[LLVMdev] [NVPTX] We need an LLVM CUDA math library, after all

Sat Feb 16 17:46:17 PST 2013

Dear Yuan,

Sorry for delay with reply,

Answers on your questions could be different, depending on the math library
placement in the code generation pipeline. At KernelGen, we currently have
a user-level CUDA math module, adopted from cicc internals [1]. It is
intended to be linked with the user LLVM IR module, right before proceeding
with the final optimization and backend. Last few months we are using this
method to temporary workaround the absence of many math functions, to keep
up the speed of applications testing in our compiler test suite. Supplying
math in such way is not portable and introduces many issues, for instance:
1) The frontend (DragonEgg - in our case) must be taught to emit real math
functions calls instead those of LLVM intrinsics, NVPTX cannot handle
2) However, not all intrinsics should be replaced by math calls directly,
for example, there is not cdexp call, but it could be modelled with sincos.
3) Our math module assumes sm_20, and could be inefficient or non-portable
on other families of GPUs.

Instead of this approach, I think math library should be implemented *as a
lowering pass in backend*, working directly with intrinsics. In this case -
naming is not important, as well as final optimization is the job of
backend. But there is another important thing: backend should codegen math
with respect to accuracy settings, specified either as backend options, or
as functions attributes (quiet recent addition of LLVM). Accuracy settings
should be:
1) fast-math (ftz, prec-div, prec-sqrt, fma, etc.)
2) Use or not GPU-specific low-precision functions (__sin, __cos, etc.)

Following latter approach, math handling of NVPTX will conform the rest of
LLVM, and no host-dependant tweaks will be needed.

I'm also interested to contribute into this developments at reasonable
depth. Moving this part only on our own would slow down the progess with
main targets too much, that's why I'm asking for your help and cooperation.

Best regards,
- Dima.

[1]
https://hpcforge.org/scm/viewvc.php/*checkout*/trunk/src/cuda/include/math.bc?root=kernelgen

2013/2/8 Yuan Lin <yulin at nvidia.com>

> Yes, it helps a lot and we are working on it.****
>
> ** **
>
> A few questions,****
>
> **1)      **What will be your use model of this library? Will you run
> optimization phases after linking with the library? If so, what are they?*
> ***
>
> **2)      **Do you care if the names of functions differ from those in
> libm? For example, it would be gpusin() instead of sin(). ****
>
> **3)      **Do you need a different library for different host platforms?
> Why?****
>
> **4)      **Any other functions (besides math) you want to see in this
> library?****
>
> ** **
>
> Thanks.****
>
> ** **
>
> Yuan****
>
> ** **
>
> ** **
>
> *From:* Dmitry Mikushin [mailto:dmitry at kernelgen.org]
> *Sent:* Thursday, February 07, 2013 2:09 PM
> *To:* Justin Holewinski; LLVM Developers Mailing List
> *Cc:* Yuan Lin
> *Subject:* [NVPTX] We need an LLVM CUDA math library, after all****
>
> ** **
>
> Hi Justin, gentlemen,
>
> I'm afraid I have to escalate this issue at this point. Since it was
> discussed for the first time last summer, it was sufficient for us for a
> while to have lowering of math calls into intrinsics disabled at DragonEgg
> level, and link them against CUDA math functions at LLVM IR level. Now I
> can say: this is not sufficient any longer, and we need NVPTX backend to
> deal with GPU math.
>
> > There also is no standard libm for PTX.
>
> Yes, that's right, but there is an interesting idea to codegen CUDA math
> headers into LLVM IR and link it with user module at IR level. This method
> gives a perfect degree of flexibility with respect to high-level languages:
> the user no longer needs to deal with headers and can have math right in
> the IR, regardless the language it was lowered from. I can confirm this
> method works for us very well with C and Fortran, but in order to make
> accurate replacements of unsupported intrinsics calls, it needs to become
> aware of NVPTX backend capabilities in the form of:
>
> bool NVPTXTargetMachine::****
>
> isIntrinsicSupported(Function& intrinsic) and
> string NVPTXTargetMachine::whichMathCallReplacesIntrinsic(Function&
> intrinsic)
>
> > I would prefer not to lower such things in the back-end since different
> compilers may want to implement such functions differently based on speed
> vs. accuracy trade-offs.
>
> Who are those different compilers? We are LLVM, the complete compiler
> stack, which should handle these things on its specific preference. Derived
> compilers may certainly think different, and it's their own business to
> change anything they want and never contribute back. We should not forget
> there are a lot of derived projects that use LLVM directly, like KernelGen
> or many of those embedded DSLs recently started flourishing. Their
> completeness and future relies on LLVM. For these reasons, I would strongly
> prefer LLVM/NVPTX should supply a reference GPU math implementation and
> invite you and everyone else to form a joint roadmap to deliver it.
>
> Before we started, IANAL, but something tells me there could be a
> licensing issue about releasing the LLVM IR emitted from CUDA headers.
> Could you please check this with NVIDIA?
>
> Many thanks,
> - D.
>
> 2012/9/6 Justin Holewinski <justin.holewinski at gmail.com>:
> > On 09/06/2012 10:02 AM, Dmitry N. Mikushin wrote:
> >>
> >> Dear all,
> >>
> >> During app compilation we have a crash in NVPTX backend:
> >>
> >> LLVM ERROR: Cannot select: 0x732b270: i64 = ExternalSymbol'__powisf2'
> >> [ID=18]
> >>
> >> As I understand LLVM tries to lower the following call
> >>
> >> %28 = call ptx_device float @llvm.powi.f32(float 2.000000e+00, i32 %8)
> >> nounwind readonly
> >>
> >> to device intrinsic. The table llvm/IntrinsicsNVVM.td does not contain
> >> such intrinsic, however it should be builtin, according to
> >> cuda/include/math_functions.h
> >
> >
> > It actually gets lowered into an external function call.
> >
> >
> >>
> >> Is my understanding correct, and we need simply add the corresponding
> >> definition to llvm/IntrinsicsNVVM.td ? How to do that, what are the
> >> rules?
> >
> >
> > PTX does not have an instruction (or simple series of instructions) that
> > implements pow, so this will not be handled.  I would prefer not to lower
> > such things in the back-end since different compilers may want to
> implement
> > such functions differently based on speed vs. accuracy trade-offs.
> >
> > There also is no standard libm for PTX.  It is up to the higher-level
> > compiler to link against a run-time library that provides functions like
> pow
> > (see include/math_functions.h in a CUDA distribution).
> >
> >>
> >> Thanks,
> >> - D.
> >> _______________________________________________
> >> LLVM Developers mailing list
> >> LLVMdev at cs.uiuc.edu         http://llvm.cs.uiuc.edu
> >> http://lists.cs.uiuc.edu/mailman/listinfo/llvmdev
> >****
>
> ****
>
> >
> > --
> > Thanks,
> >
> > Justin Holewinski
> >****
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