institute for mathematical modeling ras 1 visualization in distributed systems. overview. remote...
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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