[petsc-users] [petsc-maint] Assistance Needed with PETSc KSPSolve Performance Issue
Matthew Knepley
knepley at gmail.com
Mon Jun 24 10:45:26 CDT 2024
On Mon, Jun 24, 2024 at 11:21 AM Yongzhong Li <yongzhong.li at mail.utoronto.ca>
wrote:
> Thank you Pierre for your information. Do we have a conclusion for my
> original question about the parallelization efficiency for different stages
> of KSP Solve? Do we need to do more testing to figure out the issues? Thank
> you, Yongzhong From:
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> Thank you Pierre for your information. Do we have a conclusion for my
> original question about the parallelization efficiency for different stages
> of KSP Solve? Do we need to do more testing to figure out the issues?
>
We have an extended discussion of this here:
https://urldefense.us/v3/__https://petsc.org/release/faq/*what-kind-of-parallel-computers-or-clusters-are-needed-to-use-petsc-or-why-do-i-get-little-speedup__;Iw!!G_uCfscf7eWS!aQJpmm5W6l6FUiumnIPmkouzwzNUfx-Dyq04i1O2KS_InQGk6qjI7wUir0Hx6QEUQE2AMiJDsez3x4zRO7V_$
The kinds of operations you are talking about (SpMV, VecDot, VecAXPY, etc)
are memory bandwidth limited. If there is no more bandwidth to be
marshalled on your board, then adding more processes does nothing at all.
This is why people were asking about how many "nodes" you are running on,
because that is the unit of memory bandwidth, not "cores" which make little
difference.
Thanks,
Matt
> Thank you,
>
> Yongzhong
>
>
>
> *From: *Pierre Jolivet <pierre at joliv.et>
> *Date: *Sunday, June 23, 2024 at 12:41 AM
> *To: *Yongzhong Li <yongzhong.li at mail.utoronto.ca>
> *Cc: *petsc-users at mcs.anl.gov <petsc-users at mcs.anl.gov>
> *Subject: *Re: [petsc-users] [petsc-maint] Assistance Needed with PETSc
> KSPSolve Performance Issue
>
>
>
>
>
> On 23 Jun 2024, at 4:07 AM, Yongzhong Li <yongzhong.li at mail.utoronto.ca>
> wrote:
>
>
>
> This Message Is From an External Sender
>
> This message came from outside your organization.
>
> Yeah, I ran my program again using -mat_view::ascii_info and set
> MKL_VERBOSE to be 1, then I noticed the outputs suggested that the matrix
> to be seqaijmkl type (I’ve attached a few as below)
>
> --> Setting up matrix-vector products...
>
>
>
> Mat Object: 1 MPI process
>
> type: seqaijmkl
>
> rows=16490, cols=35937
>
> total: nonzeros=128496, allocated nonzeros=128496
>
> total number of mallocs used during MatSetValues calls=0
>
> not using I-node routines
>
> Mat Object: 1 MPI process
>
> type: seqaijmkl
>
> rows=16490, cols=35937
>
> total: nonzeros=128496, allocated nonzeros=128496
>
> total number of mallocs used during MatSetValues calls=0
>
> not using I-node routines
>
>
>
> --> Solving the system...
>
>
>
> Excitation 1 of 1...
>
>
>
> ================================================
>
> Iterative solve completed in 7435 ms.
>
> CONVERGED: rtol.
>
> Iterations: 72
>
> Final relative residual norm: 9.22287e-07
>
> ================================================
>
> [CPU TIME] System solution: 2.27160000e+02 s.
>
> [WALL TIME] System solution: 7.44387218e+00 s.
>
> However, it seems to me that there were still no MKL outputs even I set
> MKL_VERBOSE to be 1. Although, I think it should be many spmv operations
> when doing KSPSolve(). Do you see the possible reasons?
>
>
>
> SPMV are not reported with MKL_VERBOSE (last I checked), only dense BLAS
> is.
