Stream Programming Model: Difference between revisions
From esoterum.org
Jump to navigationJump to search
No edit summary |
No edit summary |
||
| Line 2: | Line 2: | ||
:#"Computer architectures are becoming multicore." | :#"Computer architectures are becoming multicore." | ||
:#"Computer applications are becoming embedded and data-centric." | :#"Computer applications are becoming embedded and data-centric." | ||
:#"Finally, there are rare cases in which the structured primitives in StreamIt have been inadequate | |||
for representing a streaming communication pattern. Figure 2-20 illustrates an example | |||
from video compression, where each parallel filter performs a motion prediction for a fixed | |||
area of the screen. Between successive frames, each filters shares its prediction with its neighbors | |||
on either side. While this could be represented with a feedback loop around the entire | |||
computation, there would be complicated interleaving involved. This case reflects a broader | |||
shortcoming, discussed in Section 2.7, that StreamIt is not designed for multidimensional data | |||
processing." (p.49) | |||
Latest revision as of 20:18, 25 April 2010
- William Thies. Language and Compiler Support for Stream Programs. Ph.D. Dissertation, MIT. February 2009.
- "Computer architectures are becoming multicore."
- "Computer applications are becoming embedded and data-centric."
- "Finally, there are rare cases in which the structured primitives in StreamIt have been inadequate
for representing a streaming communication pattern. Figure 2-20 illustrates an example from video compression, where each parallel filter performs a motion prediction for a fixed area of the screen. Between successive frames, each filters shares its prediction with its neighbors on either side. While this could be represented with a feedback loop around the entire computation, there would be complicated interleaving involved. This case reflects a broader shortcoming, discussed in Section 2.7, that StreamIt is not designed for multidimensional data processing." (p.49)
