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Revision 1165 - (download) (annotate)
Mon May 9 22:02:04 2011 UTC (7 years, 10 months ago) by jhr
File size: 8453 byte(s)
  minor edit to TODO
NOTE: GLK's approximate ranking of 8 most important tagged with
[GLK:1], [GLK:2], ...

SHORT TERM ============= (*needed* for streamlines & tractography)

[GLK:3] Add sequence types (needed for evals & evecs)
	types: ty '{' INT '}'
	value construction: '{' e1 ',' … ',' en '}'
	indexing: e '{' e '}'

[GLK:4] evals & evecs for symmetric tensor[2,2] and
tensor[3,3] (requires sequences)

ability to emit/track/record variables into dynamically re-sized
runtime buffer

tensor fields: convolution on general tensor images

SHORT-ISH TERM ========= (to make using Diderot less annoying to 
========================  program in, and slow to execute)

value-numbering optimization [DONE, but needs more testing]

[GLK:1] Add a clamp function, which takes three arguments; either
three scalars:
  clamp(lo, hi, x)  = max(lo, min(hi, x))
or three vectors of the same size:
  clamp(lo, hi, [x,y])  = [max(lo[0], min(hi[0], x)),
                           max(lo[1], min(hi[1], y))]
This would be useful in many current Diderot programs.
One question: clamp(x, lo, hi) is the argument order used in OpenCL
and other places, but clamp(lo, hi, x) is much more consistent with
lerp(lo, hi, x), hence GLK's preference

[GLK:2] Proper handling of stabilize method

allow "*" to represent "modulate": per-component multiplication of
vectors, and vectors only (not tensors of order 2 or higher).  Once
sequences are implemented this should be removed: the operation is not
invariant WRT basis so it is not a legit vector computation.

implicit type promotion of integers to reals where reals are
required (e.g. not exponentiation "^")

[GLK:5] Save Diderot output to nrrd, instead of "mip.txt"
  For grid of strands, save to similarly-shaped array
  For list of strands, save to long 1-D (or 2-D for non-scalar output) list
  For ragged things (like tractography output), will need to save both
    complete list of values, as well as list of start indices and lengths
    to index into complete list

[GLK:6] Use of Teem's "hest" command-line parser for getting
any input variables that are not defined in the source file

[GLK:7] ability to declare a field so that probe positions are
*always* "inside"; with various ways of mapping the known image values
to non-existant index locations.  One possible syntax emphasizes that
there is a index mapping function that logically precedes convolution:
  F = bspln3 ⊛ (img ◦ clamp)
  F = bspln3 ⊛ (img ◦ repeat)
  F = bspln3 ⊛ (img ◦ mirror)
where "◦" or "∘" is used to indicate function composition

Level of differentiability in field type should be statement about how
much differentiation the program *needs*, rather than what the kernel
*provides*.  The needed differentiability can be less than or equal to
the provided differentiability.

Use ∇⊗ etc. syntax
    syntax [DONE]
    IL and codegen

Add type aliases for color types
    rgb = real{3}
    rgba = real{4}

MEDIUM TERM ================== (*needed* for particles)

run-time birth of strands

"initially" supports lists

"initially" supports lists of positions output from 
different initalization Diderot program

Communication between strands: they have to be able to learn each
other's state (at the previous iteration).  Early version of this can
have the network of neighbors be completely static (for running one
strand/pixel image computations).  Later version with strands moving
through the domain will require some spatial data structure to
optimize discovery of neighbors.

MEDIUM-ISH TERM ============ (to make Diderot more useful/effective)

Python/ctypes interface to run-time

support for Python interop and GUI

Allow integer exponentiation ("^2") to apply to square matrices,
to represent repeated matrix multiplication

Alow X *= Y, X /= Y, X += Y, X -= Y to mean what they do in C,
provided that X*Y, X/Y, X+Y, X-Y are already supported.
Nearly every Diderot program would be simplified by this.

