Add Conjugate Gradient example to benchmarks #1599
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| static array A; | ||
| static array spA; // Sparse A | ||
| static array x0; |
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this looks too similar to a hex number.
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x0 is a mathematical notation used in conjugate gradient.
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@shehzan10 FYI, try to use X0 in such cases.
| array r = b - matmul(A, x); | ||
| array p = r; | ||
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| for (int i = 0; i < maxIter; ++i) { |
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doesn't the timeit function execute this multiple times anyway?
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This is not for timing, conjugate gradient is an iterative solver.
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Right. I don't know what I was thinking.
| x = x + tile(alpha, Ap.dims())*p; | ||
| array beta_num = dot(r, r); | ||
| array beta = beta_num/alpha_num; | ||
| p = r + tile(beta, p.dims())*p; |
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@umar456 These expressions are not equivalent. We want something like this p = r + scalar*p.
| array alpha_den = dot(p, Ap); | ||
| array alpha = alpha_num/alpha_den; | ||
| r = r - tile(alpha, Ap.dims())*Ap; | ||
| x = x + tile(alpha, Ap.dims())*p; |
| array alpha_num = dot(r, r); | ||
| array alpha_den = dot(p, Ap); | ||
| array alpha = alpha_num/alpha_den; | ||
| r = r - tile(alpha, Ap.dims())*Ap; |
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r -= tile(alpha, Ap.dims())*Ap;
Compare the performance and memory usage of sparse vs dense using conjugate gradient example
Compare the performance and memory usage of sparse vs dense using conjugate
gradient example
[skip arrayfire ci]