>
>
>
> Thanks,
>
> Pierre
>
>
>
> Thanks,
>
> Yongzhong
>
>
>
>
>
> *From: *Matthew Knepley <knepley at gmail.com>
> *Date: *Saturday, June 22, 2024 at 5:56 PM
> *To: *Yongzhong Li <yongzhong.li at mail.utoronto.ca>
> *Cc: *Junchao Zhang <junchao.zhang at gmail.com>, Pierre Jolivet <
> pierre at joliv.et>, petsc-users at mcs.anl.gov <petsc-users at mcs.anl.gov>
> *Subject: *Re: [petsc-users] [petsc-maint] Assistance Needed with PETSc
> KSPSolve Performance Issue
>
> 你通常不会收到来自 knepley at gmail.com 的电子邮件。了解这一点为什么很重要
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>
> On Sat, Jun 22, 2024 at 5:03 PM Yongzhong Li <
> yongzhong.li at mail.utoronto.ca> wrote:
>
> MKL_VERBOSE=1 ./ex1 matrix nonzeros = 100, allocated nonzeros = 100
> MKL_VERBOSE Intel(R) MKL 2019. 0 Update 4 Product build 20190411 for
> Intel(R) 64 architecture Intel(R) Advanced Vector Extensions 512 (Intel(R)
> AVX-512) with support of Vector
>
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> MKL_VERBOSE=1 ./ex1
>
>
> matrix nonzeros = 100, allocated nonzeros = 100
>
> MKL_VERBOSE Intel(R) MKL 2019.0 Update 4 Product build 20190411 for
> Intel(R) 64 architecture Intel(R) Advanced Vector Extensions 512 (Intel(R)
> AVX-512) with support of Vector Neural Network Instructions enabled
> processors, Lnx 2.50GHz lp64 gnu_thread
>
> MKL_VERBOSE
> ZGEMV(N,10,10,0x7ffd9d7078f0,0x187eb20,10,0x187f7c0,1,0x7ffd9d707900,0x187ff70,1)
> 167.34ms CNR:OFF Dyn:1 FastMM:1 TID:0 NThr:1
>
> MKL_VERBOSE ZSYTRF(L,10,0x1894b50,10,0x1893df0,0x7ffd9d7078c0,-1,0)
> 77.19ms CNR:OFF Dyn:1 FastMM:1 TID:0 NThr:1
>
> MKL_VERBOSE ZSYTRF(L,10,0x1894b50,10,0x1893df0,0x1894490,10,0) 83.97ms
> CNR:OFF Dyn:1 FastMM:1 TID:0 NThr:1
>
> MKL_VERBOSE ZSYTRS(L,10,1,0x1894b50,10,0x1893df0,0x1880720,10,0) 44.94ms
> CNR:OFF Dyn:1 FastMM:1 TID:0 NThr:1
>
> MKL_VERBOSE ZAXPY(10,0x7ffd9d7078f0,0x187f7c0,1,0x1880720,1) 20.72us
> CNR:OFF Dyn:1 FastMM:1 TID:0 NThr:1
>
> MKL_VERBOSE ZSYTRS(L,10,2,0x1894b50,10,0x1893df0,0x187d2a0,10,0) 4.22us
> CNR:OFF Dyn:1 FastMM:1 TID:0 NThr:1
>
> MKL_VERBOSE
> ZGEMM(N,N,10,2,10,0x7ffd9d707790,0x187eb20,10,0x187d2a0,10,0x7ffd9d7077a0,0x1896a70,10)
> 1.41ms CNR:OFF Dyn:1 FastMM:1 TID:0 NThr:1
>
> MKL_VERBOSE ZAXPY(20,0x7ffd9d7078a0,0x1896a70,1,0x187b650,1) 381ns CNR:OFF
> Dyn:1 FastMM:1 TID:0 NThr:1
>
> MKL_VERBOSE ZSYTRF(L,10,0x1894b50,10,0x1893df0,0x7ffd9d707840,-1,0) 742ns
> CNR:OFF Dyn:1 FastMM:1 TID:0 NThr:1
>
> MKL_VERBOSE ZSYTRF(L,10,0x1894b50,10,0x1893df0,0x18951a0,10,0) 4.20us
> CNR:OFF Dyn:1 FastMM:1 TID:0 NThr:1
>
> MKL_VERBOSE ZSYTRS(L,10,1,0x1894b50,10,0x1893df0,0x1880720,10,0) 2.94us
> CNR:OFF Dyn:1 FastMM:1 TID:0 NThr:1
>
