A solutlon is proposed to the problem of interactive visualization and rendering of volume data. Designed for parallel distributed memory MIMD architectures, the volume rendering system is based on the ray tracing (RT) visualization technique, the Sticks representation scheme (a data structure exploiting data coherence for the compression of classified data sets), the use of aslice-partitioning technique for the distribution of the data between the processing modes and the consequent ray-data-flow parallelizing strategy. The system has been implemented on two different architectures: an inmos Transputer network and a hypercube nCUBE 6400 architecture. The high number of processors of this latter machine has allowed us to exploit a second level or parallelism (parallelism on image space, or parallelism on pixels) in order to arrive at a higher degree of scalability. In both proposals, the similarities between the chosen data-partitioning strategy, the communications pattern of the visualization processes and the topology of the physical system architecture represent the key points and provide improved software design and efficiency. Moreover, the partitioning strategy used and the network interconnection topology reduce the communications overhead and allow for an efficient implementation of a static load-balancing technique based on the prerendering of a low resolution image. Details of the practical issues involved in the parallelization process of volumetric RT, commonly encountered problems (i.e. termination and deadlock prevention) and the sw migration process between different architectures are discussed.

Parallel rendering of volumetric data set on distributed-memory architectures

Montani C;Perego R;Scopigno R
1993

Abstract

A solutlon is proposed to the problem of interactive visualization and rendering of volume data. Designed for parallel distributed memory MIMD architectures, the volume rendering system is based on the ray tracing (RT) visualization technique, the Sticks representation scheme (a data structure exploiting data coherence for the compression of classified data sets), the use of aslice-partitioning technique for the distribution of the data between the processing modes and the consequent ray-data-flow parallelizing strategy. The system has been implemented on two different architectures: an inmos Transputer network and a hypercube nCUBE 6400 architecture. The high number of processors of this latter machine has allowed us to exploit a second level or parallelism (parallelism on image space, or parallelism on pixels) in order to arrive at a higher degree of scalability. In both proposals, the similarities between the chosen data-partitioning strategy, the communications pattern of the visualization processes and the topology of the physical system architecture represent the key points and provide improved software design and efficiency. Moreover, the partitioning strategy used and the network interconnection topology reduce the communications overhead and allow for an efficient implementation of a static load-balancing technique based on the prerendering of a low resolution image. Details of the practical issues involved in the parallelization process of volumetric RT, commonly encountered problems (i.e. termination and deadlock prevention) and the sw migration process between different architectures are discussed.
1993
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
Data
Distributed-memory architectures
File in questo prodotto:
File Dimensione Formato  
prod_267777-doc_145550.pdf

solo utenti autorizzati

Descrizione: Parallel rendering of volumetric data set on distributed-memory architectures
Tipologia: Versione Editoriale (PDF)
Dimensione 2.35 MB
Formato Adobe PDF
2.35 MB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/219532
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact