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      1 Welcome to Mesa's GLSL compiler.  A brief overview of how things flow:
      2 
      3 1) lex and yacc-based preprocessor takes the incoming shader string
      4 and produces a new string containing the preprocessed shader.  This
      5 takes care of things like #if, #ifdef, #define, and preprocessor macro
      6 invocations.  Note that #version, #extension, and some others are
      7 passed straight through.  See glcpp/*
      8 
      9 2) lex and yacc-based parser takes the preprocessed string and
     10 generates the AST (abstract syntax tree).  Almost no checking is
     11 performed in this stage.  See glsl_lexer.lpp and glsl_parser.ypp.
     12 
     13 3) The AST is converted to "HIR".  This is the intermediate
     14 representation of the compiler.  Constructors are generated, function
     15 calls are resolved to particular function signatures, and all the
     16 semantic checking is performed.  See ast_*.cpp for the conversion, and
     17 ir.h for the IR structures.
     18 
     19 4) The driver (Mesa, or main.cpp for the standalone binary) performs
     20 optimizations.  These include copy propagation, dead code elimination,
     21 constant folding, and others.  Generally the driver will call
     22 optimizations in a loop, as each may open up opportunities for other
     23 optimizations to do additional work.  See most files called ir_*.cpp
     24 
     25 5) linking is performed.  This does checking to ensure that the
     26 outputs of the vertex shader match the inputs of the fragment shader,
     27 and assigns locations to uniforms, attributes, and varyings.  See
     28 linker.cpp.
     29 
     30 6) The driver may perform additional optimization at this point, as
     31 for example dead code elimination previously couldn't remove functions
     32 or global variable usage when we didn't know what other code would be
     33 linked in.
     34 
     35 7) The driver performs code generation out of the IR, taking a linked
     36 shader program and producing a compiled program for each stage.  See
     37 ir_to_mesa.cpp for Mesa IR code generation.
     38 
     39 FAQ:
     40 
     41 Q: What is HIR versus IR versus LIR?
     42 
     43 A: The idea behind the naming was that ast_to_hir would produce a
     44 high-level IR ("HIR"), with things like matrix operations, structure
     45 assignments, etc., present.  A series of lowering passes would occur
     46 that do things like break matrix multiplication into a series of dot
     47 products/MADs, make structure assignment be a series of assignment of
     48 components, flatten if statements into conditional moves, and such,
     49 producing a low level IR ("LIR").
     50 
     51 However, it now appears that each driver will have different
     52 requirements from a LIR.  A 915-generation chipset wants all functions
     53 inlined, all loops unrolled, all ifs flattened, no variable array
     54 accesses, and matrix multiplication broken down.  The Mesa IR backend
     55 for swrast would like matrices and structure assignment broken down,
     56 but it can support function calls and dynamic branching.  A 965 vertex
     57 shader IR backend could potentially even handle some matrix operations
     58 without breaking them down, but the 965 fragment shader IR backend
     59 would want to break to have (almost) all operations down channel-wise
     60 and perform optimization on that.  As a result, there's no single
     61 low-level IR that will make everyone happy.  So that usage has fallen
     62 out of favor, and each driver will perform a series of lowering passes
     63 to take the HIR down to whatever restrictions it wants to impose
     64 before doing codegen.
     65 
     66 Q: How is the IR structured?
     67 
     68 A: The best way to get started seeing it would be to run the
     69 standalone compiler against a shader:
     70 
     71 ./glsl_compiler --dump-lir \
     72 	~/src/piglit/tests/shaders/glsl-orangebook-ch06-bump.frag
     73 
     74 So for example one of the ir_instructions in main() contains:
     75 
     76 (assign (constant bool (1)) (var_ref litColor)  (expression vec3 * (var_ref Surf
     77 aceColor) (var_ref __retval) ) )
     78 
     79 Or more visually:
     80                      (assign)
     81                  /       |        \
     82         (var_ref)  (expression *)  (constant bool 1)
     83          /          /           \
     84 (litColor)      (var_ref)    (var_ref)
     85                   /                  \
     86            (SurfaceColor)          (__retval)
     87 
     88 which came from:
     89 
     90 litColor = SurfaceColor * max(dot(normDelta, LightDir), 0.0);
     91 
     92 (the max call is not represented in this expression tree, as it was a
     93 function call that got inlined but not brought into this expression
     94 tree)
     95 
     96 Each of those nodes is a subclass of ir_instruction.  A particular
     97 ir_instruction instance may only appear once in the whole IR tree with
     98 the exception of ir_variables, which appear once as variable
     99 declarations:
    100 
    101 (declare () vec3 normDelta)
    102 
    103 and multiple times as the targets of variable dereferences:
    104 ...
    105 (assign (constant bool (1)) (var_ref __retval) (expression float dot
    106  (var_ref normDelta) (var_ref LightDir) ) )
    107 ...
    108 (assign (constant bool (1)) (var_ref __retval) (expression vec3 -
    109  (var_ref LightDir) (expression vec3 * (constant float (2.000000))
    110  (expression vec3 * (expression float dot (var_ref normDelta) (var_ref
    111  LightDir) ) (var_ref normDelta) ) ) ) )
    112 ...
    113 
    114 Each node has a type.  Expressions may involve several different types:
    115 (declare (uniform ) mat4 gl_ModelViewMatrix)
    116 ((assign (constant bool (1)) (var_ref constructor_tmp) (expression
    117  vec4 * (var_ref gl_ModelViewMatrix) (var_ref gl_Vertex) ) )
    118 
    119 An expression tree can be arbitrarily deep, and the compiler tries to
    120 keep them structured like that so that things like algebraic
    121 optimizations ((color * 1.0 == color) and ((mat1 * mat2) * vec == mat1
    122 * (mat2 * vec))) or recognizing operation patterns for code generation
    123 (vec1 * vec2 + vec3 == mad(vec1, vec2, vec3)) are easier.  This comes
    124 at the expense of additional trickery in implementing some
    125 optimizations like CSE where one must navigate an expression tree.
