Need some help on weird outputs of the benchmark demo. about cktso HOT 10 CLOSED

PS. many diagonal elements are zero valued.

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It looks that this is not a problem of tuning the solver. There is some error and the entire solver process is not performed at all. The reported times are all 0 and values are random. Please check the return value of CKTSO_Analyze.

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The return value of CKTSO_Analyze = -3

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Our matrix data are in matrix market file format with matrix market format
"%%MatrixMarket matrix coordinate real general"

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-3 means invalid matrix... does your matrix have duplicated entries(for example, you have two ai[i] of same ai[i] value and the double values of two ax[i] need to be accumulated, this case is not allowed in CKTSO)? This is the most possible reason. Other reasons are all related to value out of range or matrix singular (including ap[0]!=0, ap[n]<=0, ap[n]<n, any ap[i]<0, any ap[i]>ap[i+1], any ai[i]<0, or any ai[i]>=n).

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another reason may be in the read code of mtx file. the code provided in the demos may not handle any case. they are simple and just provided for demo purpose. you may check if the read was correct or use you own read code.

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Doctor Chen, thank you for your kindness help. The real problem is the duplicated entries. I fixed the bug and everything just worked fine. Since many of these matrix files are dumped for C or C++ scientific computation libraries to assemble a matrix in some so called "Add_Values" mode, it is very common to come into such a situation, i.e., in these libraries duplicate values will be accumulated automatically. I suggest, in my humble opinion, CKTSO could provide a simple tool to check and transform such "problematic" matrix market files into good ones.

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Yes, this is a practical requirement in some applications. Actually we already have a simple internal tool that can remove duplicated entries. It needs to be called before every factorization. It leads to some additional latency and memory usage, especially when the matrix is very sparse. I am now thinking about how to integrate this funtion into CKTSO to eliminate these overheads.
I have q question about your case. You mentioned that KLU and PARDISO can solve your matrices. But KLU does not allow duplicated entries either (I did not check PARDISO carefully). How did you handle duplicated entries in KLU?

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Well the answer is quite simple, both KLU and MKL PARDISO were called using PETSc APIs, the matrix was assembled using PETSc's own "Add_values-like" APIs.

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PETSc matrix APIs handle these duplicate entries automatically.

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