[llvm-dev] [cfe-dev] [RFC] Moving (parts of) the Cling REPL in Clang

Fri Jul 10 13:10:44 PDT 2020

Hi Vassil,

This is a very exciting proposal that I can imagine bringing important
benefits to the existing cling users and also to the clang user and
developer community. Thank you for all the work you and your team have done
on cling so far and for offering to bring that work under the LLVM umbrella!

Are you imagining cling being part of the clang repository, or a separate
LLVM subproject (with only the changes necessary to support cling-style
uses of the clang libraries added to the clang tree)?

On Thu, 9 Jul 2020 at 13:46, Vassil Vassilev via cfe-dev <
cfe-dev at lists.llvm.org> wrote:

> Motivation
> ===
>
> Over the last decade we have developed an interactive, interpretative
> C++ (aka REPL) as part of the high-energy physics (HEP) data analysis
> project -- ROOT [1-2]. We invested a significant  effort to replace the
> CINT C++ interpreter with a newly implemented REPL based on llvm --
> cling [3]. The cling infrastructure is a core component of the data
> analysis framework of ROOT and runs in production for approximately 5
> years.
>
> Cling is also  a standalone tool, which has a growing community outside
> of our field. Cling’s user community includes users in finance, biology
> and in a few companies with proprietary software. For example, there is
> a xeus-cling jupyter kernel [4]. One of the major challenges we face to
> foster that community is  our cling-related patches in llvm and clang
> forks. The benefits of using the LLVM community standards for code
> reviews, release cycles and integration has been mentioned a number of
> times by our "external" users.
>
> Last year we were awarded an NSF grant to improve cling's sustainability
> and make it a standalone tool. We thank the LLVM Foundation Board for
> supporting us with a non-binding letter of collaboration which was
> essential for getting this grant.
>
>
> Background
> ===
>
> Cling is a C++ interpreter built on top of clang and llvm. In a
> nutshell, it uses clang's incremental compilation facilities to process
> code chunk-by-chunk by assuming an ever-growing translation unit [5].
> Then code is lowered into llvm IR and run by the llvm jit. Cling has
> implemented some language "extensions" such as execution statements on
> the global scope and error recovery. Cling is in the core of HEP -- it
> is heavily used during data analysis of exabytes of particle physics
> data coming from the Large Hadron Collider (LHC) and other particle
> physics experiments.
>
>
> Plans
> ===
>
> The project foresees three main directions -- move parts of cling
> upstream along with the clang and llvm features that enable them; extend
> and generalize the language interoperability layer around cling; and
> extend and generalize the OpenCL/CUDA support in cling. We are at the
> early stages of the project and this email intends to be an RFC for the
> first part -- upstreaming parts of cling. Please do share your thoughts
> on the rest, too.
>
>
> Moving Parts of Cling Upstream
> ---
>
> Over the years we have slowly moved some patches upstream. However we
> still have around 100 patches in the clang fork. Most of them are in the
> context of extending the incremental compilation support for clang. The
> incremental compilation poses some challenges in the clang
> infrastructure. For example, we need to tune CodeGen to work with
> multiple llvm::Module instances, and finalize per each
> end-of-translation unit (we have multiple of them). Other changes
> include small adjustments in the FileManager's caching mechanism, and
> bug fixes in the SourceManager (code which can be reached mostly from
> within our setup). One conclusion we can draw from our research is that
> the clang infrastructure fits amazingly well to something which was not
> its main use case. The grand total of our diffs against clang-9 is: `62
> files changed, 1294 insertions(+), 231 deletions(-)`. Cling is currently
> being upgraded from llvm-5 to llvm-9.
>
> A major weakness of cling's infrastructure is that it does not work with
> the clang Action infrastructure due to the lack of an
> IncrementalAction.  A possible way forward would be to implement a
> clang::IncrementalAction as a starting point. This way we should be able
> to reduce the amount of setup necessary to use the incremental
> infrastructure in clang. However, this will be a bit of a testing
> challenge -- cling lives downstream and some of the new code may be
> impossible to pick straight away and use. Building a mainline example
> tool such as clang-repl which gives us a way to test that incremental
> case or repurpose the already existing clang-interpreter may  be able to
> address the issue. The major risk of the task is avoiding code in the
> clang mainline which is untested by its HEP production environment.
> There are several other types of patches to the ROOT fork of Clang,
> including ones  in the context of performance,towards  C++ modules
> support (D41416), and storage (does not have a patch yet but has an open
> projects entry and somebody working on it). These patches can be
> considered in parallel independently on the rest.
>
> Extend and Generalize the Language Interoperability Layer Around Cling
> ---
>
> HEP has extensive experience with on-demand python interoperability
> using cppyy[6], which is built around the type information provided by
> cling. Unlike tools with custom parsers such as swig and sip and tools
> built on top of C-APIs such as boost.python and pybind11, cling can
> provide information about memory management patterns (eg refcounting)
> and instantiate templates on the fly.We feel that functionality may not
> be of general interest to the llvm community but we will prepare another
> RFC and send it here later on to gather feedback.
>
>
> Extend and Generalize the OpenCL/CUDA Support in Cling
> ---
>
> Cling can incrementally compile CUDA code [7-8] allowing easier set up
> and enabling some interesting use cases. There are a number of planned
> improvements including talking to HIP [9] and SYCL to support more
> hardware architectures.
>
>
>
> The primary focus of our work is to upstreaming functionality required
> to build an incremental compiler and rework cling build against vanilla
> clang and llvm. The last two points are to give the scope of the work
> which we will be doing the next 2-3 years. We will send here RFCs for
> both of them to trigger technical discussion if there is interest in
> pursuing this direction.
>
>
> Collaboration
> ===
>
> Open source development nowadays relies on reviewers. LLVM is no
> different and we will probably disturb a good number of people in the
> community ;)We would like to invite anybody interested in joining our
> incremental C++ activities to our open every second week calls.
> Announcements will be done via google group: compiler-research-announce
> (https://groups.google.com/g/compiler-research-announce).
>
>
>
> Many thanks!
>
>
> David & Vassil
>
> References
> ===
> [1] ROOT GitHub https://github.com/root-project/root
> [2] ROOT https://root.cern
> [3] Cling https://github.com/root-project/cling
> [4] Xeus-Cling
> https://blog.jupyter.org/xeus-is-now-a-jupyter-subproject-c4ec5a1bf30b
> [5] Cling – The New Interactive Interpreter for ROOT 6,
> https://iopscience.iop.org/article/10.1088/1742-6596/396/5/052071
> [6] High-performance Python-C++ bindings with PyPy and Cling,
> https://dl.acm.org/doi/10.5555/3019083.3019087
> [7]
>
> https://indico.cern.ch/event/697389/contributions/3085538/attachments/1712698/2761717/2018_09_10_cling_CUDA.pdf
> [8] CUDA C++ in Jupyter: Adding CUDA Runtime Support to Cling',
> https://zenodo.org/record/3713753#.Xu8jqvJRXxU
> [9] HIP Programming Guide
> https://rocmdocs.amd.com/en/latest/Programming_Guides/HIP-GUIDE.html
>
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