On Sat, Jun 22, 2024 at 5:03 PM Yongzhong Li <yongzhong...@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
> ZjQcmQRYFpfptBannerStart
> This Message Is From an External Sender
> This message came from outside your organization.
>
> ZjQcmQRYFpfptBannerEnd
>
> 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.zh...@gmail.com>
> *Date: *Saturday, June 22, 2024 at 9:40 AM
> *To: *Yongzhong Li <yongzhong...@mail.utoronto.ca>
> *Cc: *Pierre Jolivet <pie...@joliv.et>, petsc-users@mcs.anl.gov <
> petsc-users@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...@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 <pie...@joliv.et>
> *Date: *Friday, June 21, 2024 at 1:47 PM
> *To: *Yongzhong Li <yongzhong...@mail.utoronto.ca>
> *Cc: *Junchao Zhang <junchao.zh...@gmail.com>, petsc-users@mcs.anl.gov <
> petsc-users@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 pie...@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...@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 <pie...@joliv.et>
> *Date: *Friday, June 21, 2024 at 1:36 AM
> *To: *Junchao Zhang <junchao.zh...@gmail.com>
> *Cc: *Yongzhong Li <yongzhong...@mail.utoronto.ca>,
> petsc-users@mcs.anl.gov <petsc-users@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 pie...@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.zh...@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...@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 <bsm...@petsc.dev>
> *Date: *Friday, June 14, 2024 at 11:36 AM
> *To: *Yongzhong Li <yongzhong...@mail.utoronto.ca>
> *Cc: *petsc-users@mcs.anl.gov <petsc-users@mcs.anl.gov>,
> petsc-ma...@mcs.anl.gov <petsc-ma...@mcs.anl.gov>, Piero Triverio <
> piero.trive...@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...@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 <bsm...@petsc.dev>
> *Date: *Thursday, June 13, 2024 at 2:14 PM
> *To: *Yongzhong Li <yongzhong...@mail.utoronto.ca>
> *Cc: *petsc-users@mcs.anl.gov <petsc-users@mcs.anl.gov>,
> petsc-ma...@mcs.anl.gov <petsc-ma...@mcs.anl.gov>, Piero Triverio <
> piero.trive...@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...@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 <knep...@gmail.com>
> *Date: *Wednesday, June 12, 2024 at 6:46 PM
> *To: *Yongzhong Li <yongzhong...@mail.utoronto.ca>
> *Cc: *petsc-users@mcs.anl.gov <petsc-users@mcs.anl.gov>,
> petsc-ma...@mcs.anl.gov <petsc-ma...@mcs.anl.gov>, Piero Triverio <
> piero.trive...@utoronto.ca>
> *Subject: *Re: [petsc-maint] Assistance Needed with PETSc KSPSolve
> Performance Issue
>
> 你通常不会收到来自 knep...@gmail.com 的电子邮件。了解这一点为什么很重要
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>
> On Wed, Jun 12, 2024 at 6:36 PM Yongzhong Li <
> yongzhong...@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
>
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> 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!bDAP9_cc4kxQoG-PxDlkBdIp_YAhb2swSdTCmldNce2eI4DO6YATl5KED0zpX5PC2AEvY1tq0jjSK32rn8gN$
>
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>
>
>
>
>
>
> --
>
> 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!bDAP9_cc4kxQoG-PxDlkBdIp_YAhb2swSdTCmldNce2eI4DO6YATl5KED0zpX5PC2AEvY1tq0jjSK2axnx8f$
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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!bDAP9_cc4kxQoG-PxDlkBdIp_YAhb2swSdTCmldNce2eI4DO6YATl5KED0zpX5PC2AEvY1tq0jjSK2axnx8f$
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>
