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authorIan Romanick <[email protected]>2016-07-12 12:44:18 -0700
committerIan Romanick <[email protected]>2016-08-30 16:28:02 -0700
commitd8dd49419aebf025fece1a2342dd880e7504c2e5 (patch)
tree5b71c725e3c289ec5e8fc0d8c8130fe39d87e30e /src/compiler
parent8954a019f7e9098738c7cc25ed097e7f85c24def (diff)
glsl: Generate code for constant ir_binop_mul expressions
v2: 'for (a, b) in d' => 'for a, b in d'. Suggested by Dylan. Signed-off-by: Ian Romanick <[email protected]> Reviewed-by: Matt Turner <[email protected]> Acked-by: Dylan Baker <[email protected]>
Diffstat (limited to 'src/compiler')
-rw-r--r--src/compiler/glsl/ir_expression_operation.py56
1 files changed, 54 insertions, 2 deletions
diff --git a/src/compiler/glsl/ir_expression_operation.py b/src/compiler/glsl/ir_expression_operation.py
index de3b866bb96..7d82ea80dd2 100644
--- a/src/compiler/glsl/ir_expression_operation.py
+++ b/src/compiler/glsl/ir_expression_operation.py
@@ -190,6 +190,56 @@ constant_template_vector_scalar = mako.template.Template("""\
}
break;""")
+# This template is for multiplication. It is unique because it has to support
+# matrix * vector and matrix * matrix operations, and those are just different.
+constant_template_mul = mako.template.Template("""\
+ case ${op.get_enum_name()}:
+ /* Check for equal types, or unequal types involving scalars */
+ if ((op[0]->type == op[1]->type && !op[0]->type->is_matrix())
+ || op0_scalar || op1_scalar) {
+ for (unsigned c = 0, c0 = 0, c1 = 0;
+ c < components;
+ c0 += c0_inc, c1 += c1_inc, c++) {
+
+ switch (op[0]->type->base_type) {
+ % for dst_type, src_types in op.signatures():
+ case ${src_types[0].glsl_type}:
+ data.${dst_type.union_field}[c] = ${op.get_c_expression(src_types, ("c0", "c1", "c2"))};
+ break;
+ % endfor
+ default:
+ assert(0);
+ }
+ }
+ } else {
+ assert(op[0]->type->is_matrix() || op[1]->type->is_matrix());
+
+ /* Multiply an N-by-M matrix with an M-by-P matrix. Since either
+ * matrix can be a GLSL vector, either N or P can be 1.
+ *
+ * For vec*mat, the vector is treated as a row vector. This
+ * means the vector is a 1-row x M-column matrix.
+ *
+ * For mat*vec, the vector is treated as a column vector. Since
+ * matrix_columns is 1 for vectors, this just works.
+ */
+ const unsigned n = op[0]->type->is_vector()
+ ? 1 : op[0]->type->vector_elements;
+ const unsigned m = op[1]->type->vector_elements;
+ const unsigned p = op[1]->type->matrix_columns;
+ for (unsigned j = 0; j < p; j++) {
+ for (unsigned i = 0; i < n; i++) {
+ for (unsigned k = 0; k < m; k++) {
+ if (op[0]->type->base_type == GLSL_TYPE_DOUBLE)
+ data.d[i+n*j] += op[0]->value.d[i+n*k]*op[1]->value.d[k+m*j];
+ else
+ data.f[i+n*j] += op[0]->value.f[i+n*k]*op[1]->value.f[k+m*j];
+ }
+ }
+ }
+ }
+ break;""")
+
# This template is for operations that are horizontal and either have only a
# single type or the implementation for all types is identical. That is, the
# operation consumes a vector and produces a scalar.
@@ -285,7 +335,9 @@ class operation(object):
else:
return constant_template3.render(op=self)
elif self.num_operands == 2:
- if vector_scalar_operation in self.flags:
+ if self.name == "mul":
+ return constant_template_mul.render(op=self)
+ elif vector_scalar_operation in self.flags:
return constant_template_vector_scalar.render(op=self)
elif horizontal_operation in self.flags and types_identical_operation in self.flags:
return constant_template_horizontal_single_implementation.render(op=self)
@@ -454,7 +506,7 @@ ir_expression_operation = [
operation("add", 2, printable_name="+", source_types=numeric_types, c_expression="{src0} + {src1}", flags=vector_scalar_operation),
operation("sub", 2, printable_name="-", source_types=numeric_types, c_expression="{src0} - {src1}", flags=vector_scalar_operation),
# "Floating-point or low 32-bit integer multiply."
- operation("mul", 2, printable_name="*"),
+ operation("mul", 2, printable_name="*", source_types=numeric_types, c_expression="{src0} * {src1}"),
operation("imul_high", 2), # Calculates the high 32-bits of a 64-bit multiply.
operation("div", 2, printable_name="/", source_types=numeric_types, c_expression={'u': "{src1} == 0 ? 0 : {src0} / {src1}", 'i': "{src1} == 0 ? 0 : {src0} / {src1}", 'default': "{src0} / {src1}"}, flags=vector_scalar_operation),