> MKL_VERBOSE ZAXPY(10,0x7ffd9d7078f0,0x187f7c0,1,0x1880720,1) 292ns CNR:OFF
> Dyn:1 FastMM:1 TID:0 NThr:1
>
> MKL_VERBOSE
> ZGEMV(N,10,10,0x7ffd9d7078f0,0x187eb20,10,0x187f7c0,1,0x7ffd9d707900,0x187ff70,1)
> 1.17us CNR:OFF Dyn:1 FastMM:1 TID:0 NThr:1
>
> MKL_VERBOSE ZGETRF(10,10,0x1894b50,10,0x1893df0,0) 202.48ms CNR:OFF Dyn:1
> FastMM:1 TID:0 NThr:1
>
> MKL_VERBOSE ZGETRS(N,10,1,0x1894b50,10,0x1893df0,0x1880720,10,0) 20.78ms
> CNR:OFF Dyn:1 FastMM:1 TID:0 NThr:1
>
> MKL_VERBOSE ZAXPY(10,0x7ffd9d7078f0,0x187f7c0,1,0x1880720,1) 954ns CNR:OFF
> Dyn:1 FastMM:1 TID:0 NThr:1
>
> MKL_VERBOSE ZGETRS(N,10,2,0x1894b50,10,0x1893df0,0x187d2a0,10,0) 30.74ms
> CNR:OFF Dyn:1 FastMM:1 TID:0 NThr:1
>
> MKL_VERBOSE
> ZGEMM(N,N,10,2,10,0x7ffd9d707790,0x187eb20,10,0x187d2a0,10,0x7ffd9d7077a0,0x18969c0,10)
> 3.95us CNR:OFF Dyn:1 FastMM:1 TID:0 NThr:1
>
> MKL_VERBOSE ZAXPY(20,0x7ffd9d7078a0,0x18969c0,1,0x187b650,1) 995ns CNR:OFF
> Dyn:1 FastMM:1 TID:0 NThr:1
>
> MKL_VERBOSE ZGETRF(10,10,0x1894b50,10,0x1893df0,0) 4.09us CNR:OFF Dyn:1
> FastMM:1 TID:0 NThr:1
>
> MKL_VERBOSE ZGETRS(N,10,1,0x1894b50,10,0x1893df0,0x1880720,10,0) 3.92us
> CNR:OFF Dyn:1 FastMM:1 TID:0 NThr:1
>
> MKL_VERBOSE ZAXPY(10,0x7ffd9d7078f0,0x187f7c0,1,0x1880720,1) 274ns CNR:OFF
> Dyn:1 FastMM:1 TID:0 NThr:1
>
> MKL_VERBOSE
> ZGEMV(N,15,10,0x7ffd9d7078f0,0x187ec70,15,0x187fc30,1,0x7ffd9d707900,0x1880400,1)
> 1.59us CNR:OFF Dyn:1 FastMM:1 TID:0 NThr:1
>
> MKL_VERBOSE ZGEQRF(15,10,0x1894b40,15,0x1894550,0x7ffd9d707900,-1,0)
> 47.07us CNR:OFF Dyn:1 FastMM:1 TID:0 NThr:1
>
> MKL_VERBOSE ZGEQRF(15,10,0x1894b40,15,0x1894550,0x1895cb0,10,0) 26.62us
> CNR:OFF Dyn:1 FastMM:1 TID:0 NThr:1
>
> MKL_VERBOSE
> ZUNMQR(L,C,15,1,10,0x1894b40,15,0x1894550,0x1895b00,15,0x7ffd9d7078b0,-1,0)
> 35.32us CNR:OFF Dyn:1 FastMM:1 TID:0 NThr:1
>
> MKL_VERBOSE
> ZUNMQR(L,C,15,1,10,0x1894b40,15,0x1894550,0x1895b00,15,0x1895cb0,10,0)
> 42.33ms CNR:OFF Dyn:1 FastMM:1 TID:0 NThr:1
>
> MKL_VERBOSE ZTRTRS(U,N,N,10,1,0x1894b40,15,0x1895b00,15,0) 16.11us CNR:OFF
> Dyn:1 FastMM:1 TID:0 NThr:1
>
> MKL_VERBOSE ZAXPY(10,0x7ffd9d7078f0,0x187fc30,1,0x1880c70,1) 395ns CNR:OFF
> Dyn:1 FastMM:1 TID:0 NThr:1
>
> MKL_VERBOSE
> ZGEMM(N,N,15,2,10,0x7ffd9d707790,0x187ec70,15,0x187d310,10,0x7ffd9d7077a0,0x187b5b0,15)
> 3.22us CNR:OFF Dyn:1 FastMM:1 TID:0 NThr:1
>
> MKL_VERBOSE
> ZUNMQR(L,C,15,2,10,0x1894b40,15,0x1894550,0x1897760,15,0x7ffd9d7078c0,-1,0)
> 730ns CNR:OFF Dyn:1 FastMM:1 TID:0 NThr:1
>
> MKL_VERBOSE
> ZUNMQR(L,C,15,2,10,0x1894b40,15,0x1894550,0x1897760,15,0x1895cb0,10,0)
> 4.42us CNR:OFF Dyn:1 FastMM:1 TID:0 NThr:1
>
> MKL_VERBOSE ZTRTRS(U,N,N,10,2,0x1894b40,15,0x1897760,15,0) 5.96us CNR:OFF
> Dyn:1 FastMM:1 TID:0 NThr:1
>
