Institute for Mathematical Modeling RAS

1

Visualization in distributed systems. Overview.• Remote visualization means interactive viewing of three dimensional scientific data sets

over the global network.• Scientists use remote parallel computer recourses in many scientific simulations.• Scientific data sets are in the gigabyte or even terabyte size range.• It is impossible or unreasonable to send the entire data set over the network.• Moreover, the client usually has a limited amount of memory and CPU power for viewing

and analyzing the data, and scientific data are too large to be processed by a single computer.

• So, we need powerful visualization tools to analyze massive data sets.• Parallel visualization is a solution.

n1 Client

File server

Global or local network

n2

nN

I/O node

Master node

Computational nodes

User Workplace

M.Iakobovski. P.Krinov, S.MuraviovM.Iakobovski. P.Krinov, S.Muraviov

Institute for Mathematical Modeling RAS

2

Visualization in distributed systems. Goals.

• RemoteViewer is aimed to quickly and easily process and visualize massive data sets (3D CFD simulations results).

• Scalar data such as pressure or temperature may be viewed as a series of iso-surfaces and/or as a series of slices

• Vector data such as the velocity field can be interactively explored using trajectoriesMesh Flow over plane Iso-surfaces

M.Iakobovski. P.Krinov, S.MuraviovM.Iakobovski. P.Krinov, S.Muraviov

Institute for Mathematical Modeling RAS

3

Visualization in distributed systems. Problem statement.

RemoteViewer

Scalar fields visualization

Vector fields visualization

Data compression

Parallel and grid realization

Structure Visualization of Scalar and Vector fields

Iso-surfaces for scalar fields

Trajectories for vector field

Cubic & tetrahedral meshes

RemoteViewer TecplotTecplot

Computational Server

Data Server

Visualization Server

Client Workspace

M.Iakobovski. P.Krinov, S.MuraviovM.Iakobovski. P.Krinov, S.Muraviov

Institute for Mathematical Modeling RAS

4

Visualization in distributed systems. Issues.

a) Edge removalb) Node removalc) Topology refinement

a)

b)

c)

Synthesis

Reduction

Vector data visualizationGeneral visualization technique – geometric visualization.

Main approaches Experimental analog:to the flow visualization:

Path line calculations (individual trajectory)Streakline calculation (fog or smoke)Timelines calculations (coloration)

Basic principle - computation of massless particle trajectories

Data animation

Scalar data visualization methods: Syntesis & Reduction

M.Iakobovski. P.Krinov, S.MuraviovM.Iakobovski. P.Krinov, S.Muraviov

Institute for Mathematical Modeling RAS

5

Visualization in distributed systems. Status.

Operations on visualization server• Data processing• Iso-surfaces compression • Data transferring to the client

Operations on Client• Setting of boundaries of the visual area

(zoom) and resolution• Setting of basic image characteristics

(number of iso-surfaces, represented on the screen, corresponding function values; number of trajectories of particles and coordinates of their starting points)

• The 3D image is displayed on the client computer screen and can be explored using rotation and zooming without referring back to the server

• If the closer examination of a smaller object fragment is required, the demand for image of this fragment is sent to the server

• The new image can approximate the object with the higher accuracy due to the reduction in data size

IMM CLx12

File server

Local or global network

Slave nodes

server File

IMM Intel24

PACX-MPI Control node Control node

PACX-MPI

Remote workspace

Client

Local or global network

Control node sockets

Slave nodes

M.Iakobovski. P.Krinov, S.MuraviovM.Iakobovski. P.Krinov, S.Muraviov