PANUA-PARDISO 8.0 was released in February 2023. It contains full support of multi-threaded Schur-complement computations, parallel selected inversion, incremental updates, and many others accelerations. Some of the new features have been used, e.g., in the following papers:

• C. Alappat, G. Hager, O. Schenk, J. Thies, A. Basermann, A. Bischop, H. Fehske, G. Wellein, A Recursive Algebraic Coloring Technique for Hardware-Efficient Symmetric Sparse Matrix-Vector Multiplication, ACM Transactions on Parallel Computing, Vol. 7, No. 3(19), 2020.
• M. Bollhöfer, O. Schenk , R. Janalik, S. Hamm, K. Gullapalli, State-of-The-Art Sparse Direct Solvers, Parallel Algorithms in Computational Science and Engineering. Modeling and Simulation in Science, Engineering and Technology, 1-32, Birkhäuser, 2020.
• M. Bollhöfer, A. Eftekhari, S. Scheidegger, and O. Schenk, Large-Scale Sparse Inverse Covariance Matrix Estimation, SIAM J. Sci. Comput., 41(1), A380–A401, 2019.

Additional publications related to PARDISO are available on the webpage of the research group of Prof. Olaf Schenk, Advanced Computing Laboratory, Institute of Computing, USI Lugano, Switzerland.

Important: Please note that the Intel MKL version of PARDISO is based on our version from 2006 and that a lot of new features and improvements of PARDISO are not available in the Intel MKL library.

PARDISO 8.0 is benchmarked against Intel MKL PARDISO version 2020 on up to 16 cores on an Intel Xeon E7-4880. The matrices are from NXP's industrial circuit simulator Mica. The plots shows the performance acceleration for the factorization and solution phase against MKL PARDISO.

PARDISO 8.0 is benchmarked against Intel MKL PARDISO version 2020 on up to 32 cores on an Intel Xeon Intel E5-2650 with 2.30GHz architecture. The matrices are from Silvaco industrial circuit simulator. The plots shows the performance acceleration for the factorization and solution phase against MKL PARDISO.

Regression analysis on the k-rank update LU factorization in PARDISO. The scatter plot shows the number of k-rank updates and the corresponding factorization time in milliseconds. The regression analysis cleary demonstates a linear trend both for the single and the multiple core version. The dashed line shows the time for the full factorization.