> MKL_VERBOSE ZAXPY(20,0x7ffd9d7078a0,0x187d310,1,0x1897610,1) 222ns CNR:OFF
> Dyn:1 FastMM:1 TID:0 NThr:1
>
> MKL_VERBOSE ZGEQRF(15,10,0x1894b40,15,0x18954b0,0x7ffd9d707820,-1,0) 685ns
> CNR:OFF Dyn:1 FastMM:1 TID:0 NThr:1
>
> MKL_VERBOSE ZGEQRF(15,10,0x1894b40,15,0x18954b0,0x1895d60,10,0) 6.11us
> CNR:OFF Dyn:1 FastMM:1 TID:0 NThr:1
>
> MKL_VERBOSE
> ZUNMQR(L,C,15,1,10,0x1894b40,15,0x18954b0,0x1895bb0,15,0x7ffd9d7078b0,-1,0)
> 390ns CNR:OFF Dyn:1 FastMM:1 TID:0 NThr:1
>
> MKL_VERBOSE
> ZUNMQR(L,C,15,1,10,0x1894b40,15,0x18954b0,0x1895bb0,15,0x1895d60,10,0)
> 3.09us CNR:OFF Dyn:1 FastMM:1 TID:0 NThr:1
>
> MKL_VERBOSE ZTRTRS(U,N,N,10,1,0x1894b40,15,0x1895bb0,15,0) 1.05us CNR:OFF
> Dyn:1 FastMM:1 TID:0 NThr:1
>
> MKL_VERBOSE ZAXPY(10,0x7ffd9d7078f0,0x187fc30,1,0x1880c70,1) 257ns CNR:OFF
> Dyn:1 FastMM:1 TID:0 NThr:1
>
> Yes, for petsc example, there are MKL outputs, but for my own program. All
> I did is to change the matrix type from MATAIJ to MATAIJMKL to get
> optimized performance for spmv from MKL. Should I expect to see any MKL
> outputs in this case?
>
>
>
> Are you sure that the type changed? You can MatView() the matrix with
> format ascii_info to see.
>
>
>
> Thanks,
>
>
>
> Matt
>
>
>
>
>
> Thanks,
>
> Yongzhong
>
>
>
> *From: *Junchao Zhang <junchao.zhang at gmail.com>
> *Date: *Saturday, June 22, 2024 at 9:40 AM
> *To: *Yongzhong Li <yongzhong.li at mail.utoronto.ca>
> *Cc: *Pierre Jolivet <pierre at joliv.et>, petsc-users at mcs.anl.gov <
> petsc-users at mcs.anl.gov>
> *Subject: *Re: [petsc-users] [petsc-maint] Assistance Needed with PETSc
> KSPSolve Performance Issue
>
> No, you don't. It is strange. Perhaps you can you run a petsc example
> first and see if MKL is really used
>
> $ cd src/mat/tests
>
> $ make ex1
>
> $ MKL_VERBOSE=1 ./ex1
>
>
> --Junchao Zhang
>
>
>
>
>
> On Fri, Jun 21, 2024 at 4:03 PM Yongzhong Li <
> yongzhong.li at mail.utoronto.ca> wrote:
>
> I am using
>
> export MKL_VERBOSE=1
>
> ./xx
>
> in the bash file, do I have to use - ksp_converged_reason?
>
> Thanks,
>
> Yongzhong
>
>
>
> *From: *Pierre Jolivet <pierre at joliv.et>
> *Date: *Friday, June 21, 2024 at 1:47 PM
> *To: *Yongzhong Li <yongzhong.li at mail.utoronto.ca>
> *Cc: *Junchao Zhang <junchao.zhang at gmail.com>, petsc-users at mcs.anl.gov <
> petsc-users at mcs.anl.gov>
> *Subject: *Re: [petsc-users] [petsc-maint] Assistance Needed with PETSc
> KSPSolve Performance Issue
>
> 你通常不会收到来自 pierre at joliv.et 的电子邮件。了解这一点为什么很重要
> <https://urldefense.us/v3/__https://aka.ms/LearnAboutSenderIdentification__;!!G_uCfscf7eWS!flsZMI97ne0yyxHhLda3hROB9qsgstuZS-jPinxGIzFCCSdn1ujdoMR8dyz-5_kVqqMM-12Lt0dTdjKrx3wXhHZmBhNydvFQeSY$>
>
> How do you set the variable?