Put small 1-D and 2-D fields, when reconstructed specifically by tent
and when differentiation is not needed, into faster texture buffers.
test/illust-vr.diderot is good example of program that uses multiple
such 1-D fields basically as lookup-table-based function evaluation

expand trace in mid to low translation

extend norm (|exp|) to all tensor types [DONE for vectors and matrices]

determinant ("det") for tensor[3,3]

add ":" for tensor dot product (contracts out two indices
instead of one like •), valid for all pairs of tensors with
at least two indices

documents need for better compiler error messages when output variables
are not initialized; the current messages are very cryptic

want: warnings when "D" (reserved for differentiation) is declared as
a variable name (get confusing error messages now)

LONG TERM ==================== (make Diderot more interesting/attractive from 
==============================  a research standpoint)

IL support for higher-order tensor values (matrices, etc).
    tensor construction [DONE]
    tensor indexing [DONE]
    tensor slicing
    verify that hessians work correctly [DONE]

Better handling of variables that determines the scope of a variable
based on its actual use, instead of where the user defined it.  So,
for example, we should lift strand-invariant variables to global
scope.  Also prune out useless variables, which should include field
variables after the translation to mid-il.

test/vr-kcomp2.diderot: Add support for code like
	(F1 if x else F2)@pos
This will require duplication of the continuation of the conditional
(but we should only duplicate over the live-range of the result of the

[GLK:8] Want: non-trivial field expressions & functions.
scalar fields from scalar fields F and G:
  field#0(2)[] X = (sin(F) + 1.0)/2;
  field#0(2)[] X = F*G;
scalar field of vector field magnitude:
  image(2)[2] Vimg = load(...);
  field#0(2)[] Vlen = |Vimg ⊛ bspln3|;
field of normalized vectors (for LIC and vector field feature extraction)
  field#2(2)[2] F = ...
  field#0(2)[2] V = normalize(F);
scalar field of gradient magnitude (for edge detection))
  field#2(2)[] F = Fimg ⊛ bspln3;
  field#0(2)[] Gmag = |∇F|;    
scalar field of squared gradient magnitude (simpler to differentiate):
  field#2(2)[] F = Fimg ⊛ bspln3;
  field#0(2)[] Gmsq = ∇F•∇F;
There is value in having these, even if the differentiation of them is
not supported (hence the indication of "field#0" for these above)

co- vs contra- index distinction

Permit field composition:
  field#2(3)[3] warp = bspln3 ⊛ warpData;
  field#2(3)[] F = bspln3 ⊛ img;
  field#2(3)[] Fwarp = F ◦ warp;
So Fwarp(x) = F(warp(X)).  Chain rule can be used for differentation.
This will be instrumental for expressing non-rigid registration
methods (but those will require co-vs-contra index distinction)

Allow the convolution to be specified either as a single 1D kernel
(as we have it now):
  field#2(3)[] F = bspln3 ⊛ img;
or, as a tensor product of kernels, one for each axis, e.g.
  field#0(3)[] F = (bspln3 ⊗ bspln3 ⊗ tent) ⊛ img;
This is especially important for things like time-varying data, or
other multi-dimensional fields where one axis of the domain is very
different from the rest, and hence must be treated separately when
it comes to convolution.  What is very unclear is how, in such cases,
we should notate the gradient, when we only want to differentiate with
respect to some subset of the axes.  One ambitious idea would be:
  field#0(3)[] Ft = (bspln3 ⊗ bspln3 ⊗ tent) ⊛ img; // 2D time-varying field
  field#0(2)[] F = lambda([x,y], Ft([x,y,42.0]))    // restriction to time=42.0
  vec2 grad = ∇F([x,y]);                            // 2D gradient 

representation of tensor symmetry
(have to identify the group of index permutations that are symmetries)

dot works on all tensors

outer works on all tensors

Einstein summation notation

"tensor comprehension" (like list comprehension)

BUGS =================

// HEY (bug) bspln5 leads to problems ...
//  uncaught exception Size [size]
//    raised at c-target/c-target.sml:47.15-47.19
//field#4(3)[] F = img ⊛ bspln5;

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