'scf' Dialect

Operation definition ¶

scf.condition (::mlir::scf::ConditionOp) ¶

loop continuation condition

Syntax:

operation ::= `scf.condition` `(` $condition `)` attr-dict ($args^ `:` type($args))?

This operation accepts the continuation (i.e., inverse of exit) condition of the scf.while construct. If its first argument is true, the “after” region of scf.while is executed, with the remaining arguments forwarded to the entry block of the region. Otherwise, the loop terminates.

Operands: ¶

scf.for (::mlir::scf::ForOp) ¶

for operation

The “scf.for” operation represents a loop taking 3 SSA value as operands that represent the lower bound, upper bound and step respectively. The operation defines an SSA value for its induction variable. It has one region capturing the loop body. The induction variable is represented as an argument of this region. This SSA value always has type index, which is the size of the machine word. The step is a value of type index, required to be positive. The lower and upper bounds specify a half-open range: the range includes the lower bound but does not include the upper bound.

The body region must contain exactly one block that terminates with “scf.yield”. Calling ForOp::build will create such a region and insert the terminator implicitly if none is defined, so will the parsing even in cases when it is absent from the custom format. For example:

scf.for %iv = %lb to %ub step %step {
  ... // body
}

scf.for can also operate on loop-carried variables and returns the final values after loop termination. The initial values of the variables are passed as additional SSA operands to the “scf.for” following the 3 loop control SSA values mentioned above (lower bound, upper bound and step). The operation region has equivalent arguments for each variable representing the value of the variable at the current iteration.

The region must terminate with a “scf.yield” that passes all the current iteration variables to the next iteration, or to the “scf.for” result, if at the last iteration. Note, that when the loop-carried variables are present, calling ForOp::build will not insert the terminator implicitly. The caller must insert “scf.yield” in that case.

“scf.for” results hold the final values after the last iteration. For example, to sum-reduce a memref:

func @reduce(%buffer: memref<1024xf32>, %lb: index,
             %ub: index, %step: index) -> (f32) {
  // Initial sum set to 0.
  %sum_0 = constant 0.0 : f32
  // iter_args binds initial values to the loop's region arguments.
  %sum = scf.for %iv = %lb to %ub step %step
      iter_args(%sum_iter = %sum_0) -> (f32) {
    %t = load %buffer[%iv] : memref<1024xf32>
    %sum_next = addf %sum_iter, %t : f32
    // Yield current iteration sum to next iteration %sum_iter or to %sum
    // if final iteration.
    scf.yield %sum_next : f32
  }
  return %sum : f32
}

If the “scf.for” defines any values, a yield must be explicitly present. The number and types of the “scf.for” results must match the initial values in the “iter_args” binding and the yield operands.

Another example with a nested “scf.if” (see “scf.if” for details) to perform conditional reduction:

func @conditional_reduce(%buffer: memref<1024xf32>, %lb: index,
                         %ub: index, %step: index) -> (f32) {
  %sum_0 = constant 0.0 : f32
  %c0 = constant 0.0 : f32
  %sum = scf.for %iv = %lb to %ub step %step
      iter_args(%sum_iter = %sum_0) -> (f32) {
    %t = load %buffer[%iv] : memref<1024xf32>
    %cond = cmpf "ugt", %t, %c0 : f32
    %sum_next = scf.if %cond -> (f32) {
      %new_sum = addf %sum_iter, %t : f32
      scf.yield %new_sum : f32
    } else {
      scf.yield %sum_iter : f32
    }
    scf.yield %sum_next : f32
  }
  return %sum : f32
}

Operands: ¶

Results: ¶

scf.if (::mlir::scf::IfOp) ¶

if-then-else operation

The scf.if operation represents an if-then-else construct for conditionally executing two regions of code. The operand to an if operation is a boolean value. For example:

scf.if %b  {
  ...
} else {
  ...
}

scf.if may also return results that are defined in its regions. The values defined are determined by which execution path is taken.