>
>
>
> $ MKL_VERBOSE=1 ./ex1 -ksp_converged_reason
>
> MKL_VERBOSE oneMKL 2024.0 Update 1 Product build 20240215 for Intel(R) 64
> architecture Intel(R) Advanced Vector Extensions 2 (Intel(R) AVX2) enabled
> processors, Lnx 2.80GHz lp64 intel_thread
>
> MKL_VERBOSE DDOT(10,0x22127c0,1,0x22127c0,1) 2.02ms CNR:OFF Dyn:1 FastMM:1
> TID:0 NThr:1
>
> MKL_VERBOSE DSCAL(10,0x7ffc9fb4ff08,0x22127c0,1) 12.67us CNR:OFF Dyn:1
> FastMM:1 TID:0 NThr:1
>
> MKL_VERBOSE DDOT(10,0x22127c0,1,0x2212840,1) 1.52us CNR:OFF Dyn:1 FastMM:1
> TID:0 NThr:1
>
> MKL_VERBOSE DDOT(10,0x2212840,1,0x2212840,1) 167ns CNR:OFF Dyn:1 FastMM:1
> TID:0 NThr:1
>
> [...]
>
>
>
> On 21 Jun 2024, at 7:37 PM, Yongzhong Li <yongzhong.li at mail.utoronto.ca>
> wrote:
>
>
>
> This Message Is From an External Sender
>
> This message came from outside your organization.
>
> Hello all,
>
> I set MKL_VERBOSE = 1, but observed no print output specific to the use of
> MKL. Does PETSc enable this verbose output?
>
> Best,
>
> Yongzhong
>
>
>
> *From: *Pierre Jolivet <pierre at joliv.et>
> *Date: *Friday, June 21, 2024 at 1:36 AM
> *To: *Junchao Zhang <junchao.zhang at gmail.com>
> *Cc: *Yongzhong Li <yongzhong.li at mail.utoronto.ca>,
> petsc-users at mcs.anl.gov <petsc-users at mcs.anl.gov>
> *Subject: *Re: [petsc-users] [petsc-maint] Assistance Needed with PETSc
> KSPSolve Performance Issue
>
> 你通常不会收到来自 pierre at joliv.et 的电子邮件。了解这一点为什么很重要
> <https://urldefense.us/v3/__https://aka.ms/LearnAboutSenderIdentification__;!!G_uCfscf7eWS!eXBeeIXo9Yqgp2nypqwKYimLnGBZXnF4dXxgLM1UoOIO6n8nt3XlfgjVWLPWJh4UOa5NNpx-nrJb_H828XRQKUREfR2m69oCbxI$>
>
>
>
>
>
> On 21 Jun 2024, at 6:42 AM, Junchao Zhang <junchao.zhang at gmail.com> wrote:
>
>
>
> This Message Is From an External Sender
>
> This message came from outside your organization.
>
> I remember there are some MKL env vars to print MKL routines called.
>
>
>
> The environment variable is MKL_VERBOSE
>
>
>
> Thanks,
>
> Pierre
>
>
>
> Maybe we can try it to see what MKL routines are really used and then we
> can understand why some petsc functions did not speed up
>
>
> --Junchao Zhang
>
>
>
>
>
> On Thu, Jun 20, 2024 at 10:39 PM Yongzhong Li <
> yongzhong.li at mail.utoronto.ca> wrote:
>
> *This Message Is From an External Sender*
>
> This message came from outside your organization.
>
>
>
> Hi Barry, sorry for my last results. I didn’t fully understand the stage
> profiling and logging in PETSc, now I only record KSPSolve() stage of my
> program. Some sample codes are as follow,
>
> // Static variable to keep track of the stage counter
>
> static int stageCounter = 1;
>
>
>
> // Generate a unique stage name
>
> std::ostringstream oss;
>
> oss << "Stage " << stageCounter << " of Code";
>
> std::string stageName = oss.str();
>
>
>
> // Register the stage
>
> PetscLogStage stagenum;
>
>
>
> PetscLogStageRegister(stageName.c_str(), &stagenum);
>
> PetscLogStagePush(stagenum);
>
>
>
> *KSPSolve(*ksp_ptr, b, x);*
>
>
>
> PetscLogStagePop();
>
> stageCounter++;
>
> I have attached my new logging results, there are 1 main stage and 4 other
> stages where each one is KSPSolve() call.
