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39 lines
1.3 KiB
Plaintext
39 lines
1.3 KiB
Plaintext
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GPU Device 0: "Hopper" with compute capability 9.0
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Using default input file [../../../../Samples/4_CUDA_Libraries/cuSolverSp_LinearSolver/lap2D_5pt_n100.mtx]
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step 1: read matrix market format
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sparse matrix A is 10000 x 10000 with 49600 nonzeros, base=1
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step 2: reorder the matrix A to minimize zero fill-in
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if the user choose a reordering by -P=symrcm, -P=symamd or -P=metis
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step 2.1: no reordering is chosen, Q = 0:n-1
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step 2.2: B = A(Q,Q)
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step 3: b(j) = 1 + j/n
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step 4: prepare data on device
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step 5: solve A*x = b on CPU
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step 6: evaluate residual r = b - A*x (result on CPU)
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(CPU) |b - A*x| = 5.393685E-12
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(CPU) |A| = 8.000000E+00
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(CPU) |x| = 1.136492E+03
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(CPU) |b| = 1.999900E+00
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(CPU) |b - A*x|/(|A|*|x| + |b|) = 5.931079E-16
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step 7: solve A*x = b on GPU
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step 8: evaluate residual r = b - A*x (result on GPU)
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(GPU) |b - A*x| = 1.970424E-12
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(GPU) |A| = 8.000000E+00
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(GPU) |x| = 1.136492E+03
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(GPU) |b| = 1.999900E+00
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(GPU) |b - A*x|/(|A|*|x| + |b|) = 2.166745E-16
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timing chol: CPU = 0.097956 sec , GPU = 0.103812 sec
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show last 10 elements of solution vector (GPU)
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consistent result for different reordering and solver
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x[9990] = 3.000016E+01
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x[9991] = 2.807343E+01
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x[9992] = 2.601354E+01
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x[9993] = 2.380285E+01
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x[9994] = 2.141866E+01
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x[9995] = 1.883070E+01
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x[9996] = 1.599668E+01
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x[9997] = 1.285365E+01
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x[9998] = 9.299423E+00
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x[9999] = 5.147265E+00
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