P A R A L L E L A L G O R I T H M S F O R M I N I N G L A R G E - - - PowerPoint PPT Presentation

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Feb 18, 2024 18 likes •109 views

P D S W- D I S C S 2 0 1 8 : 3 R D J O I N T I N T E R N AT I O N A L W O R K S H O P O N PA R A L L E L D ATA S T O R A G E & D ATA I N T E N S I V E S C A L A B L E C O M P U T I N G S Y S T E M S P A R A L L E L A L G O R I T

SLIDE 1

P A R A L L E L A L G O R I T H M S F O R M I N I N G L A R G E - S C A L E T I M E - V A R Y I N G ( D Y N A M I C ) G R A P H S

S H A I K H A R I F U Z Z A M A N N AW S A F R I N S AT TA R M D A B D U L M OTA L E B F AY S A L

P D S W- D I S C S 2 0 1 8 : 3 R D J O I N T I N T E R N AT I O N A L W O R K S H O P O N PA R A L L E L D ATA S T O R A G E & D ATA I N T E N S I V E S C A L A B L E C O M P U T I N G S Y S T E M S New Orleans, LA 70148 USA Big Data and Scalable Computing Research Lab

SLIDE 2

TEMPORAL GRAPH

powerful representation of various social, biological and

technological dynamic systems

– Social interactions and human activities, – appearance and disappearance of links in the Web, – patterns of interactions among genes – patterns of interactions in functional brain networks

Complex system

Big Data and Scalable Computing Research Lab

SLIDE 3

APPLICATIONS

Diffusion and propagation in complex and social networks

– spread of viruses through a community

Understanding communication networks

– false news propagation

Improving transportation systems

– route-planning algorithms depending on the traffic with varied time

Neuron (brain) network analysis

– Locating key neurons in cortical networks

Big Data and Scalable Computing Research Lab

SLIDE 4

MOTIVATION & CHALLENGES

defining and computing various temporal network metrics

–classic studies’ analysis of the topological properties of static graphs

emergence of network big data

–massive networks often do not fit in the main memory of a single machine –prohibitively large runtime for existing sequential methods

Big Data and Scalable Computing Research Lab

SLIDE 5

OUR APPROACH

Designing scalable algorithms
Metrics

–Computing path –Centrality –Communities

Big Data and Scalable Computing Research Lab

SLIDE 6

OUR SCALABLE ALGORITHMS FOR STATIC GRAPH

DISTRIBUTED-MEMORY PARALLEL ALGORITHMS FOR COUNTING AND LISTING TRIANGLES IN BIG GRAPHS DPLAL (DISTRIBUTED PARALLEL LOUVAIN ALGORITHM WITH LOAD-BALANCING) TO DETECT COMMUNITIES

Big Data and Scalable Computing Research Lab

SLIDE 7

OUR MULTI-THREADED ALGORITHM FOR DYNAMIC GRAPH

Speedup factors of

ur multithreaded

shortest path algorithm

Big Data and Scalable Computing Research Lab

0.5 1 1.5 2 2.5 3 3.5 1 3 5 7 SPEEDUP NO OF THREADS

SPEEDUP VS NO OF THREADS

youtube string biogrid

SLIDE 8

FUTURE WORKS

Parallelize existing sequential temporal networks mining and computation of network metrics

–Efficient load balancing –Communication schemes –Data reduction (e.g., graph sparsification and approximation) –Efficient formalization of temporal metrics

Big Data and Scalable Computing Research Lab

SLIDE 9

THANK YOU

Big Data and Scalable Computing Research Lab