>
> To provide some additional backgrounds, if you recall, I have been trying
> to get efficient iterative solution using multithreading. I found out by
> compiling PETSc with Intel MKL library instead of OpenBLAS, I am able to
> perform sparse matrix-vector multiplication faster, I am using
> MATSEQAIJMKL. This makes the shell matrix vector product in each iteration
> scale well with the #of threads. However, I found out the total GMERS solve
> time (~KSPSolve() time) is not scaling well the #of threads.
>
> From the logging results I learned that when performing KSPSolve(), there
> are some CPU overheads in PCApply() and KSPGMERSOrthog(). I ran my programs
> using different number of threads and plotted the time consumption for
> PCApply() and KSPGMERSOrthog() against #of thread. I found out these two
> operations are not scaling with the threads at all! My results are attached
> as the pdf to give you a clear view.
>
> My questions is,
>
> From my understanding, in PCApply, MatSolve() is involved,
> KSPGMERSOrthog() will have many vector operations, so why these two parts
> can’t scale well with the # of threads when the intel MKL library is linked?
>
> Thank you,
> Yongzhong
>
>
>
> *From: *Barry Smith <bsmith at petsc.dev>
> *Date: *Friday, June 14, 2024 at 11:36 AM
> *To: *Yongzhong Li <yongzhong.li at mail.utoronto.ca>
> *Cc: *petsc-users at mcs.anl.gov <petsc-users at mcs.anl.gov>,
> petsc-maint at mcs.anl.gov <petsc-maint at mcs.anl.gov>, Piero Triverio <
> piero.triverio at utoronto.ca>
> *Subject: *Re: [petsc-maint] Assistance Needed with PETSc KSPSolve
> Performance Issue
>
>
>
> I am a bit confused. Without the initial guess computation, there are
> still a bunch of events I don't understand
>
>
>
> MatTranspose 79 1.0 4.0598e+01 1.0 0.00e+00 0.0 0.0e+00 0.0e+00
> 0.0e+00 0 0 0 0 0 0 0 0 0 0 0
>
> MatMatMultSym 110 1.0 1.7419e+02 1.0 0.00e+00 0.0 0.0e+00 0.0e+00
> 0.0e+00 1 0 0 0 0 1 0 0 0 0 0
>
> MatMatMultNum 90 1.0 1.2640e+02 1.0 0.00e+00 0.0 0.0e+00 0.0e+00
> 0.0e+00 1 0 0 0 0 1 0 0 0 0 0
>
> MatMatMatMultSym 20 1.0 1.3049e+02 1.0 0.00e+00 0.0 0.0e+00 0.0e+00
> 0.0e+00 1 0 0 0 0 1 0 0 0 0 0
>
> MatRARtSym 25 1.0 1.2492e+02 1.0 0.00e+00 0.0 0.0e+00 0.0e+00
> 0.0e+00 1 0 0 0 0 1 0 0 0 0 0
>
> MatMatTrnMultSym 25 1.0 8.8265e+01 1.0 0.00e+00 0.0 0.0e+00 0.0e+00
> 0.0e+00 0 0 0 0 0 0 0 0 0 0 0
>
> MatMatTrnMultNum 25 1.0 2.4820e+02 1.0 6.83e+10 1.0 0.0e+00 0.0e+00
> 0.0e+00 1 0 0 0 0 1 0 0 0 0 275
>
> MatTrnMatMultSym 10 1.0 7.2984e-01 1.0 0.00e+00 0.0 0.0e+00 0.0e+00
> 0.0e+00 0 0 0 0 0 0 0 0 0 0 0
>
> MatTrnMatMultNum 10 1.0 9.3128e-01 1.0 0.00e+00 0.0 0.0e+00 0.0e+00
> 0.0e+00 0 0 0 0 0 0 0 0 0 0 0
>
>
>
> in addition there are many more VecMAXPY then VecMDot (in GMRES they are
> each done the same number of times)
>
>
>
> VecMDot 5588 1.0 1.7183e+03 1.0 2.06e+13 1.0 0.0e+00 0.0e+00
> 0.0e+00 8 10 0 0 0 8 10 0 0 0 12016
>
> VecMAXPY 22412 1.0 8.4898e+03 1.0 4.17e+13 1.0 0.0e+00 0.0e+00
> 0.0e+00 39 20 0 0 0 39 20 0 0 0 4913
>
>
>
> Finally there are a huge number of
>
>
>
> MatMultAdd 258048 1.0 1.4178e+03 1.0 6.10e+13 1.0 0.0e+00 0.0e+00
> 0.0e+00 7 29 0 0 0 7 29 0 0 0 43025
>
>
>
> Are you making calls to all these routines? Are you doing this inside your
> MatMult() or before you call KSPSolve?
