[petsc-dev] ?????? Petsc: Error code 1

[Chen Gang]

Dear Professor??


Attachment is the alltests.log file.


Best,
Gang




----
??: 
   "petsc-dev"  
  


alltests.log
Description: Binary data

Re: [petsc-dev] -with-kokkos-cuda-arch=AMPERE80 nonsense

[Jeff Hammond]

>
>
> Generically, independent of Kokkos,  ideally I would run a single
> precompiled NVIDIA program that gave me all the information about the
> current hardware I was running and that would provide in simple format
> exactly the information I needed to configure PETSc, Kokkos etc for THAT
> system.
>

I will try to write something for you tomorrow.  For NVIDIA hardware, the
sole dependency will be nvcc.

Jeff

-- 
Jeff Hammond
jeff.scie...@gmail.com
http://jeffhammond.github.io/

Re: [petsc-dev] Petsc: Error code 1

[Satish Balay via petsc-dev]

Note: do not use '-j' with alltests.

And run alltests on both machines [but *not* at the same time on machines] and 
send us logs from both the runs.

Satish


On Mon, 5 Apr 2021, Satish Balay wrote:

> Try:
> 
> make alltests TIMEOUT=600
> 
> And send us the complete log (alltests.log)
> 
> Satish
> 
> On Tue, 6 Apr 2021, Chen Gang wrote:
> 
> > Dear sir,
> > 
> > 
> > The result of make check is OK. And I do set the timeout to a larger value, 
> > which keeps me from getting timeout error. The thing is I have two 
> > machines. And I get the error code 1 in different tests on different 
> > machines.I don’t know what is error code1. What case this? How can I fix 
> > the failure tests.
> > 
> > 
> > -- Original --
> > From: Satish Balay  > Date: Tue,Apr 6,2021 0:18 PM
> > To: Chen Gang <569615...@qq.com
> > Cc: petsc-dev  > Subject: Re: [petsc-dev] Petsc: Error code 1
> 

Re: [petsc-dev] Petsc: Error code 1

[Satish Balay via petsc-dev]

Try:

make alltests TIMEOUT=600

And send us the complete log (alltests.log)

Satish

On Tue, 6 Apr 2021, Chen Gang wrote:

> Dear sir,
> 
> 
> The result of make check is OK. And I do set the timeout to a larger value, 
> which keeps me from getting timeout error. The thing is I have two machines. 
> And I get the error code 1 in different tests on different machines.I don’t 
> know what is error code1. What case this? How can I fix the failure tests.
> 
> 
> -- Original --
> From: Satish Balay  Date: Tue,Apr 6,2021 0:18 PM
> To: Chen Gang <569615...@qq.com
> Cc: petsc-dev  Subject: Re: [petsc-dev] Petsc: Error code 1

Re: [petsc-dev] Petsc: Error code 1

[Chen Gang]

Dear sir,


The result of make check is OK. And I do set the timeout to a larger value, 
which keeps me from getting timeout error. The thing is I have two machines. 
And I get the error code 1 in different tests on different machines.I don’t 
know what is error code1. What case this? How can I fix the failure tests.


-- Original --
From: Satish Balay 

Re: [petsc-dev] Petsc: Error code 1

[Satish Balay via petsc-dev]

To check the install - we suggest:

make check

'make test' runs the full test suite.

Note the test suite is parallel - so if using '-j' the multiple
parallel jobs can overload the machine and slow things down.  So best
to use a much smaller -j value, and with a larger timeout.

make -j4 test TIMEOUT=600

Satish

On Tue, 6 Apr 2021, Chen Gang wrote:

> Dear Professor,
> 
> 
> 
> 
> 
> 
> I was running the petsc test using
> 
> 
> # make all test -j
> 
> 
> AND I got the error code 1 message of six examples.
> 
> 
> What is error code 1 and how can location the error.
> 
> 
> I went the exactly file and make, it seems the examples can be running well. 
> I don't understand what is error code 1.
> 
> 
> The below is the summary.
> 
> 
> Looking forward to hearing you!
> 
> 
> -
>  
> # Summary
>  
> # -
>  
> # FAILED diff-tao_complementarity_tutorials-blackscholes_2 
> diff-tao_bound_tutorials-plate2f_2 
> diff-tao_complementarity_tutorials-blackscholes_6 
> diff-tao_bound_tutorials-plate2f_1 diff-vec_is_is_tutorials-ex2f_1 
> diff-tao_complementarity_tutorials-blackscholes_7
>  
> # success 7544/9528 tests (79.2%)
>  
> # failed 6/9528 tests (0.1%)
>  
> # todo 225/9528 tests (2.4%)
>  
> # skip 1753/9528 tests (18.4%)
>  
> #
>  
> # Wall clock time for tests: 1552 sec
>  
> # Approximate CPU time (not incl. build time): 106566.873 sec
>  
> #
>  
> # To rerun failed tests:
>  
> # /opt/rh/devtoolset-9/root/usr/bin/gmake -f 
> gmakefile test test-fail=1
>  
> #
>  
> # Timing summary (actual test time / total CPU time):
>  
> # mat_tests-ex44_mpiio_15: 220.10 sec / 221.33 sec
>  
> # mat_tests-ex44_stdio_15: 220.07 sec / 221.15 sec
>  
> # dm_impls_stag_tests-ex1_basic_2: 209.29 sec / 211.16 sec
>  
> # dm_tutorials-ex15_3: 177.42 sec / 178.46 sec
>  
> # dm_impls_stag_tutorials-ex6_4: 177.10 sec / 178.31 sec
> 
> Best,
> 
> 
> Gang Chen
> 
> 
> Sichuan Univertsity,
> School of Mathematics,
> Chengdu, China

Re: [petsc-dev] -with-kokkos-cuda-arch=AMPERE80 nonsense

[Barry Smith]

  Junchao,

I hope my latest MRs  manages that for the current generation of those 
values. If not, we need refinement.

  Barry


> On Apr 5, 2021, at 9:30 PM, Junchao Zhang  wrote:
> 
> 
> 
> 
> On Mon, Apr 5, 2021 at 7:33 PM Jeff Hammond  > wrote:
> NVCC has supported multi-versioned "fat" binaries since I worked for Argonne. 
>  Libraries should figure out what the oldest hardware they are about is and 
> then compile for everything from that point forward.  Kepler (3.5) is oldest 
> version any reasonable person should be thinking about at this point.  The 
> oldest thing I know of in the DOE HPC fleet is Pascal (6.x).  Volta and 
> Turing are 7.x and Ampere is 8.x.
> 
> The biggest architectural changes came with unified memory 
> (https://developer.nvidia.com/blog/unified-memory-in-cuda-6/ 
> ) and 
> cooperative (https://developer.nvidia.com/blog/cooperative-groups/ 
>  in CUDA 9) but Kokkos 
> doesn't use the latter.  Both features can be used on quite old GPU 
> architectures, although the performance is better on newer ones.
> 
> I haven't dug into what Kokkos and PETSc are doing but the direct use of this 
> stuff in CUDA is well-documented, certainly as well as the CPU switches for 
> x86 binaries in the Intel compiler are.
> 
> https://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html#compute-capabilities
>  
> 
> 
> Devices with the same major revision number are of the same core 
> architecture. The major revision number is 8 for devices based on the NVIDIA 
> Ampere GPU architecture, 7 for devices based on the Volta architecture, 6 for 
> devices based on the Pascal architecture, 5 for devices based on the Maxwell 
> architecture, 3 for devices based on the Kepler architecture, 2 for devices 
> based on the Fermi architecture, and 1 for devices based on the Tesla 
> architecture.
> Kokkos has config options Kokkos_ARCH_TURING75, Kokkos_ARCH_VOLTA70, 
> Kokkos_ARCH_VOLTA72.Any idea how one can map compute capability versions 
> to arch names?
>  
> 
> 
> https://docs.nvidia.com/cuda/pascal-compatibility-guide/index.html#building-pascal-compatible-apps-using-cuda-8-0
>  
> 
> https://docs.nvidia.com/cuda/volta-compatibility-guide/index.html#building-volta-compatible-apps-using-cuda-9-0
>  
> 
> https://docs.nvidia.com/cuda/turing-compatibility-guide/index.html#building-turing-compatible-apps-using-cuda-10-0
>  
> 
> https://docs.nvidia.com/cuda/ampere-compatibility-guide/index.html#building-ampere-compatible-apps-using-cuda-11-0
>  
> 
> 
> Programmatic querying can be done with the following 
> (https://docs.nvidia.com/cuda/cuda-runtime-api/group__CUDART__DEVICE.html 
> ):
> 
> cudaDeviceGetAttribute
> cudaDevAttrComputeCapabilityMajor 
> :
>  Major compute capability version number;
> cudaDevAttrComputeCapabilityMinor 
> :
>  Minor compute capability version number;
> The compiler help tells me this, which can be cross-referenced with CUDA 
> documentation above.
> 
> $ /usr/local/cuda-10.0/bin/nvcc -h
> 
> Usage  : nvcc [options] 
> 
> ...
> 
> Options for steering GPU code generation.
> =
> 
> --gpu-architecture   (-arch) 
> Specify the name of the class of NVIDIA 'virtual' GPU architecture 
> for which
> the CUDA input files must be compiled.
> With the exception as described for the shorthand below, the 
> architecture
> specified with this option must be a 'virtual' architecture (such as 
> compute_50).
> Normally, this option alone does not trigger assembly of the 
> generated PTX
> for a 'real' architecture (that is the role of nvcc option 
> '--gpu-code',
> see below); rather, its purpose is to control preprocessing and 
> compilation
> of the input to PTX.
> For convenience, in case of simple nvcc compilations, the following 
> shorthand
>  

