Interactive volume visualization on a heterogeneous message-passing multicomputer

Question

1. What are the contributions mentioned in the paper "Interactive volume visualization on a heterogeneous message-passing multicomputer" ?

2. What is the common visualization method used in VOL2?

3. What is the function that can be used to examine the volumetric data?

4. Why is volume rendering a widely used visualization method?

Accepted Answer

This paper describes VOL2, an interactive general-purpose volume renderer based on ray casting and implemented on Pixel-Planes 5, a distributed-memory, message-passing multicomputer.. The authors describe the parallelization and load balancing techniques used in order to achieve interactive response and near-real-time frame rates.. The authors also present a number of applications for their system and derive some general conclusions about operation of image-order rendering algorithms on message-passing multicomputers.

Accepted Answer

It uses ray casting with perspective projection, a general volume rendering method suitable for a variety of visualization tasks.

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The cut plane can be moved by the user to examine any arbitrarily positioned or oriented cross-section of the volumetric data set.

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Due to the large number of graphics primitives (voxels) which must be visited during the image generation process, real-time (or even interactive) frame rates are difficult to achieve, even on highestperformance graphics engines.

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By-pass code is derived from the code normally executing on the computing nodes by removing all compute-intensive operations and retaining only the message-passing instructions, thus preserving a computing node’s ability to operate in the system (by essentially “fooling” the nodes it communicates with).

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Each rendering node can execute pixel operations in parallel on a 128x128 pixel raster, which corresponds to 1/20 of the final 512x640 pixel image.

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Typically 8 nodes are allocated to the compositing task, each responsible for a 640x64 pixel horizontal band of the final 640x512 pixel image.

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Rather than updating a randomly distributed set of samples, the authors update the samples on a regular grid, which has the benefit that the bookkeeping required to ensure every sample eventually gets replaced if samples are chosen randomly all but disappears; a simple modulus of the sample coordinates with the frame number tells whether to cast a ray for a given sample on a given frame.

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assignment of squares on the basis of descending cost provides approximately 10-20% increase in frame rate over distribution in screen order.

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In the second load balancing approach (sample squares) the master GP distributes a total of eighty 65x65-pixel square screen regions (Fig 7, right) on a FCFS basis to the ray casting nodes.

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In addition to the multiple successive refinement levels, the user can select a partial updating mode to increase the frame rate.

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If the data set is too large to be replicated on all ray casting nodes, it is partitioned into slabs at system startup time; the ray casting GPs are partitioned into groups [8].

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Both the sample rows and sample squares approachesproduce good load balance with the former giving better performances for images with low screen coverage and the latter approach giving better performance for full-screen images, as well as more consistent frame rates over varied image sizes (Fig. 9).

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A A AThe generality of ray-casting (for example, in isosurface rendering the surface thresholds can be changed on-the-fly, since no intermediate geometric primitives have to be generated).

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This image is sent to rendering nodes operating as splat processors which interpolate the image over the full display resolution and write the result to the frame buffer.

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The actual resolution of the computed image varies due to the use of successive refinement; the array of composited image samples sent to the splat processors to generate the fixed resolution (640x512) final image is thus of variable size.

Interactive volume visualization on a heterogeneous message-passing multicomputer

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Most frequently asked questions

1. What are the contributions mentioned in the paper "Interactive volume visualization on a heterogeneous message-passing multicomputer" ?

2. What is the common visualization method used in VOL2?

3. What is the function that can be used to examine the volumetric data?

4. Why is volume rendering a widely used visualization method?

5. What is the purpose of by-pass code?

6. How many pixel operations can be executed in parallel?

7. How many nodes are allocated to the compositing task?

8. What is the benefit of updating a random set of samples?

9. How much increase in frame rate does the assignment of squares provide?

10. How many ray casting nodes are assigned to each other?

11. What is the way to increase the frame rate of a ray caster?

12. What is the ray casting GP partitioning process?

13. What is the way to compute a square?

14. What is the generality of ray casting?

15. What is the image sent to rendering nodes?

16. What is the resolution of the composited image?

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Citations

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References

Display of surfaces from volume data

Volume rendering

Pixel-planes 5: a heterogeneous multiprocessor graphics system using processor-enhanced memories

PixelFlow: high-speed rendering using image composition

Volume rendering by adaptive refinement

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