Example:

%x, %y = scf.if %b -> (f32, f32) {
  %x_true = ...
  %y_true = ...
  scf.yield %x_true, %y_true : f32, f32
} else {
  %x_false = ...
  %y_false = ...
  scf.yield %x_false, %y_false : f32, f32
}

scf.if regions are always terminated with “scf.yield”. If “scf.if” defines no values, the “scf.yield” can be left out, and will be inserted implicitly. Otherwise, it must be explicit. Also, if “scf.if” defines one or more values, the ‘else’ block cannot be omitted.

Example:

scf.if %b  {
  ...
}

Operands: ¶

Results: ¶

scf.parallel (::mlir::scf::ParallelOp) ¶

parallel for operation

The “scf.parallel” operation represents a loop nest taking 4 groups of SSA values as operands that represent the lower bounds, upper bounds, steps and initial values, respectively. The operation defines a variadic number of SSA values for its induction variables. It has one region capturing the loop body. The induction variables are represented as an argument of this region. These SSA values always have type index, which is the size of the machine word. The steps are values of type index, required to be positive. The lower and upper bounds specify a half-open range: the range includes the lower bound but does not include the upper bound. The initial values have the same types as results of “scf.parallel”. If there are no results, the keyword init can be omitted.

Semantically we require that the iteration space can be iterated in any order, and the loop body can be executed in parallel. If there are data races, the behavior is undefined.

The parallel loop operation supports reduction of values produced by individual iterations into a single result. This is modeled using the scf.reduce operation (see scf.reduce for details). Each result of a scf.parallel operation is associated with an initial value operand and reduce operation that is an immediate child. Reductions are matched to result and initial values in order of their appearance in the body. Consequently, we require that the body region has the same number of results and initial values as it has reduce operations.

The body region must contain exactly one block that terminates with “scf.yield” without operands. Parsing ParallelOp will create such a region and insert the terminator when it is absent from the custom format.

Example:

%init = constant 0.0 : f32
scf.parallel (%iv) = (%lb) to (%ub) step (%step) init (%init) -> f32 {
  %elem_to_reduce = load %buffer[%iv] : memref<100xf32>
  scf.reduce(%elem_to_reduce) : f32 {
    ^bb0(%lhs : f32, %rhs: f32):
      %res = addf %lhs, %rhs : f32
      scf.reduce.return %res : f32
  }
}

Operands: ¶

Results: ¶

scf.reduce (::mlir::scf::ReduceOp) ¶

reduce operation for parallel for

“scf.reduce” is an operation occurring inside “scf.parallel” operations. It consists of one block with two arguments which have the same type as the operand of “scf.reduce”.

“scf.reduce” is used to model the value for reduction computations of a “scf.parallel” operation. It has to appear as an immediate child of a “scf.parallel” and is associated with a result value of its parent operation.

Association is in the order of appearance in the body where the first result of a parallel loop operation corresponds to the first “scf.reduce” in the operation’s body region. The reduce operation takes a single operand, which is the value to be used in the reduction.

The reduce operation contains a region whose entry block expects two arguments of the same type as the operand. As the iteration order of the parallel loop and hence reduction order is unspecified, the result of reduction may be non-deterministic unless the operation is associative and commutative.

The result of the reduce operation’s body must have the same type as the operands and associated result value of the parallel loop operation. Example:

%operand = constant 1.0 : f32
scf.reduce(%operand) : f32 {
  ^bb0(%lhs : f32, %rhs: f32):
    %res = addf %lhs, %rhs : f32
    scf.reduce.return %res : f32
}

Operands: ¶

scf.reduce.return (::mlir::scf::ReduceReturnOp) ¶

terminator for reduce operation

Syntax:

operation ::= `scf.reduce.return` $result attr-dict `:` type($result)

“scf.reduce.return” is a special terminator operation for the block inside “scf.reduce”. It terminates the region. It should have the same type as the operand of “scf.reduce”. Example for the custom format:

scf.reduce.return %res : f32

Operands: ¶

scf.while (::mlir::scf::WhileOp) ¶

a generic ‘while’ loop

This operation represents a generic “while”/“do-while” loop that keeps iterating as long as a condition is satisfied. There is no restriction on the complexity of the condition. It consists of two regions (with single block each): “before” region and “after” region. The names of regions indicates whether they execute before or after the condition check. Therefore, if the main loop payload is located in the “before” region, the operation is a “do-while” loop. Otherwise, it is a “while” loop.

