`DO CONCURRENT` isn’t necessarily concurrent¶

A variant form of Fortran’s primary looping construct was added to the Fortran 2008 language standard with the apparent intent of enabling more effective automatic parallel execution of code written in the standard language without the use of non-standard directives. Spelled DO CONCURRENT, the construct takes a rectilinear iteration space specification like FORALL and allows us to write a multidimensional loop nest construct with a single DO CONCURRENT statement and a single terminating END DO statement.

Within the body of a DO CONCURRENT loop the program must respect a long list of restrictions on its use of Fortran language features. Actions that obviously can’t be executed in parallel or that don’t allow all iterations to execute are prohibited. These include:

Control flow statements that would prevent the loop nest from executing all its iterations: RETURN, EXIT, and any GOTO or CYCLE that leaves the construct.
Image control statements: STOP, SYNC, LOCK/UNLOCK, EVENT, and ALLOCATE/DEALLOCATE of a coarray.
Calling a procedure that is not PURE.
Deallocation of any polymorphic entity, as that could cause an impure FINAL subroutine to be called.
Messing with the IEEE floating-point control and status flags.
Accepting some restrictions on data flow between iterations (i.e., none) and on liveness of modified objects after the loop. (The details are spelled out later.)

In return for accepting these restrictions, a DO CONCURRENT might compile into code that exploits the parallel features of the target machine to run the iterations of the DO CONCURRENT construct. One needn’t necessarily require OpenACC or OpenMP directives.

But it turns out that these rules, though necessary for safe parallel execution, are not sufficient. One may write conforming DO CONCURRENT constructs that cannot be safely parallelized by a compiler; worse, one may write conforming DO CONCURRENT constructs whose parallelizability a compiler cannot determine even in principle – forcing a conforming compiler to assume the worst and generate sequential code.

Localization ¶

The Fortran language standard does not actually define DO CONCURRENT as a concurrent construct, or even as a construct that imposes sufficient requirements on the programmer to allow for parallel execution. DO CONCURRENT is instead defined as executing the iterations of the loop in some arbitrary order (see subclause 11.1.7.4.3 paragraph 3).

A DO CONCURRENT construct cannot modify an object in one iteration and expect to be able to read it in another, or read it in one before it gets modified by another – there’s no way to synchronize inter-iteration communication with critical sections or atomics.

But a conforming DO CONCURRENT construct can modify an object in multiple iterations of the loop so long as its only reads from that object after having modified it earler in the same iteration. (See 11.1.7.5 paragraph 4 for the details.)

For example:

  DO CONCURRENT (J=1:N)
    TMP = A(J) + B(J)
    C(J) = TMP
  END DO
  ! And TMP is undefined afterwards

The scalar variable TMP is used in this loop in a way that conforms to the standard, as every use of TMP follows a definition that appears earlier in the same iteration.

The idea, of course, is that a parallelizing compiler isn’t required to use the same word of memory to hold the value of TMP; for parallel execution, TMP can be localized. This means that the loop can be internally rewritten as if it had been

  DO CONCURRENT (J=1:N)
    BLOCK
      REAL :: TMP
      TMP = A(J) + B(J)
      C(J) = TMP
    END BLOCK
  END DO

and thus any risk of data flow between the iterations is removed.

The identification problem ¶

The automatic localization rules of DO CONCURRENT that allow usage like TMP above are not limited to simple local scalar variables. They also apply to arbitrary variables, and thus may apply in cases that a compiler cannot determine exactly due to the presence of indexing, indirection, and interprocedural data flow.

Let’s see why this turns out to be a problem.

Examples:

  DO CONCURRENT (J=1:N)
    T(IX(J)) = A(J) + B(J)
    C(J) = T(IY(J))
  END DO

This loop conforms to the standard language if, whenever IX(J) equals IY(J') for any distinct pair of iterations J and J', then the load must be reading a value stored earlier in the same iteration – so IX(J')==IY(J'), and hence IX(J)==IX(J') too, in this example. Otherwise, a load in one iteration might depend on a store in another.

When all values of IX(J) are distinct, and the program conforms to the restrictions of DO CONCURRENT, a compiler can parallelize the construct easily without applying localization to T(...). And when some values of IX(J) are duplicates, a compiler can parallelize the loop by forwarding the stored value to the load in those iterations. But at compilation time, there’s no way to distinguish these cases in general, and a conservative implementation has to assume the worst and run the loop’s iterations serially. (Or compare IX(J) with IY(J) at runtime and forward the stored value conditionally, which adds overhead and becomes quickly impractical in loops with multiple loads and stores.)

  TYPE :: T
    REAL, POINTER :: P
  END TYPE
  TYPE(T) :: T1(N), T2(N)
  DO CONCURRENT (J=1:N)
    T1(J)%P = A(J) + B(J)
    C(J) = T2(J)%P
  END DO

we have the same kind of ambiguity from the compiler’s perspective. Are the targets of the pointers used for the stores all distinct from the targets of the pointers used for the loads? The programmer may know that they are so, but a compiler cannot; and there is no syntax by which one can stipulate that they are so.

The global variable localization problem ¶

Here’s another case:

  MODULE M
    REAL :: T
  END MODULE
  ...
  USE M
  INTERFACE
    PURE REAL FUNCTION F(X)
      REAL, INTENT(IN) :: X
    END FUNCTION
  END INTERFACE
  DO CONCURRENT (J=1:N)
    T = A(J) + B(J)
    D(J) = F(A(J)) + T
  END DO

The variable T is obviously meant to be localized. However, a compiler can’t be sure that the pure function F doesn’t read from T; if it does, there wouldn’t be a practical way to convey the localized copy to it.