Re: [petsc-dev] -with-kokkos-cuda-arch=AMPERE80 nonsense

[Barry Smith]

  Thanks Jeff,

 The information is eventually there somewhere, the issue is more getting 
the information in a simple way, automatically, at PETSc configure time that is 
portable and will never crash. 
https://docs.nvidia.com/cuda/cuda-runtime-api/group__CUDART__DEVICE.html 
 
seems to require compiling a program and running it to get the information, 
this means invoking nvcc (what sub compiler to use for nvcc  with what flags 
etc? Not so easy on systems like Summit where their are multiple choices for 
the sub-compiler). So how complicated and fragile do we want to make PETSc 
configure be (for each particular piece of hardware) to always get the best 
information about the current hardware? 

   It looks like Kokkos really only needs the NVIDIA numerical generation 
information, not the code name, but their API requires both the codename 
(irrelevant) and the numerical information (relevant) in what is passed to 
Kokkos. The problem has always been generating the irrelevant part so Kokkos 
does not complain. We can, with a little pain, possibly automate completely the 
CUDA device information, the numerical part, but the mapping to code name has 
been problematic because it is hard to find in a single place the mapping from 
numerical information to codename. But I think, thanks to Max's input, I now 
understand the mapping and have put it in PETSc's configure.

Generically, independent of Kokkos,  ideally I would run a single 
precompiled NVIDIA program that gave me all the information about the current 
hardware I was running and that would provide in simple format exactly the 
information I needed to configure PETSc, Kokkos etc for THAT system. The idea 
of support a multitude of hardware is important for package management systems, 
but is not important for 99% of PETSc users who are configuring for exactly the 
hardware they have on the system they are configuring on, then all they care 
about it is "give me the best reasonable performance on the machine I am using 
today". This means the system software should be able to provide in a trivial 
way what the current hardware is. The problem is not unique to GPUs, of course, 
it is not always easy in a portable way to get this information for generic 
CPUs either.


