PageletClusters
AI Logic 2
Anticipate Cache
Master DB 1
Routing By Session
Static Content Clusters
AI Logic 3
Input Cache
Master DB 2
Routing By Capacity
PageletClusters
AI Logic 4
Output Cache
Slave DB 2
NERVESIS SDN BHD
AZHAR K. MUSTAPHA CONTACT
Nervesis Sdn Bhd
Lot 5.50, Wisma Central, JalanAmpang 50450 Kuala Lumpur,Malaysia
www.nervesis.comwww.zygy.commidas.nervesis.com
www.facebook.com/azhar.k.mustapha
my.linkedin.com/in/azharkm
ADDRESS:
WEBSITE:
EMAIL:
Nervesis Sdn BhdCOMPaNY:
THANKS FOR YOUR TIMEPlatform: http://www.zygy.comCompany: http://www.nervesis.com