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[diderot] Diff of /branches/opencl/TODO
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Diff of /branches/opencl/TODO

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revision 1204, Thu May 12 19:10:20 2011 UTC revision 1254, Mon May 23 19:40:55 2011 UTC
# Line 23  Line 23 
23  SHORT-ISH TERM ========= (to make using Diderot less annoying to  SHORT-ISH TERM ========= (to make using Diderot less annoying to
24  ========================  program in, and slow to execute)  ========================  program in, and slow to execute)
25    
26  value-numbering optimization [DONE, but needs more testing]  value-numbering optimization [DONE]
27    
28  Allow ".ddro" file extensions in addition to ".diderot"  Allow ".ddro" file extensions in addition to ".diderot"
29    
# Line 60  Line 60 
60      to index into complete list      to index into complete list
61    
62  [GLK:6] Use of Teem's "hest" command-line parser for getting  [GLK:6] Use of Teem's "hest" command-line parser for getting
63  any input variables that are not defined in the source file  any "input" variables that are not defined in the source file.
64    
65  [GLK:7] ability to declare a field so that probe positions are  [GLK:7] ability to declare a field so that probe positions are
66  *always* "inside"; with various ways of mapping the known image values  *always* "inside"; with various ways of mapping the known image values
# Line 93  Line 93 
93    
94  "initially" supports lists  "initially" supports lists
95    
96  "initially" supports lists of positions output from  "initially" supports lists of positions output from different
97  different initalization Diderot program  initalization Diderot program (or output from the same program;
98    e.g. using output of iso2d.diderot for one isovalue to seed the input
99    to another invocation of the same program)
100    
101  Communication between strands: they have to be able to learn each  Communication between strands: they have to be able to learn each
102  other's state (at the previous iteration).  Early version of this can  other's state (at the previous iteration).  Early version of this can
# Line 205  Line 207 
207    field#2(3)[] F = bspln3 ⊛ img;    field#2(3)[] F = bspln3 ⊛ img;
208  or, as a tensor product of kernels, one for each axis, e.g.  or, as a tensor product of kernels, one for each axis, e.g.
209    field#0(3)[] F = (bspln3 ⊗ bspln3 ⊗ tent) ⊛ img;    field#0(3)[] F = (bspln3 ⊗ bspln3 ⊗ tent) ⊛ img;
210  This is especially important for things like time-varying data, or  This is especially important for things like time-varying fields
211  other multi-dimensional fields where one axis of the domain is very  and the use of scale-space in field visualization: one axis of the
212  different from the rest, and hence must be treated separately when  must be convolved with a different kernel during probing.
213  it comes to convolution.  What is very unclear is how, in such cases,  What is very unclear is how, in such cases, we should notate the
214  we should notate the gradient, when we only want to differentiate with  gradient, when we only want to differentiate with respect to some
215  respect to some subset of the axes.  One ambitious idea would be:  subset of the axes.  One ambitious idea would be:
216    field#0(3)[] Ft = (bspln3 ⊗ bspln3 ⊗ tent) ⊛ img; // 2D time-varying field    field#0(3)[] Ft = (bspln3 ⊗ bspln3 ⊗ tent) ⊛ img; // 2D time-varying field
217    field#0(2)[] F = lambda([x,y], Ft([x,y,42.0]))     // restriction to time=42.0    field#0(2)[] F = lambda([x,y], Ft([x,y,42.0]))     // restriction to time=42.0
218    vec2 grad = ∇F([x,y]);                             // 2D gradient    vec2 grad = ∇F([x,y]);                             // 2D gradient

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