  Barry






> On Apr 5, 2021, at 7:32 PM, Jeff Hammond  wrote:
> 
> NVCC has supported multi-versioned "fat" binaries since I worked for Argonne. 
>  Libraries should figure out what the oldest hardware they are about is and 
> then compile for everything from that point forward.  Kepler (3.5) is oldest 
> version any reasonable person should be thinking about at this point.  The 
> oldest thing I know of in the DOE HPC fleet is Pascal (6.x).  Volta and 
> Turing are 7.x and Ampere is 8.x.
> 
> The biggest architectural changes came with unified memory 
> (https://developer.nvidia.com/blog/unified-memory-in-cuda-6/ 
> ) and 
> cooperative (https://developer.nvidia.com/blog/cooperative-groups/ 
>  in CUDA 9) but Kokkos 
> doesn't use the latter.  Both features can be used on quite old GPU 
> architectures, although the performance is better on newer ones.
> 
> I haven't dug into what Kokkos and PETSc are doing but the direct use of this 
> stuff in CUDA is well-documented, certainly as well as the CPU switches for 
> x86 binaries in the Intel compiler are.
> 
> https://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html#compute-capabilities
>  
> 
> 
> Devices with the same major revision number are of the same core 
> architecture. The major revision number is 8 for devices based on the NVIDIA 
> Ampere GPU architecture, 7 for devices based on the Volta architecture, 6 for 
> devices based on the Pascal architecture, 5 for devices based on the Maxwell 
> architecture, 3 for devices based on the Kepler architecture, 2 for devices 
> based on the Fermi architecture, and 1 for devices based on the Tesla 
> architecture.
> 
> https://docs.nvidia.com/cuda/pascal-compatibility-guide/index.html#building-pascal-compatible-apps-using-cuda-8-0
>  
> 
> https://docs.nvidia.com/cuda/volta-compatibility-guide/index.html#building-volta-compatible-apps-using-cuda-9-0
>  
> 
> https://docs.nvidia.com/cuda/turing-compatibility-guide/index.html#building-turing-compatible-apps-using-cuda-10-0
>  
> 
> 

Re: [petsc-dev] -with-kokkos-cuda-arch=AMPERE80 nonsense

[Junchao Zhang]

On Mon, Apr 5, 2021 at 7:33 PM Jeff Hammond  wrote:

> NVCC has supported multi-versioned "fat" binaries since I worked for
> Argonne.  Libraries should figure out what the oldest hardware they are
> about is and then compile for everything from that point forward.  Kepler
> (3.5) is oldest version any reasonable person should be thinking about at
> this point.  The oldest thing I know of in the DOE HPC fleet is Pascal
> (6.x).  Volta and Turing are 7.x and Ampere is 8.x.
>
> The biggest architectural changes came with unified memory (
> https://developer.nvidia.com/blog/unified-memory-in-cuda-6/) and
> cooperative (https://developer.nvidia.com/blog/cooperative-groups/ in
> CUDA 9) but Kokkos doesn't use the latter.  Both features can be used on
> quite old GPU architectures, although the performance is better on newer
> ones.
>
> I haven't dug into what Kokkos and PETSc are doing but the direct use of
> this stuff in CUDA is well-documented, certainly as well as the CPU
> switches for x86 binaries in the Intel compiler are.
>
>
> https://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html#compute-capabilities
>
> Devices with the same major revision number are of the same core
> architecture. The major revision number is 8 for devices based on the NVIDIA
> Ampere GPU architecture, 7 for devices based on the Volta architecture, 6
> for devices based on the Pascal architecture, 5 for devices based on the
> Maxwell architecture, 3 for devices based on the Kepler architecture, 2
> for devices based on the Fermi architecture, and 1 for devices based on
> the Tesla architecture.
>
Kokkos has config options Kokkos_ARCH_TURING75,
Kokkos_ARCH_VOLTA70, Kokkos_ARCH_VOLTA72.Any idea how one can map
compute capability versions to arch names?