>
>
>
> The reason I wanted you to make a simpler run without the initial guess
> code is that your events are far more complicated than would be produced by
> GMRES alone so it is not possible to understand the behavior you are seeing
> without fully understanding all the events happening in the code.
>
>
>
> Barry
>
>
>
>
>
> On Jun 14, 2024, at 1:19 AM, Yongzhong Li <yongzhong.li at mail.utoronto.ca>
> wrote:
>
>
>
> Thanks, I have attached the results without using any KSPGuess. At low
> frequency, the iteration steps are quite close to the one with KSPGuess,
> specifically
>
> KSPGuess Object: 1 MPI process
>
> type: fischer
>
> Model 1, size 200
>
> However, I found at higher frequency, the # of iteration steps are
> significant higher than the one with KSPGuess, I have attahced both of the
> results for your reference.
>
> Moreover, could I ask why the one without the KSPGuess options can be used
> for a baseline comparsion? What are we comparing here? How does it relate
> to the performance issue/bottleneck I found? “*I have noticed that the
> time taken by **KSPSolve** is **almost two times **greater than the CPU
> time for matrix-vector product multiplied by the number of iteration*”
>
> Thank you!
> Yongzhong
>
>
>
> *From: *Barry Smith <bsmith at petsc.dev>
> *Date: *Thursday, June 13, 2024 at 2:14 PM
> *To: *Yongzhong Li <yongzhong.li at mail.utoronto.ca>
> *Cc: *petsc-users at mcs.anl.gov <petsc-users at mcs.anl.gov>,
> petsc-maint at mcs.anl.gov <petsc-maint at mcs.anl.gov>, Piero Triverio <
> piero.triverio at utoronto.ca>
> *Subject: *Re: [petsc-maint] Assistance Needed with PETSc KSPSolve
> Performance Issue
>
>
>
> Can you please run the same thing without the KSPGuess option(s) for a
> baseline comparison?
>
>
>
> Thanks
>
>
>
> Barry
>
>
>
> On Jun 13, 2024, at 1:27 PM, Yongzhong Li <yongzhong.li at mail.utoronto.ca>
> wrote:
>
>
>
> This Message Is From an External Sender
>
> This message came from outside your organization.
>
> Hi Matt,
>
> I have rerun the program with the keys you provided. The system output
> when performing ksp solve and the final petsc log output were stored in a
> .txt file attached for your reference.
>
> Thanks!
> Yongzhong
>
>
>
> *From: *Matthew Knepley <knepley at gmail.com>
> *Date: *Wednesday, June 12, 2024 at 6:46 PM
> *To: *Yongzhong Li <yongzhong.li at mail.utoronto.ca>
> *Cc: *petsc-users at mcs.anl.gov <petsc-users at mcs.anl.gov>,
> petsc-maint at mcs.anl.gov <petsc-maint at mcs.anl.gov>, Piero Triverio <
> piero.triverio at utoronto.ca>
> *Subject: *Re: [petsc-maint] Assistance Needed with PETSc KSPSolve
> Performance Issue
>
> 你通常不会收到来自 knepley at gmail.com 的电子邮件。了解这一点为什么很重要
> <https://urldefense.us/v3/__https://aka.ms/LearnAboutSenderIdentification__;!!G_uCfscf7eWS!djGfJnEhNJROfsMsBJy5u_KoRKbug55xZ64oHKUFnH2cWku_Th1hwt4TDdoMd8pWYVDzJeqJslMNZwpO3y0Et94d31qk-oCEwo4$>
>
> On Wed, Jun 12, 2024 at 6:36 PM Yongzhong Li <
> yongzhong.li at mail.utoronto.ca> wrote:
>
> Dear PETSc’s developers, I hope this email finds you well. I am currently
> working on a project using PETSc and have encountered a performance issue
> with the KSPSolve function. Specifically, I have noticed that the time
> taken by KSPSolve is
>
> ZjQcmQRYFpfptBannerStart
>
> *This Message Is From an External Sender*
>
> This message came from outside your organization.
>
>
>
> ZjQcmQRYFpfptBannerEnd
>
> Dear PETSc’s developers,
>
> I hope this email finds you well.
