[llvm-dev] [RFC] IR-level Region Annotations
Hal Finkel via llvm-dev
llvm-dev at lists.llvm.org
Wed Jan 11 14:02:52 PST 2017
A Proposal for adding an experimental IR-level region-annotation
infrastructure
=============================================================================
Hal Finkel (ANL) and Xinmin Tian (Intel)
This is a proposal for adding an experimental infrastructure to support
annotating regions in LLVM IR, making use of intrinsics and metadata, and
a generic analysis to allow transformations to easily make use of these
annotated regions. This infrastructure is flexible enough to support
representation of directives for parallelization, vectorization, and
offloading of both loops and more-general code regions. Under this scheme,
the conceptual distance between source-level directives and the region
annotations need not be significant, making the incremental cost of
supporting new directives and modifiers often small. It is not, however,
specific to those use cases.
Problem Statement
=================
There are a series of discussions on LLVM IR extensions for representing
region
and loop annotations for parallelism, and other user-guided
transformations,
among both industrial and academic members of the LLVM community.
Increasing
the quality of our OpenMP implementation is an important motivating use
case,
but certainly not the only one. For OpenMP in particular, we've discussed
having an IR representation for years. Presently, all OpenMP pragmas are
transformed directly into runtime-library calls in Clang, and outlining
(i.e.
extracting parallel regions into their own functions to be invoked by the
runtime library) is done in Clang as well. Our implementation does not
further
optimize OpenMP constructs, and a lot of thought has been put into how
we might
improve this. For some optimizations, such as redundant barrier removal, we
could use a TargetLibraryInfo-like mechanism to recognize
frontend-generated
runtime calls and proceed from there. Dealing with cases where we lose
pointer-aliasing information, information on loop bounds, etc. we could
improve
by improving our inter-procedural-analysis capabilities. We should do that
regardless. However, there are important cases where the underlying
scheme we
want to use to lower the various parallelism constructs, especially when
targeting accelerators, changes depending on what is in the parallel
region.
In important cases where we can see everything (i.e. there aren't arbitrary
external calls), code generation should proceed in a way that is very
different
from the general case. To have a sensible implementation, this must be done
after inlining. When using LTO, this should be done during the link-time
phase.
As a result, we must move away from our purely-front-end based lowering
scheme.
The question is what to do instead, and how to do it in a way that is
generally
useful to the entire community.
Designs previously discussed can be classified into four categories:
(a) Add a large number of new kinds of LLVM metadata, and use them to
annotate
each necessary instruction for parallelism, data attributes, etc.
(b) Add several new LLVM instructions such as, for parallelism, fork,
spawn,
join, barrier, etc.
(c) Add a large number of LLVM intrinsics for directives and clauses, each
intrinsic representing a directive or a clause.
(d) Add a small number of LLVM intrinsics for region or loop annotations,
represent the directive/clause names using metadata and the remaining
information using arguments.
Here we're proposing (d), and below is a brief pros and cons analysis
based on
these discussions and our own experiences of supporting region/loop
annotations
in LLVM-based compilers. The table below shows a short summary of our
analysis.
Various commercial compilers (e.g. from Intel, IBM, Cray, PGI), and GCC
[1,2],
have IR-level representations for parallelism constructs. Based on
experience
from these previous developments, we'd like a solution for LLVM that
maximizes
optimization enablement while minimizing the maintenance costs and
complexity
increase experienced by the community as a whole.
Representing the desired information in the LLVM IR is just the first
step. The
challenge is to maintain the desired semantics without blocking useful
optimizations. With options (c) and (d), dependencies can be preserved
mainly
based on the use/def chain of the arguments of each intrinsic, and a
manageable
set LLVM analysis and transformations can be made aware of certain kinds of
annotations in order to enable specific optimizations. In this regard,
options (c) and (d) are close with respect to maintenance efforts. However,
based on our experiences, option (d) is preferable because it is easier to
extend to support new directives and clauses in the future without the
need to
add new intrinsics as required by option (c).
Table 1. Pros/cons summary of LLVM IR experimental extension options
--------+----------------------+-----------------------------------------------
Options | Pros | Cons
--------+----------------------+-----------------------------------------------
(a) | No need to add new | LLVM passes do not always maintain
metadata.
| instructions or | Need to educate many passes (if not
all) to
| new intrinsics | understand and handle them.
--------+----------------------+-----------------------------------------------
(b) | Parallelism becomes | Huge effort for extending all LLVM
passes and
| first class citizen | code generation to support new
instructions.
| | A large set of information still needs
to be
| | represented using other means.
--------+----------------------+-----------------------------------------------
(c) | Less impact on the | A large number of intrinsics must be
added.
| exist LLVM passes. | Some of the optimizations need to be
| Fewer requirements | educated to understand them.
| for passes to |
| maintain metadata. |
--------+----------------------+-----------------------------------------------
(d) | Minimal impact on | Some of the optimizations need to be
| existing LLVM | educated to understand them.
| optimizations passes.| No requirements for all passes to
maintain
| directive and clause | large set of metadata with values.
| names use metadata |
| strings. |
--------+----------------------+-----------------------------------------------
Regarding (a), LLVM already uses metadata for certain loop information
(e.g.
annotations directing loop transformations and assertions about
loop-carried
dependencies), but there is no natural or consistent way to extend this
scheme
to represent necessary data-movement or region information.
New Intrinsics for Region and Value Annotations
==============================================
The following new (experimental) intrinsics are proposed which allow:
a) Annotating a code region marked with directives / pragmas,
b) Annotating values associated with the region (or loops), that is, those
values associated with directives / pragmas.
c) Providing information on LLVM IR transformations needed for the
annotated
code regions (or loops).