>
>
>
> https://docs.nvidia.com/cuda/pascal-compatibility-guide/index.html#building-pascal-compatible-apps-using-cuda-8-0
>
> https://docs.nvidia.com/cuda/volta-compatibility-guide/index.html#building-volta-compatible-apps-using-cuda-9-0
>
> https://docs.nvidia.com/cuda/turing-compatibility-guide/index.html#building-turing-compatible-apps-using-cuda-10-0
>
> https://docs.nvidia.com/cuda/ampere-compatibility-guide/index.html#building-ampere-compatible-apps-using-cuda-11-0
>
> Programmatic querying can be done with the following (
> https://docs.nvidia.com/cuda/cuda-runtime-api/group__CUDART__DEVICE.html):
>
> cudaDeviceGetAttribute
>
>-
>
>cudaDevAttrComputeCapabilityMajor
>
> :
>Major compute capability version number;
>-
>
>cudaDevAttrComputeCapabilityMinor
>
> :
>Minor compute capability version number;
>
> The compiler help tells me this, which can be cross-referenced with CUDA
> documentation above.
>
> $ /usr/local/cuda-10.0/bin/nvcc -h
>
>
> Usage  : nvcc [options] 
>
>
> ...
>
>
> Options for steering GPU code generation.
>
> =
>
>
> --gpu-architecture   (-arch)
>
>
> Specify the name of the class of NVIDIA 'virtual' GPU
> architecture for which
>
> the CUDA input files must be compiled.
>
> With the exception as described for the shorthand below, the
> architecture
>
> specified with this option must be a 'virtual' architecture (such
> as compute_50).
>
> Normally, this option alone does not trigger assembly of the
> generated PTX
>
> for a 'real' architecture (that is the role of nvcc option
> '--gpu-code',
>
> see below); rather, its purpose is to control preprocessing and
> compilation
>
> of the input to PTX.
>
> For convenience, in case of simple nvcc compilations, the
> following shorthand
>
> is supported.  If no value for option '--gpu-code' is specified,
> then the
>
> value of this option defaults to the value of
> '--gpu-architecture'.  In this
>
> situation, as only exception to the description above, the value
> specified
>
> for '--gpu-architecture' may be a 'real' architecture (such as a
> sm_50),
>
> in which case nvcc uses the specified 'real' architecture and its
> closest
>
> 'virtual' architecture as effective architecture values.  For
> example, 'nvcc
>
> --gpu-architecture=sm_50' is equivalent to 'nvcc
> --gpu-architecture=compute_50
>
> --gpu-code=sm_50,compute_50'.
>
> Allowed values for this option:
> 'compute_30','compute_32','compute_35',
>
>
> 'compute_37','compute_50','compute_52','compute_53','compute_60','compute_61',
>
>
> 'compute_62','compute_70','compute_72','compute_75','sm_30','sm_32','sm_35',
>
>
> 'sm_37','sm_50','sm_52','sm_53','sm_60','sm_61','sm_62','sm_70','sm_72',
>
>  

Re: [petsc-dev] -with-kokkos-cuda-arch=AMPERE80 nonsense

[Jeff Hammond]

NVCC has supported multi-versioned "fat" binaries since I worked for
Argonne.  Libraries should figure out what the oldest hardware they are
about is and then compile for everything from that point forward.  Kepler
(3.5) is oldest version any reasonable person should be thinking about at
this point.  The oldest thing I know of in the DOE HPC fleet is Pascal
(6.x).  Volta and Turing are 7.x and Ampere is 8.x.

The biggest architectural changes came with unified memory (
https://developer.nvidia.com/blog/unified-memory-in-cuda-6/) and
cooperative (https://developer.nvidia.com/blog/cooperative-groups/ in CUDA
9) but Kokkos doesn't use the latter.  Both features can be used on quite
old GPU architectures, although the performance is better on newer ones.

I haven't dug into what Kokkos and PETSc are doing but the direct use of
this stuff in CUDA is well-documented, certainly as well as the CPU
switches for x86 binaries in the Intel compiler are.

https://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html#compute-capabilities

Devices with the same major revision number are of the same core
architecture. The major revision number is 8 for devices based on the NVIDIA
Ampere GPU architecture, 7 for devices based on the Volta architecture, 6
for devices based on the Pascal architecture, 5 for devices based on the
Maxwell architecture, 3 for devices based on the Kepler architecture, 2 for
devices based on the Fermi architecture, and 1 for devices based on the
Tesla architecture.

https://docs.nvidia.com/cuda/pascal-compatibility-guide/index.html#building-pascal-compatible-apps-using-cuda-8-0
https://docs.nvidia.com/cuda/volta-compatibility-guide/index.html#building-volta-compatible-apps-using-cuda-9-0
https://docs.nvidia.com/cuda/turing-compatibility-guide/index.html#building-turing-compatible-apps-using-cuda-10-0
https://docs.nvidia.com/cuda/ampere-compatibility-guide/index.html#building-ampere-compatible-apps-using-cuda-11-0

Programmatic querying can be done with the following (
https://docs.nvidia.com/cuda/cuda-runtime-api/group__CUDART__DEVICE.html):

cudaDeviceGetAttribute

   -

   cudaDevAttrComputeCapabilityMajor
   
:
   Major compute capability version number;
   -

   cudaDevAttrComputeCapabilityMinor
   
:
   Minor compute capability version number;

The compiler help tells me this, which can be cross-referenced with CUDA
documentation above.

$ /usr/local/cuda-10.0/bin/nvcc -h


Usage  : nvcc [options] 


...


Options for steering GPU code generation.

