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

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revision 1165, Mon May 9 22:02:04 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"
29    
30    Be able to output values of type tensor[2,2] and tensor[3,3];
31    (currently only scalars & vectors).  Want to add some regression tests
32    based on this and currently can't
33    
34  [GLK:1] Add a clamp function, which takes three arguments; either  [GLK:1] Add a clamp function, which takes three arguments; either
35  three scalars:  three scalars:
# Line 54  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 87  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 175  Line 183 
183  There is value in having these, even if the differentiation of them is  There is value in having these, even if the differentiation of them is
184  not supported (hence the indication of "field#0" for these above)  not supported (hence the indication of "field#0" for these above)
185    
186    Introduce region types (syntax region(d), where d is the dimension of the
187    region.  One useful operator would be
188            dom : field#k(d)[s] -> region(d)
189    Then the inside test could be written as
190            pos ∈ dom(F)
191    We could further extend this approach to allow geometric definitions of
192    regions.  It might also be useful to do inside tests in world space,
193    instead of image space.
194    
195  co- vs contra- index distinction  co- vs contra- index distinction
196    
197  Permit field composition:  Permit field composition:
# Line 190  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
219    
220    Tensors of order 3 (e.g. gradients of diffusion tensor fields, or
221    hessians of vector fields) and order 4 (e.g. Hessians of diffusion
222    tensor fields).
223    
224  representation of tensor symmetry  representation of tensor symmetry
225  (have to identify the group of index permutations that are symmetries)  (have to identify the group of index permutations that are symmetries)
226    
# Line 207  Line 228 
228    
229  outer works on all tensors  outer works on all tensors
230    
231    Help for debugging Diderot programs: need to be able to uniquely
232    identify strands, and for particular strands that are known to behave
233    badly, do something like printf or other logging of their computations
234    and updates.
235    
236    Permit writing dimensionally general code: Have some statement of the
237    dimension of the world "W" (or have it be learned from one particular
238    field of interest), and then able to write "vec" instead of
239    "vec2/vec3", and perhaps "tensor[W,W]" instead of
240    "tensor[2,2]/tensor[3,3]"
241    
242    Traits: all things things that have boilerplate code (especially
243    volume rendering) should be expressed in terms of the unique
244    computational core.  Different kinds of streamline/tractography
245    computation will be another example, as well as particle systems.
246    
247  Einstein summation notation  Einstein summation notation
248    
249  "tensor comprehension" (like list comprehension)  "tensor comprehension" (like list comprehension)
250    
251    Fields coming from different sources of data:
252    * triangular or tetrahedral meshes over 2D or 3D domains (of the
253      source produced by finite-element codes; these will come with their
254      own specialized kinds of reconstruction kernels, called "basis
255      functions" in this context)
256    * Large point clouds, with some radial basis function around each point,
257      which will be tuned by parameters of the point (at least one parameter
258      giving some notion of radius)
259    
260  ======================  ======================
261  BUGS =================  BUGS =================
262  ======================  ======================

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