In summary, standard Fortran defines DO CONCURRENT as a serial construct with a sheaf of constraints that we assume are intended to enable straightforward parallelization without all of the complexity of defining threading models or shared memory semantics, with the addition of an automatic localization rule that provides convenient temporaries objects without requiring the use of nested BLOCK or ASSOCIATE constructs. But the language allows ambiguous cases in which a compiler can neither

prove that automatic localization is required for a given object in every iteration, nor
prove that automatic localization isn’t required in any iteration.

Locality specifiers ¶

The Fortran 2018 standard added “locality specifiers” to the DO CONCURRENT statement. These allow one to define some variable names as being LOCAL or SHARED, overriding the automatic localization rule so that it applies only in the remaining cases of “unspecified” locality.

LOCAL variables are those that can be defined by more than one iteration but are referenced only after having been defined earlier in the same iteration. SHARED variables are those that, if defined in any iteration, are not defined or referenced in any other iteration.

(There is also a LOCAL_INIT specifier that is not relevant to the problem at hand, and a DEFAULT(NONE) specifier that requires a locality specifier be present for every variable mentioned in the DO CONCURRENT construct.)

These locality specifiers can help resolve some otherwise ambiguous cases of localization, but they’re not a complete solution to the problems described above.

First, the specifiers allow explicit localization of objects (like the scalar T in MODULE M above) that are not local variables of the subprogram. DO CONCURRENT still allows a pure procedure called from the loop to reference T, and so explicit localization just confirms the worst-case assumptions about interprocedural data flow within an iteration that a compiler must make anyway.

Second, the specifiers allow arbitary variables to be localized, not just scalars. One may localize a million-element array of derived type with allocatable components to be created in each iteration, for example. (It is not clear whether localized objects are finalized; probably not.)

Third, as Fortran uses context to distinguish references to pointers from (de)references to their targets, it’s not clear whether LOCAL(PTR) localizes a pointer, its target, or both.

Fourth, the specifiers can be applied only to variable names, not to any designator with subscripts or component references. One may have defined a derived type to hold a representation of a sparse matrix, using ALLOCATABLE components to store its packed data and indexing structures, but a program cannot localize some parts of it and share the rest. (Perhaps one may wrap ASSOCIATE constructs around the DO CONCURRENT construct; the interaction between locality specifiers and construct entities is not clearly defined in the language.)

In the example above that defines T(IX(J)) and reads from T(IY(J)), the locality specifiers can’t be used to share those elements of T() that are modified at most once and localize the cases where IX(J) is a duplicate and IY(J)==IX(J).

Last, when a loop both defines and references many shared objects, including potential references to globally accessible object in called procedures, one may need to name all of them in a SHARED specifier.

What to do now ¶

These problems have been presented to the J3 Fortran language standard committee. Their responses in recent e-mail discussions did not include an intent to address them in future standards or corrigenda. The most effective-looking response – which was essentially “just use DEFAULT(SHARED) to disable all automatic localization” – is not an viable option, since the language does not include such a specifier!

Programmers writing DO CONCURRENT loops that are safely parallelizable need an effective means to convey to compilers that those compilers do not have to assume only the weaker stipulations required by today’s DO CONCURRENT without having to write verbose and error-prone locality specifiers (when those would suffice). Specifically, an easy means is required that stipulates that localization should apply at most only to the obvious cases of local non-pointer non-allocatable scalars.

In the LLVM Fortran compiler project (a/k/a “flang”, “f18”) we considered several solutions to this problem.

Add syntax (e.g., DO PARALLEL or DO CONCURRENT() DEFAULT(PARALLEL)) by which one can inform the compiler that it should localize only the obvious cases of simple local scalars. Such syntax seems unlikely to ever be standardized, so its usage would be nonportable.
Add a command-line option &/or a source directive to stipulate the stronger guarantees. Obvious non-parallelizable usage in the construct would elicit a stern warning. The DO CONCURRENT loops in the source would continue to be portable to other compilers.
Assume that these stronger conditions hold by default, and add a command-line option &/or a source directive to “opt out” back to the weaker requirements of the standard language in the event that the program contains one of those inherently non-parallelizable DO CONCURRENT loops that perhaps should never have been possible to write in a conforming program in the first place. Actual parallel DO CONCURRENT constructs would produce parallel code for users who would otherwise be surprised to learn about these problems in the language. But this option could lead to non-standard behavior for codes that depend, accidentally or not, on non-parallelizable implicit localization.
Accept the standard as it exists, do the best job of automatic parallelization that can be done, and refer dissatisfied users to J3. This would be avoiding the problem.

None of these options is without a fairly obvious disadvantage. The best option seems to be the one that assumes that users who write DO CONCURRENT constructs are doing so with the intent to write parallel code.

Other precedents ¶

As of August 2020, we observe that the GNU Fortran compiler (10.1) does not yet implement the Fortran 2018 locality clauses, but will parallelize some DO CONCURRENT constructs without ambiguous data dependences when the automatic parallelization option is enabled.

The Intel Fortran compiler supports the new locality clauses and will parallelize some DO CONCURRENT constructs when automatic parallelization option is enabled. When OpenMP is enabled, ifort reports that all DO CONCURRENT constructs are parallelized, but they seem to execute in a serial fashion when data flow hazards are present.

The Flang Compiler