=


--gpu-architecture   (-arch)

Specify the name of the class of NVIDIA 'virtual' GPU architecture
for which

the CUDA input files must be compiled.

With the exception as described for the shorthand below, the
architecture

specified with this option must be a 'virtual' architecture (such
as compute_50).

Normally, this option alone does not trigger assembly of the
generated PTX

for a 'real' architecture (that is the role of nvcc option
'--gpu-code',

see below); rather, its purpose is to control preprocessing and
compilation

of the input to PTX.

For convenience, in case of simple nvcc compilations, the following
shorthand

is supported.  If no value for option '--gpu-code' is specified,
then the

value of this option defaults to the value of '--gpu-architecture'.
In this

situation, as only exception to the description above, the value
specified

for '--gpu-architecture' may be a 'real' architecture (such as a
sm_50),

in which case nvcc uses the specified 'real' architecture and its
closest

'virtual' architecture as effective architecture values.  For
example, 'nvcc

--gpu-architecture=sm_50' is equivalent to 'nvcc
--gpu-architecture=compute_50

--gpu-code=sm_50,compute_50'.

Allowed values for this option:
'compute_30','compute_32','compute_35',


'compute_37','compute_50','compute_52','compute_53','compute_60','compute_61',


'compute_62','compute_70','compute_72','compute_75','sm_30','sm_32','sm_35',


'sm_37','sm_50','sm_52','sm_53','sm_60','sm_61','sm_62','sm_70','sm_72',

'sm_75'.


--gpu-code ,...  (-code)

Specify the name of the NVIDIA GPU to assemble and optimize PTX for.

nvcc embeds a compiled code image in the resulting executable for
each specified

 architecture, which is a true binary load image for each
'real' architecture

(such as sm_50), and PTX code for the 'virtual' architecture (such
as compute_50).

During runtime, such embedded PTX 

Re: [petsc-dev] -with-kokkos-cuda-arch=AMPERE80 nonsense

[Satish Balay via petsc-dev]

This is nvidia mess-up. Why isn't there a command that give me these values [if 
they insist on this interface for nvcc]

I see Barry want configure to do something here - but whatever we do - we would 
be shifting the problem around.
[even if we detect stuff - build box might not have the GPU used for runs.]

We have --with-cuda-arch - which I tried to remove from configure - but its 
come back in a different form (--with-cuda-gencodearch)

And I see other packages:

  --with-kokkos-cuda-arch

Wrt spack - I'm having to do:

spack install xsdk+cuda ^magma cuda_arch=60

[magma uses CudaPackage() infrastructure in spack]

Satish

On Mon, 5 Apr 2021, Mills, Richard Tran via petsc-dev wrote:

> You raise a good point, Barry. I've been completely mystified by what some of 
> these names even mean. What does "PASCAL60" vs. "PASCAL61" even mean? Do you 
> know of where this is even documented? I can't really find anything about it 
> in the Kokkos documentation. The only thing I can really find is an issue or 
> two about "hey, shouldn't our CMake stuff figure this out automatically" and 
> then some posts about why it can't really do that. Not encouraging.
> 
> --Richard
> 
> On 4/3/21 8:42 PM, Barry Smith wrote:
> 
> 
>   It would be very nice to NOT require PETSc users to provide this flag, how 
> the heck will they know what it should be when we cannot automate it 
> ourselves?
> 
>   Any ideas of how this can be determined based on the current system? NVIDIA 
> does not help since these "advertising" names don't seem to trivially map to 
> information you can get from a particular GPU when you logged into it. For 
> example nvidia-smi doesn't use these names directly. Is there some mapping 
> from nvidia-smi  to these names we could use? If we are serious about having 
> a non-trivial number of users utilizing GPUs, which we need to be for future, 
> we cannot have this absurd demands in our installation process.
> 
>   Barry
> 
> Does spack have some magic for this we could use?
> 
> 
> 
> 

Re: [petsc-dev] -with-kokkos-cuda-arch=AMPERE80 nonsense

[Mills, Richard Tran via petsc-dev]

Hmm, OK, I found a table at

  https://sparta.sandia.gov/doc/accelerate_kokkos.html

and it tells me that "PASCAL60" refers to "NVIDIA Pascal generation CC 6.0 GPU" 
and "PASCAL61" refers to "NVIDIA Pascal generation CC 6.1 GPU". But I have no 
idea what those 6.0 vs 6.1 version numbers mean, and I can't seem to easily 
find any information from NVIDIA that connects anything in the output of 
"nvidia-smi -a" to these versions.