The “before” region terminates with a special operation, scf.condition, that accepts as its first operand an i1 value indicating whether to proceed to the “after” region (value is true) or not. The two regions communicate by means of region arguments. Initially, the “before” region accepts as arguments the operands of the scf.while operation and uses them to evaluate the condition. It forwards the trailing, non-condition operands of the scf.condition terminator either to the “after” region if the control flow is transferred there or to results of the scf.while operation otherwise. The “after” region takes as arguments the values produced by the “before” region and uses scf.yield to supply new arguments for the “after” region, into which it transfers the control flow unconditionally.

A simple “while” loop can be represented as follows.

%res = scf.while (%arg1 = %init1) : (f32) -> f32 {
  /* "Before" region.
   * In a "while" loop, this region computes the condition. */
  %condition = call @evaluate_condition(%arg1) : (f32) -> i1

  /* Forward the argument (as result or "after" region argument). */
  scf.condition(%condition) %arg1 : f32

} do {
^bb0(%arg2: f32):
  /* "After region.
   * In a "while" loop, this region is the loop body. */
  %next = call @payload(%arg2) : (f32) -> f32

  /* Forward the new value to the "before" region.
   * The operand types must match the types of the `scf.while` operands. */
  scf.yield %next : f32
}

A simple “do-while” loop can be represented by reducing the “after” block to a simple forwarder.

%res = scf.while (%arg1 = %init1) : (f32) -> f32 {
  /* "Before" region.
   * In a "do-while" loop, this region contains the loop body. */
  %next = call @payload(%arg1) : (f32) -> f32

  /* And also evaluates the condition. */
  %condition = call @evaluate_condition(%arg1) : (f32) -> i1

  /* Loop through the "after" region. */
  scf.condition(%condition) %next : f32

} do {
^bb0(%arg2: f32):
  /* "After" region.
   * Forwards the values back to "before" region unmodified. */
  scf.yield %arg2 : f32
}

Note that the types of region arguments need not to match with each other. The op expects the operand types to match with argument types of the “before” region”; the result types to match with the trailing operand types of the terminator of the “before” region, and with the argument types of the “after” region. The following scheme can be used to share the results of some operations executed in the “before” region with the “after” region, avoiding the need to recompute them.

%res = scf.while (%arg1 = %init1) : (f32) -> i64 {
  /* One can perform some computations, e.g., necessary to evaluate the
   * condition, in the "before" region and forward their results to the
   * "after" region. */
  %shared = call @shared_compute(%arg1) : (f32) -> i64

  /* Evaluate the condition. */
  %condition = call @evaluate_condition(%arg1, %shared) : (f32, i64) -> i1

  /* Forward the result of the shared computation to the "after" region.
   * The types must match the arguments of the "after" region as well as
   * those of the `scf.while` results. */
  scf.condition(%condition) %shared : i64

} do {
^bb0(%arg2: i64) {
  /* Use the partial result to compute the rest of the payload in the
   * "after" region. */
  %res = call @payload(%arg2) : (i64) -> f32

  /* Forward the new value to the "before" region.
   * The operand types must match the types of the `scf.while` operands. */
  scf.yield %res : f32
}

The custom syntax for this operation is as follows.

op ::= `scf.while` assignments `:` function-type region `do` region
       `attributes` attribute-dict
initializer ::= /* empty */ | `(` assignment-list `)`
assignment-list ::= assignment | assignment `,` assignment-list
assignment ::= ssa-value `=` ssa-value

Operands: ¶

Results: ¶

scf.yield (::mlir::scf::YieldOp) ¶

loop yield and termination operation

Syntax:

operation ::= `scf.yield` attr-dict ($results^ `:` type($results))?

“scf.yield” yields an SSA value from the SCF dialect op region and terminates the regions. The semantics of how the values are yielded is defined by the parent operation. If “scf.yield” has any operands, the operands must match the parent operation’s results. If the parent operation defines no values, then the “scf.yield” may be left out in the custom syntax and the builders will insert one implicitly. Otherwise, it has to be present in the syntax to indicate which values are yielded.

Operands: ¶