[LLVMdev] [RFC] MCJIT usage models

Tue Dec 10 04:49:44 PST 2013

I have a personal interest in areas that are a mix of (1) and (6) usage, in
particular where certain funcitons are being specified by the command line
but other functionality is added from an existing set of IR functions. In
this context minimising "total response time" but where the execution time
is likely to be much larger than the compilation time. One of the important
things is being able to do LTO effectively inlining newly specified code
into existing "library IR" and optimizing.

In terms of creating/destroying an MCJIT per REPL interaction vs having
multiple modules with one MCJIT, I haven't really benchmarked this but I
suspect that multiple modules is the way to go since this makes re-running
a previous computation to compare it against a new one avoid all the
recompilation of the old one. But I need to find time to think this through.

On Mon, Dec 9, 2013 at 7:08 PM, Kaylor, Andrew <andrew.kaylor at intel.com>wrote:

>  Below is an outline of various usage models for MCJIT that I put
> together based on conversations at last month’s LLVM Developer Meeting.  If
> you’re using or thinking about using MCJIT and your use case doesn’t seem
> to fit in one of the categories below then either I didn’t talk to you or I
> didn’t understand what you’re doing.
>
>
>
> In any case, I’d like to see this get worked into a shape suitable for
> inclusion in the LLVM documentation.  I imagine it serving as a guide both
> to those who are new to using MCJIT and to those who are developing and
> maintaining MCJIT.  If you’re using MCJIT the latter (yes, the latter) case
> is particularly important to you right now as having your use case properly
> represented in this document is the best way to ensure that it is
> adequately considered when changes are made to MCJIT and when the decision
> is made as to when we are ready to deprecate the old JIT engine (probably
> in the 3.5 release, BTW).
>
>
>
> So here’s what I’m asking for: if you are currently using MCJIT or
> considering using MCJIT, can you please find the use case that best fits
> your program and comment on how well the outline describes it.  If you
> understand what I’m saying below but you see something that is missing,
> please let me know.  If you aren’t sure what I’m saying or you don’t know
> how MCJIT might address your particular issues, please let me know that
> too.  If you think my outline is too sketchy and you need me to elaborate
> before you can provide meaningful feedback, please let me know about that.
> If you think it’s the best piece of documentation you’ve read all year and
> you can’t wait to read it again, that’s good information too.
>
>
>
> Thanks in advance for any and all feedback.
>
>
>
> -Andy
>
>
>
>
> ------------------------------------------------------------------------------------------
>
>
>
> Models for MCJIT use
>
>
>
> 1. Interactive dynamic code generation
>
>     - user types code which is compiled as needed for execution
>
>     - example: Kaleidoscope
>
>     - compilation speed probably isn't critical
>
>     - use one MCJIT instance with many modules
>
>     - create new modules on compilation
>
>     - MCJIT handles linking between modules
>
>         - external references still need prototypes
>
>         - we can at least provide a module pass to automate it
>
>     - memory overhead may be an issue but MCJIT can fix that
>
>     - see model 2 for pre-defined library
>
>     - if processing a large script pre-optimize before passing modules to
> MCJIT
>
>
>
> 2. Code generation for external target execution
>
>     - client generates code to be injected into an external process
>
>     - example: LLDB expression evaluation
>
>     - target may be another local or remote
>
>     - target architecture may not match host architecture
>
>     - may use one or more instances of MCJIT (client preference)
>
>     - MCJIT handles address remapping on request
>
>     - custom memory manager handles code/data transfer
>
>     - speed/memory requirements may vary
>
>
>
> 3. Large pre-defined module compilation and execution
>
>     - code/IR is loaded from disk and prepared for execution
>
>     - example: Intel(R) OpenCL SDK
>
>     - compilation speed matters but isn't critical
>
>     - initial startup time is somewhat important
>
>     - execution speed is critical
>
>     - memory consumption isn't an issue
>
>     - tool integration may be important
>
>     - use one MCJIT instance with multiple (but usually) few modules
>
>     - use object caching for commonly used code
>
>     - for very large, sparsely used libraries pre-link modules
>
>     - object and archive support may be useful
>
>
>
> 4. Hot function replacement
>
>     - client uses MCJIT to optimize frequently executed code
>
>     - example: WebKit
>
>     - compilation time is not critical
>
>     - execution speed is critical
>
>     - steady state memory consumption is very important
>
>     - client handles pre-JIT interpretation/execution
>
>     - MCJIT instances may be created as needed
>
>     - custom memory manager transfers code memory ownership after
> compilation
>
>     - MCJIT instance is deleted when no longer needed
>
>     - client handles function replacement and lifetime management
>
>
>
> 5. On demand "one-time" execution
>
>     - client provides a library of code which is used by small, disposable
> functions
>
>     - example: database query?
>
>     - initial load time isn't important
>
>     - execution time is critical
>
>     - if library code is fixed, load as shared library
>
>     - if library code must be generated use a separate instance of MCJIT
> to hold the library
>
>         - this instance can support multiple modules
>
>         - use a custom memory manager to link with functions in this module
>
>         - object caching and archive support may be useful in this case
>
>     - if inlining/lto is more important than compile time keep library in
> an IR module and pre-link just before invoking MCJIT
>
>     - create one instance of MCJIT as needed and destroy after execution
>
> _______________________________________________
> LLVM Developers mailing list
> LLVMdev at cs.uiuc.edu         http://llvm.cs.uiuc.edu
> http://lists.cs.uiuc.edu/mailman/listinfo/llvmdev
>
>

-- 
cheers, dave tweed__________________________
high-performance computing and machine vision expert: david.tweed at gmail.com
"while having code so boring anyone can maintain it, use Python." --
attempted insult seen on slashdot
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://lists.llvm.org/pipermail/llvm-dev/attachments/20131210/1da26b58/attachment.html>