I think maybe what I want is an NVIDIA equivalent to Intel's ark.intel.com, 
which decodes the mysterious Intel version numbers to tell me what 
architectural features are present. But does anything like this exist for 
NVIDIA?

--Richard



On 4/5/21 1:10 PM, Mills, Richard Tran wrote:
You raise a good point, Barry. I've been completely mystified by what some of 
these names even mean. What does "PASCAL60" vs. "PASCAL61" even mean? Do you 
know of where this is even documented? I can't really find anything about it in 
the Kokkos documentation. The only thing I can really find is an issue or two 
about "hey, shouldn't our CMake stuff figure this out automatically" and then 
some posts about why it can't really do that. Not encouraging.

--Richard

On 4/3/21 8:42 PM, Barry Smith wrote:

  It would be very nice to NOT require PETSc users to provide this flag, how 
the heck will they know what it should be when we cannot automate it ourselves?

  Any ideas of how this can be determined based on the current system? NVIDIA 
does not help since these "advertising" names don't seem to trivially map to 
information you can get from a particular GPU when you logged into it. For 
example nvidia-smi doesn't use these names directly. Is there some mapping from 
nvidia-smi  to these names we could use? If we are serious about having a 
non-trivial number of users utilizing GPUs, which we need to be for future, we 
cannot have this absurd demands in our installation process.

  Barry

Does spack have some magic for this we could use?

Re: [petsc-dev] -with-kokkos-cuda-arch=AMPERE80 nonsense

[Mills, Richard Tran via petsc-dev]

You raise a good point, Barry. I've been completely mystified by what some of 
these names even mean. What does "PASCAL60" vs. "PASCAL61" even mean? Do you 
know of where this is even documented? I can't really find anything about it in 
the Kokkos documentation. The only thing I can really find is an issue or two 
about "hey, shouldn't our CMake stuff figure this out automatically" and then 
some posts about why it can't really do that. Not encouraging.

--Richard

On 4/3/21 8:42 PM, Barry Smith wrote:


  It would be very nice to NOT require PETSc users to provide this flag, how 
the heck will they know what it should be when we cannot automate it ourselves?

  Any ideas of how this can be determined based on the current system? NVIDIA 
does not help since these "advertising" names don't seem to trivially map to 
information you can get from a particular GPU when you logged into it. For 
example nvidia-smi doesn't use these names directly. Is there some mapping from 
nvidia-smi  to these names we could use? If we are serious about having a 
non-trivial number of users utilizing GPUs, which we need to be for future, we 
cannot have this absurd demands in our installation process.

  Barry

Does spack have some magic for this we could use?

[petsc-dev] DMNetwork static sizing

[Matthew Knepley]

Dowe really need a configure time constant for

struct _p_DMNetworkComponentHeader {
  PetscInt index;/* index for user input global edge and vertex */
  PetscInt subnetid; /* Id for subnetwork */
  PetscInt ndata;/* number of components */
  PetscInt size[PETSC_DMNETWORK_MAXIMUM_COMPONENTS_PER_POINT];
  PetscInt key[PETSC_DMNETWORK_MAXIMUM_COMPONENTS_PER_POINT];
  PetscInt offset[PETSC_DMNETWORK_MAXIMUM_COMPONENTS_PER_POINT];
  PetscInt nvar[PETSC_DMNETWORK_MAXIMUM_COMPONENTS_PER_POINT]; /* Number of
variables */
  PetscInt offsetvarrel[PETSC_DMNETWORK_MAXIMUM_COMPONENTS_PER_POINT]; /*
offset from the first variable of the network point */
} PETSC_ATTRIBUTEALIGNED(PetscMax(sizeof(double),sizeof(PetscScalar)));

Can't we just allocate this struct when needed and carry the size along?

This design seem to go against the rest of what we do in PETSc?

  Thanks,

 Matt

-- 
What most experimenters take for granted before they begin their
experiments is infinitely more interesting than any results to which their
experiments lead.
-- Norbert Wiener

https://www.cse.buffalo.edu/~knepley/