These can be used both by frontends and also by transformation passes (e.g.
automated parallelization). The names used here are similar to those
used by
our internal prototype, but obviously we expect a community bikeshed
discussion.
def int_experimental_directive : Intrinsic<[], [llvm_metadata_ty],
[IntrArgMemOnly],
"llvm.experimental.directive">;
def int_experimental_dir_qual : Intrinsic<[], [llvm_metadata_ty],
[IntrArgMemOnly],
"llvm.experimental.dir.qual">;
def int_experimental_dir_qual_opnd : Intrinsic<[],
[llvm_metadata_ty, llvm_any_ty],
[IntrArgMemOnly],
"llvm.experimental.dir.qual.opnd">;
def int_experimental_dir_qual_opndlist : Intrinsic<
[],
[llvm_metadata_ty, llvm_vararg_ty],
[IntrArgMemOnly],
"llvm.experimental.dir.qual.opndlist">;
Note that calls to these intrinsics might need to be annotated with the
convergent attribute when they represent fork/join operations, barriers,
and
similar.
Usage Examples
==============
This section shows a few examples using these experimental intrinsics.
LLVM developers who will use these intrinsics can defined their own
MDstring.
All details of using these intrinsics on representing OpenMP 4.5
constructs are described in [1][3].
Example I: An OpenMP combined construct
#pragma omp target teams distribute parallel for simd
loop
LLVM IR
-------
call void @llvm.experimental.directive(metadata !0)
call void @llvm.experimental.directive(metadata !1)
call void @llvm.experimental.directive(metadata !2)
call void @llvm.experimental.directive(metadata !3)
loop
call void @llvm.experimental.directive(metadata !6)
call void @llvm.experimental.directive(metadata !5)
call void @llvm.experimental.directive(metadata !4)
!0 = metadata !{metadata !DIR.OMP.TARGET}
!1 = metadata !{metadata !DIR.OMP.TEAMS}
!2 = metadata !{metadata !DIR.OMP.DISTRIBUTE.PARLOOP.SIMD}
!6 = metadata !{metadata !DIR.OMP.END.DISTRIBUTE.PARLOOP.SIMD}
!5 = metadata !{metadata !DIR.OMP.END.TEAMS}
!4 = metadata !{metadata !DIR.OMP.END.TARGET}
Example II: Assume x,y,z are int variables, and s is a non-POD variable.
Then, lastprivate(x,y,s,z) is represented as:
LLVM IR
-------
call void @llvm.experimental.dir.qual.opndlist(
metadata !1, %x, %y, metadata !2, %a, %ctor, %dtor, %z)
!1 = metadata !{metadata !QUAL.OMP.PRIVATE}
!2 = metadata !{metadata !QUAL.OPND.NONPOD}
Example III: A prefetch pragma example
// issue vprefetch1 for xp with a distance of 20 vectorized iterations
ahead
// issue vprefetch0 for yp with a distance of 10 vectorized iterations
ahead
#pragma prefetch x:1:20 y:0:10
for (i=0; i<2*N; i++) { xp[i*m + j] = -1; yp[i*n +j] = -2; }
LLVM IR
-------
call void @llvm.experimental.directive(metadata !0)
call void @llvm.experimental.dir.qual.opnslist(metadata !1, %xp, 1, 20,
metadata !1, %yp, 0, 10)
loop
call void @llvm.experimental.directive(metadata !3)
References
==========
[1] LLVM Framework and IR extensions for Parallelization, SIMD
Vectorization
and Offloading Support. SC'2016 LLVM-HPC3 Workshop. (Xinmin Tian
et.al.)
Saltlake City, Utah.
[2] Extending LoopVectorizer towards supporting OpenMP4.5 SIMD and outer
loop
auto-vectorization. (Hideki Saito, et.al.) LLVM Developers' Meeting
2016,
San Jose.
[3] Intrinsics, Metadata, and Attributes: The Story continues! (Hal Finkel)
LLVM Developers' Meeting, 2016. San Jose
[4] LLVM Intrinsic Function and Metadata String Interface for Directive (or
Pragmas) Representation. Specification Draft v0.9, Intel
Corporation, 2016.
Acknowledgements
================
We would like to thank Chandler Carruth (Google), Johannes Doerfert
(Saarland
Univ.), Yaoqing Gao (HuaWei), Michael Wong (Codeplay), Ettore Tiotto,
Carlo Bertolli, Bardia Mahjour (IBM), and all other LLVM-HPC IR
Extensions WG
members for their constructive feedback on the LLVM framework and IR
extension
proposal.
Proposed Implementation
=======================
Two sets of patches of supporting these experimental intrinsics and
demonstrate
the usage are ready for community review.
a) Clang patches that support core OpenMP pragmas using this approach.
b) W-Region framework patches: CFG restructuring to form single-entry-
single-exit work region (W-Region) based on annotations, Demand-driven
intrinsic parsing, and WRegionInfo collection and analysis passes,
Dump functions of WRegionInfo.
On top of this functionality, we will provide the transformation patches
for
core OpenMP constructs (e.g. start with "#pragma omp parallel for" loop for
lowering and outlining, and "#pragma omp simd" to hook it up with
LoopVectorize.cpp). We have internal implementations for many constructs
now.
We will break this functionality up to create a series of patches for
community review.
--
Hal Finkel
Lead, Compiler Technology and Programming Languages
Leadership Computing Facility
Argonne National Laboratory
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