    126 
    127 Q: Why no SSA representation?
    128 
    129 A: Converting an IR tree to SSA form makes dead code elmimination,
    130 common subexpression elimination, and many other optimizations much
    131 easier.  However, in our primarily vector-based language, there's some
    132 major questions as to how it would work.  Do we do SSA on the scalar
    133 or vector level?  If we do it at the vector level, we're going to end
    134 up with many different versions of the variable when encountering code
    135 like:
    136 
    137 (assign (constant bool (1)) (swiz x (var_ref __retval) ) (var_ref a) ) 
    138 (assign (constant bool (1)) (swiz y (var_ref __retval) ) (var_ref b) ) 
    139 (assign (constant bool (1)) (swiz z (var_ref __retval) ) (var_ref c) ) 
    140 
    141 If every masked update of a component relies on the previous value of
    142 the variable, then we're probably going to be quite limited in our
    143 dead code elimination wins, and recognizing common expressions may
    144 just not happen.  On the other hand, if we operate channel-wise, then
    145 we'll be prone to optimizing the operation on one of the channels at
    146 the expense of making its instruction flow different from the other
    147 channels, and a vector-based GPU would end up with worse code than if
    148 we didn't optimize operations on that channel!
    149 
    150 Once again, it appears that our optimization requirements are driven
    151 significantly by the target architecture.  For now, targeting the Mesa
    152 IR backend, SSA does not appear to be that important to producing
    153 excellent code, but we do expect to do some SSA-based optimizations
    154 for the 965 fragment shader backend when that is developed.
    155 
    156 Q: How should I expand instructions that take multiple backend instructions?
    157 
    158 Sometimes you'll have to do the expansion in your code generation --
    159 see, for example, ir_to_mesa.cpp's handling of ir_unop_sqrt.  However,
    160 in many cases you'll want to do a pass over the IR to convert
    161 non-native instructions to a series of native instructions.  For
    162 example, for the Mesa backend we have ir_div_to_mul_rcp.cpp because
    163 Mesa IR (and many hardware backends) only have a reciprocal
    164 instruction, not a divide.  Implementing non-native instructions this
    165 way gives the chance for constant folding to occur, so (a / 2.0)
    166 becomes (a * 0.5) after codegen instead of (a * (1.0 / 2.0))
    167 
    168 Q: How shoud I handle my special hardware instructions with respect to IR?
    169 
    170 Our current theory is that if multiple targets have an instruction for
    171 some operation, then we should probably be able to represent that in
    172 the IR.  Generally this is in the form of an ir_{bin,un}op expression
    173 type.  For example, we initially implemented fract() using (a -
    174 floor(a)), but both 945 and 965 have instructions to give that result,
    175 and it would also simplify the implementation of mod(), so
    176 ir_unop_fract was added.  The following areas need updating to add a
    177 new expression type:
    178 
    179 ir.h (new enum)
    180 ir.cpp:get_num_operands() (used for ir_reader)
    181 ir.cpp:operator_strs (used for ir_reader)
    182 ir_constant_expression.cpp (you probably want to be able to constant fold)
    183 ir_validate.cpp (check users have the right types)
    184 
    185 You may also need to update the backends if they will see the new expr type:
    186 
    187 ../mesa/shaders/ir_to_mesa.cpp
    188 
    189 You can then use the new expression from builtins (if all backends
    190 would rather see it), or scan the IR and convert to use your new
    191 expression type (see ir_mod_to_fract, for example).
    192 
    193 Q: How is memory management handled in the compiler?
    194 
    195 The hierarchical memory allocator "talloc" developed for the Samba
    196 project is used, so that things like optimization passes don't have to
    197 worry about their garbage collection so much.  It has a few nice
    198 features, including low performance overhead and good debugging
    199 support that's trivially available.
    200 
    201 Generally, each stage of the compile creates a talloc context and
    202 allocates its memory out of that or children of it.  At the end of the
    203 stage, the pieces still live are stolen to a new context and the old
    204 one freed, or the whole context is kept for use by the next stage.
    205 
    206 For IR transformations, a temporary context is used, then at the end
    207 of all transformations, reparent_ir reparents all live nodes under the
    208 shader's IR list, and the old context full of dead nodes is freed.
    209 When developing a single IR transformation pass, this means that you
    210 want to allocate instruction nodes out of the temporary context, so if
    211 it becomes dead it doesn't live on as the child of a live node.  At
    212 the moment, optimization passes aren't passed that temporary context,
    213 so they find it by calling talloc_parent() on a nearby IR node.  The
    214 talloc_parent() call is expensive, so many passes will cache the
    215 result of the first talloc_parent().  Cleaning up all the optimization
    216 passes to take a context argument and not call talloc_parent() is left
    217 as an exercise.
    218 
    219 Q: What is the file naming convention in this directory?
    220 
    221 Initially, there really wasn't one.  We have since adopted one:
    222 
    223  - Files that implement code lowering passes should be named lower_*
    224    (e.g., lower_noise.cpp).
    225  - Files that implement optimization passes should be named opt_*.
    226  - Files that implement a class that is used throught the code should
    227    take the name of that class (e.g., ir_hierarchical_visitor.cpp).
    228  - Files that contain code not fitting in one of the previous
    229    categories should have a sensible name (e.g., glsl_parser.ypp).
    230