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I have added a few sparse benchmarks to NPBench:

  • Banded Matrix-Matrix-Transposed multiplication (A * B * A^T). NumPy already had an implementation for banded matrix multiplication, but it required the data to be in dense format (2D numpy arrays).
  • Conjugate Gradient Method for CSR matrices.
  • BiConjugate Gradient Method for CSR matrices.
  • BiConjugate Stabilized Gradient Method for CSR matrices.
  • Minimum Residual Method for CSR matrices.
  • Generalized Minimum Residual Method for CSR matrices.
  • CSR Matrix-Matrix multiplication.

I have added a few sparse benchmarks to NPBench:
- Banded Matrix-Matrix-Transposed multiplication (A * B * A^T). NumPy already had an implementation for banded matrix multiplication, but it required the data to be in dense format (2D numpy arrays).
- Conjugate Gradient Method for CSR matrices.
- BiConjugate Gradient Method for CSR matrices.
- BiConjugate Stabilized Gradient Method for CSR matrices.
- Minimum Residual Method for CSR matrices.
- Generalized Minimum Residual Method for CSR matrices.
- CSR Matrix-Matrix multiplication.
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