>
> I am currently working on a project using PETSc and have encountered a
> performance issue with the KSPSolve function. Specifically, *I have
> noticed that the time taken by **KSPSolve** is **almost two times **greater
> than the CPU time for matrix-vector product multiplied by the number of
> iteration steps*. I use C++ chrono to record CPU time.
>
> For context, I am using a shell system matrix A. Despite my efforts to
> parallelize the matrix-vector product (Ax), the overall solve time
> remains higher than the matrix vector product per iteration indicates
> when multiple threads were used. Here are a few details of my setup:
>
> - *Matrix Type*: Shell system matrix
> - *Preconditioner*: Shell PC
> - *Parallel Environment*: Using Intel MKL as PETSc’s BLAS/LAPACK
> library, multithreading is enabled
>
> I have considered several potential reasons, such as preconditioner setup,
> additional solver operations, and the inherent overhead of using a shell
> system matrix. *However, since KSPSolve is a high-level API, I have been
> unable to pinpoint the exact cause of the increased solve time.*
>
> Have you observed the same issue? Could you please provide some experience
> on how to diagnose and address this performance discrepancy? Any
> insights or recommendations you could offer would be greatly appreciated.
>
>
>
> For any performance question like this, we need to see the output of your
> code run with
>
>
>
> -ksp_view -ksp_monitor_true_residual -ksp_converged_reason -log_view
>
>
>
> Thanks,
>
>
>
> Matt
>
>
>
> Thank you for your time and assistance.
>
> Best regards,
>
> Yongzhong
>
> -----------------------------------------------------------
>
> *Yongzhong Li*
>
> PhD student | Electromagnetics Group
>
> Department of Electrical & Computer Engineering
>
> University of Toronto
>
> https://urldefense.us/v3/__http://www.modelics.org__;!!G_uCfscf7eWS!aQJpmm5W6l6FUiumnIPmkouzwzNUfx-Dyq04i1O2KS_InQGk6qjI7wUir0Hx6QEUQE2AMiJDsez3x3b414pj$
> <https://urldefense.us/v3/__http://www.modelics.org__;!!G_uCfscf7eWS!cuLttMJEcegaqu461Bt4QLsO4fASfLM5vjRbtyNhWJQiInbjgNwkGNdkFE1ebSbFjOUatYB0-jd2yQWMWzqkDFFjwMvNl3ZKAr8$>
>
>
>
>
>
>
> --
>
> What most experimenters take for granted before they begin their
> experiments is infinitely more interesting than any results to which their
> experiments lead.
> -- Norbert Wiener
>
>
>
> https://urldefense.us/v3/__https://www.cse.buffalo.edu/*knepley/__;fg!!G_uCfscf7eWS!aQJpmm5W6l6FUiumnIPmkouzwzNUfx-Dyq04i1O2KS_InQGk6qjI7wUir0Hx6QEUQE2AMiJDsez3x7MKsDeh$
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>
> <ksp_petsc_log.txt>
>
>
>
> <ksp_petsc_log.txt><ksp_petsc_log_noguess.txt>
>
>
>
>
>
>
> --
>
> 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://urldefense.us/v3/__https://www.cse.buffalo.edu/*knepley/__;fg!!G_uCfscf7eWS!aQJpmm5W6l6FUiumnIPmkouzwzNUfx-Dyq04i1O2KS_InQGk6qjI7wUir0Hx6QEUQE2AMiJDsez3x7MKsDeh$
> <https://urldefense.us/v3/__http://www.cse.buffalo.edu/*knepley/__;fg!!G_uCfscf7eWS!fVvbGldqcUV5ju4jpu5oGmt-VjITi5JpCJzhHxpbgsERLVYZzglpxKOOyrBRGxjRxp7vWHwt3SnINFOQErR1Z8kcDcf3cNeD9Gw$>
>
>
>
--
What most experimenters take for granted before they begin their
experiments is infinitely more interesting than any results to which their
experiments lead.
-- Norbert Wiener
https://urldefense.us/v3/__https://www.cse.buffalo.edu/*knepley/__;fg!!G_uCfscf7eWS!aQJpmm5W6l6FUiumnIPmkouzwzNUfx-Dyq04i1O2KS_InQGk6qjI7wUir0Hx6QEUQE2AMiJDsez3x7MKsDeh$ <https://urldefense.us/v3/__http://www.cse.buffalo.edu/*knepley/__;fg!!G_uCfscf7eWS!aQJpmm5W6l6FUiumnIPmkouzwzNUfx-Dyq04i1O2KS_InQGk6qjI7wUir0Hx6QEUQE2AMiJDsez3x2Os2C2d$ >
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